2018 |
Cintrano, Christian; Chicano, Francisco; Stützle, Thomas; %editor="Herrera, Francisco Enrique Alba"; Damas, Sergio; Montes, Rosana; Alonso, Sergio; Cordón, Óscar; González, Antonio; Troncoso, Alicia Studying Solutions of the p-Median Problem for the Location of Public Bike Stations Inproceedings Advances in Artificial Intelligence, pp. 198–208, Springer International Publishing, Cham, 2018, ISBN: 978-3-030-00374-6. @inproceedings{10.1007/978-3-030-00374-6_19, title = {Studying Solutions of the p-Median Problem for the Location of Public Bike Stations}, author = {Christian Cintrano and Francisco Chicano and Thomas Stützle and Francisco Enrique Alba" %editor="Herrera and Sergio Damas and Rosana Montes and Sergio Alonso and Óscar Cordón and Antonio González and Alicia Troncoso}, isbn = {978-3-030-00374-6}, year = {2018}, date = {2018-01-01}, booktitle = {Advances in Artificial Intelligence}, pages = {198--208}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {The use of bicycles as a means of transport is becoming more and more popular today, especially in urban areas, to avoid the disadvantages of individual car traffic. In fact, city managers react to this trend and actively promote the use of bicycles by providing a network of bicycles for public use and stations where they can be stored. Establishing such a network involves the task of finding best locations for stations, which is, however, not a trivial task. In this work, we examine models to determine the best location of bike stations so that citizens will travel the shortest distance possible to one of them. Based on real data from the city of Malaga, we formulate our problem as a p-median problem and solve it with a variable neighborhood search algorithm that was automatically configured with irace. We compare the locations proposed by the algorithm with the real ones used currently by the city council. We also study where new locations should be placed if the network grows.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } The use of bicycles as a means of transport is becoming more and more popular today, especially in urban areas, to avoid the disadvantages of individual car traffic. In fact, city managers react to this trend and actively promote the use of bicycles by providing a network of bicycles for public use and stations where they can be stored. Establishing such a network involves the task of finding best locations for stations, which is, however, not a trivial task. In this work, we examine models to determine the best location of bike stations so that citizens will travel the shortest distance possible to one of them. Based on real data from the city of Malaga, we formulate our problem as a p-median problem and solve it with a variable neighborhood search algorithm that was automatically configured with irace. We compare the locations proposed by the algorithm with the real ones used currently by the city council. We also study where new locations should be placed if the network grows. |
Villalobos, Ignacio; Ferrer, Javier; Alba, Enrique Un primer enfoque para medir la calidad de FIWARE Inproceedings JISBD 2018, 2018. BibTeX | Tags: @inproceedings{Villalobos2018, title = {Un primer enfoque para medir la calidad de FIWARE}, author = {Ignacio Villalobos and Javier Ferrer and Enrique Alba}, year = {2018}, date = {2018-01-01}, booktitle = {JISBD 2018}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
2017 |
Dahi, Zakaria Abdelmoiz; Mezioud, Chaker ; Draa, Amer A 0-1 bat algorithm for cellular network optimisation: a systematic study on mapping techniques Journal Article Int. J. Reason. based Intell. Syst., 9 (1), pp. 22–42, 2017. @article{DBLP:journals/ijris/DahiMD17, title = {A 0-1 bat algorithm for cellular network optimisation: a systematic study on mapping techniques}, author = {Zakaria Abdelmoiz Dahi and Chaker Mezioud and Amer Draa}, url = {https://doi.org/10.1504/IJRIS.2017.10007147}, doi = {10.1504/IJRIS.2017.10007147}, year = {2017}, date = {2017-01-01}, journal = {Int. J. Reason. based Intell. Syst.}, volume = {9}, number = {1}, pages = {22--42}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Chicano, Francisco; Luque, Gabriel A Mobile Application and Academic Portal to Support Professionals Working with People Having Severe Intellectual or Developmental Disabilities Journal Article Procedia - Social and Behavioral Sciences, 237 , pp. 568 - 575, 2017, ISSN: 18770428. @article{296, title = {A Mobile Application and Academic Portal to Support Professionals Working with People Having Severe Intellectual or Developmental Disabilities}, author = {Francisco Chicano and Gabriel Luque}, url = {http://dx.doi.org/10.1016/j.sbspro.2017.02.108}, doi = {10.1016/j.sbspro.2017.02.108}, issn = {18770428}, year = {2017}, date = {2017-01-01}, journal = {Procedia - Social and Behavioral Sciences}, volume = {237}, pages = {568 - 575}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Saborido, Rubén; Ruiz, Ana B; Luque, Mariano Global WASF-GA: An Evolutionary Algorithm in Multiobjective Optimization to Approximate the Whole Pareto Optimal Front Journal Article Evolutionary Computation, 25 (2), pp. 309–349, 2017. Abstract | Links | BibTeX | Tags: @article{saborido_global_2017, title = {Global WASF-GA: An Evolutionary Algorithm in Multiobjective Optimization to Approximate the Whole Pareto Optimal Front}, author = {Rubén Saborido and Ana B Ruiz and Mariano Luque}, url = {http://dx.doi.org/10.1162/EVCO_a_00175}, doi = {10.1162/EVCO_a_00175}, year = {2017}, date = {2017-01-01}, journal = {Evolutionary Computation}, volume = {25}, number = {2}, pages = {309--349}, abstract = {In this article, we propose a new evolutionary algorithm for multiobjective optimization called Global WASF-GA (global weighting achievement scalarizing function genetic algorithm), which falls within the aggregation-based evolutionary algorithms. The main purpose of Global WASF-GA is to approximate the whole Pareto optimal front. Its fitness function is defined by an achievement scalarizing function (ASF) based on the Tchebychev distance, in which two reference points are considered (both utopian and nadir objective vectors) and the weight vector used is taken from a set of weight vectors whose inverses are well-distributed. At each iteration, all individuals are classified into different fronts. Each front is formed by the solutions with the lowest values of the ASF for the different weight vectors in the set, using the utopian vector and the nadir vector as reference points simultaneously. Varying the weight vector in the ASF while considering the utopian and the nadir vectors at the same time enables the algorithm to obtain a final set of nondominated solutions that approximate the whole Pareto optimal front. We compared Global WASF-GA to MOEA/D (different versions) and NSGA-II in two-, three-, and five-objective problems. The computational results obtained permit us to conclude that Global WASF-GA gets better performance, regarding the hypervolume metric and the epsilon indicator, than the other two algorithms in many cases, especially in three- and five-objective problems.}, keywords = {}, pubstate = {published}, tppubtype = {article} } In this article, we propose a new evolutionary algorithm for multiobjective optimization called Global WASF-GA (global weighting achievement scalarizing function genetic algorithm), which falls within the aggregation-based evolutionary algorithms. The main purpose of Global WASF-GA is to approximate the whole Pareto optimal front. Its fitness function is defined by an achievement scalarizing function (ASF) based on the Tchebychev distance, in which two reference points are considered (both utopian and nadir objective vectors) and the weight vector used is taken from a set of weight vectors whose inverses are well-distributed. At each iteration, all individuals are classified into different fronts. Each front is formed by the solutions with the lowest values of the ASF for the different weight vectors in the set, using the utopian vector and the nadir vector as reference points simultaneously. Varying the weight vector in the ASF while considering the utopian and the nadir vectors at the same time enables the algorithm to obtain a final set of nondominated solutions that approximate the whole Pareto optimal front. We compared Global WASF-GA to MOEA/D (different versions) and NSGA-II in two-, three-, and five-objective problems. The computational results obtained permit us to conclude that Global WASF-GA gets better performance, regarding the hypervolume metric and the epsilon indicator, than the other two algorithms in many cases, especially in three- and five-objective problems. |
Morales, Rodrigo; é, Z; Khomh, Foutse; Antoniol, Giuliano; Chicano, Francisco On the use of developerstextquoteright context for automatic refactoring of software anti-patterns Journal Article Journal of Systems and Software, 128 , pp. 236-251, 2017, ISSN: 0164-1212. Abstract | Links | BibTeX | Tags: Metaheuristics @article{290, title = {On the use of developerstextquoteright context for automatic refactoring of software anti-patterns}, author = {Rodrigo Morales and Z é and Foutse Khomh and Giuliano Antoniol and Francisco Chicano}, url = {http://www.sciencedirect.com/science/article/pii/S0164121216300632}, doi = {http://dx.doi.org/10.1016/j.jss.2016.05.042}, issn = {0164-1212}, year = {2017}, date = {2017-06-01}, journal = {Journal of Systems and Software}, volume = {128}, pages = {236-251}, abstract = { Abstract Anti-patterns are poor solutions to design problems that make software systems hard to understand and extend. Entities involved in anti-patterns are reported to be consistently related to high change and fault rates. Refactorings, which are behavior preserving changes are often performed to remove anti-patterns from software systems. Developers are advised to interleave refactoring activities with their regular coding tasks to remove anti-patterns, and consequently improve software design quality. However, because the number of anti-patterns in a software system can be very large, and their interactions can require a solution in a set of conflicting objectives, the process of manual refactoring can be overwhelming. To automate this process, previous works have modeled anti-patterns refactoring as a batch process where a program provides a solution for the total number of classes in a system, and the developer has to examine a long list of refactorings, which is not feasible in most situations. Moreover, these proposed solutions often require that developers modify classes on which they never worked before (i.e., classes on which they have little or no knowledge). To improve on these limitations, this paper proposes an automated refactoring approach, ReCon (Refactoring approach based on task Context), that leverages information about a developertextquoterights task (i.e., the list of code entities relevant to the developertextquoterights task) and metaheuristics techniques to compute the best sequence of refactorings that affects only entities in the developertextquoterights context. We mine 1705 task contexts (collected using the Eclipse plug-in Mylyn) and 1013 code snapshots from three open-source software projects (Mylyn, PDE, Eclipse Platform) to assess the performance of our proposed approach. Results show that ReCon can remove more than 50% of anti-patterns in a software system, using fewer resources than the traditional approaches from the literature. },keywords = {Metaheuristics}, pubstate = {published}, tppubtype = {article} } <p>Abstract Anti-patterns are poor solutions to design problems that make software systems hard to understand and extend. Entities involved in anti-patterns are reported to be consistently related to high change and fault rates. Refactorings, which are behavior preserving changes are often performed to remove anti-patterns from software systems. Developers are advised to interleave refactoring activities with their regular coding tasks to remove anti-patterns, and consequently improve software design quality. However, because the number of anti-patterns in a software system can be very large, and their interactions can require a solution in a set of conflicting objectives, the process of manual refactoring can be overwhelming. To automate this process, previous works have modeled anti-patterns refactoring as a batch process where a program provides a solution for the total number of classes in a system, and the developer has to examine a long list of refactorings, which is not feasible in most situations. Moreover, these proposed solutions often require that developers modify classes on which they never worked before (i.e., classes on which they have little or no knowledge). To improve on these limitations, this paper proposes an automated refactoring approach, ReCon (Refactoring approach based on task Context), that leverages information about a developertextquoterights task (i.e., the list of code entities relevant to the developertextquoterights task) and metaheuristics techniques to compute the best sequence of refactorings that affects only entities in the developertextquoterights context. We mine 1705 task contexts (collected using the Eclipse plug-in Mylyn) and 1013 code snapshots from three open-source software projects (Mylyn, PDE, Eclipse Platform) to assess the performance of our proposed approach. Results show that ReCon can remove more than 50% of anti-patterns in a software system, using fewer resources than the traditional approaches from the literature.</p> |
Doerr, Carola; Chicano, Francisco Preface to the Special Issue on Theory of Genetic and Evolutionary Computation Journal Article Algorithmica, 78 , pp. 558 - 560, 2017, ISSN: 0178-4617. @article{298, title = {Preface to the Special Issue on Theory of Genetic and Evolutionary Computation}, author = {Carola Doerr and Francisco Chicano}, url = {http://rdcu.be/F1tG}, doi = {10.1007/s00453-017-0280-x}, issn = {0178-4617}, year = {2017}, date = {2017-01-01}, journal = {Algorithmica}, volume = {78}, pages = {558 - 560}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Ruiz, Ana B; Saborido, Rubén; Bermúdez, José D; Luque, Mariano; Vercher, Enriqueta Preference-based Evolutionary Multi-objective Optimization for Solving Fuzzy Portfolio Selection Problems Journal Article Revista Electrónica de Comunicaciones y Trabajos de ASEPUMA. Rect@, 18 (1), pp. 1–15, 2017. @article{ruiz_preference-based_2017, title = {Preference-based Evolutionary Multi-objective Optimization for Solving Fuzzy Portfolio Selection Problems}, author = {Ana B Ruiz and Rubén Saborido and José D Bermúdez and Mariano Luque and Enriqueta Vercher}, doi = {10.24309/recta.2017.18.1.01}, year = {2017}, date = {2017-01-01}, journal = {Revista Electrónica de Comunicaciones y Trabajos de ASEPUMA. Rect@}, volume = {18}, number = {1}, pages = {1--15}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Perez-Wohlfeil, Esteban; Chicano, Francisco; Alba, Enrique Springer International Publishing, Cham, 2017, ISSN: 2194-5357. @book{304, title = {An Intelligent Data Analysis of the Structure of~NP Problems for Efficient Solution: The Vehicle Routing Case}, author = {Esteban Perez-Wohlfeil and Francisco Chicano and Enrique Alba}, editor = {Pavel ömer and Enrique Alba and Jeng-Shyang Pan and áclav á{v s}el}, url = {https://link.springer.com/chapter/10.1007/978-3-319-68527-4_40}, doi = {10.1007/978-3-319-68527-410.1007/978-3-319-68527-4_40}, issn = {2194-5357}, year = {2017}, date = {2017-01-01}, volume = {6823264447}, pages = {368 - 378}, publisher = {Springer International Publishing}, address = {Cham}, organization = {Springer International Publishing}, keywords = {}, pubstate = {published}, tppubtype = {book} } |
Cintrano, Christian; Chicano, Francisco; Alba, Enrique Bi-objective Shortest Path Problem in Real Road Networks Book Springer International Publishing, Cham, 2017, ISSN: 0302-9743. @book{309, title = {Bi-objective Shortest Path Problem in Real Road Networks}, author = {Christian Cintrano and Francisco Chicano and Enrique Alba}, editor = {Enrique Alba and Francisco Chicano and Gabriel Luque}, url = {http://link.springer.com/10.1007/978-3-319-59513-9_13}, doi = {10.1007/978-3-319-59513-9_13}, issn = {0302-9743}, year = {2017}, date = {2017-01-01}, volume = {10268143824236221241252}, pages = {128 - 136}, publisher = {Springer International Publishing}, address = {Cham}, organization = {Springer International Publishing}, keywords = {}, pubstate = {published}, tppubtype = {book} } |
Saborido, Rubén; Khomh, Foutse Helping Android Users to Find the Most Efficient Apps Conference 24th International Conference on Multiple Criteria Decision Making, Ottawa (Canada), 2017. BibTeX | Tags: @conference{saborido_helping_2017, title = {Helping Android Users to Find the Most Efficient Apps}, author = {Rubén Saborido and Foutse Khomh}, year = {2017}, date = {2017-01-01}, booktitle = {24th International Conference on Multiple Criteria Decision Making}, address = {Ottawa (Canada)}, keywords = {}, pubstate = {published}, tppubtype = {conference} } |
Chicano, Francisco; Whitley, Darrell; Ochoa, Gabriela; Tinos, Renato the Genetic and Evolutionary Computation ConferenceProceedings of the Genetic and Evolutionary Computation Conference on - GECCO textquoteright17, ACM Press ACM Press, Berlin, GermanyNew York, New York, USA, 2017, ISBN: 9781450349208. @conference{300, title = {Optimizing one million variable NK landscapes by hybridizing deterministic recombination and local search}, author = {Francisco Chicano and Darrell Whitley and Gabriela Ochoa and Renato Tinos}, url = {http://dl.acm.org/authorize?N30354}, doi = {10.1145/307117810.1145/3071178.3071285}, isbn = {9781450349208}, year = {2017}, date = {2017-01-01}, booktitle = {the Genetic and Evolutionary Computation ConferenceProceedings of the Genetic and Evolutionary Computation Conference on - GECCO textquoteright17}, publisher = {ACM Press}, address = {Berlin, GermanyNew York, New York, USA}, organization = {ACM Press}, keywords = {}, pubstate = {published}, tppubtype = {conference} } |
Cintrano, Christian; Chicano, Francisco; Alba, Enrique Robust Bi-objective Shortest Path Problem in Real Road Networks Incollection International Conference on Smart Cities, Smart-CT 2017, pp. 128–136, Springer, Cham, 2017, ISBN: 978-3-319-59513-9. Abstract | Links | BibTeX | Tags: Bi-objective shortest path, Multi-objective optimization, Robustness, Traffic road network @incollection{Cintrano2017, title = {Robust Bi-objective Shortest Path Problem in Real Road Networks}, author = {Christian Cintrano and Francisco Chicano and Enrique Alba}, doi = {10.1007/978-3-319-59513-9_13}, isbn = {978-3-319-59513-9}, year = {2017}, date = {2017-06-01}, booktitle = {International Conference on Smart Cities, Smart-CT 2017}, pages = {128--136}, publisher = {Springer, Cham}, edition = {Lecture No}, abstract = {Road journeys are one of our most frequent daily tasks. Despite we need them, these trips have some associated costs: time, money, pollution, etc. One of the usual ways of modeling the road network is as a graph. The shortest path problem consists in finding the path in a graph that minimizes a certain cost function. However, in real world applications, more than one objective must be optimized simultaneously (e.g. time and pollution) and the data used in the optimization is not precise: it contains errors. In this paper we propose a new mathematical model for the robust bi-objective shortest path problem. In addition, some empirical studies are included to illustrate the utility of our formulation.}, keywords = {Bi-objective shortest path, Multi-objective optimization, Robustness, Traffic road network}, pubstate = {published}, tppubtype = {incollection} } Road journeys are one of our most frequent daily tasks. Despite we need them, these trips have some associated costs: time, money, pollution, etc. One of the usual ways of modeling the road network is as a graph. The shortest path problem consists in finding the path in a graph that minimizes a certain cost function. However, in real world applications, more than one objective must be optimized simultaneously (e.g. time and pollution) and the data used in the optimization is not precise: it contains errors. In this paper we propose a new mathematical model for the robust bi-objective shortest path problem. In addition, some empirical studies are included to illustrate the utility of our formulation. |
Saborido, Rubén; Khomh, Foutse; Antoniol, Giuliano; Guéhéneuc, Yann-Gaël Comprehension of Ads-supported and Paid Android Applications: Are They Different? Inproceedings Proceedings of the 25th International Conference on Program Comprehension (ICPC), pp. 143–153, IEEE, Buenos Aires, Argentina, 2017. @inproceedings{saborido_comprehension_2017, title = {Comprehension of Ads-supported and Paid Android Applications: Are They Different?}, author = {Rubén Saborido and Foutse Khomh and Giuliano Antoniol and Yann-Gaël Guéhéneuc}, doi = {10.1109/ICPC.2017.25}, year = {2017}, date = {2017-01-01}, booktitle = {Proceedings of the 25th International Conference on Program Comprehension (ICPC)}, pages = {143--153}, publisher = {IEEE}, address = {Buenos Aires, Argentina}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Morell, JA; Alba, Enrique Distributed genetic algorithms on portable devices for smart cities Inproceedings International Conference on Smart Cities, pp. 51–62, Springer 2017. BibTeX | Tags: @inproceedings{morell2017distributed, title = {Distributed genetic algorithms on portable devices for smart cities}, author = {JA Morell and Enrique Alba}, year = {2017}, date = {2017-01-01}, booktitle = {International Conference on Smart Cities}, pages = {51--62}, organization = {Springer}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Ferrer, Javier; Chicano, Francisco; Alba, Enrique Hybrid algorithms based on integer programming for the search of prioritized test data in software product lines Inproceedings Squillero, Giovanni; Sim, Kevin (Ed.): Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 3–19, Springer International Publishing, Cham, 2017, ISSN: 16113349. Abstract | Links | BibTeX | Tags: Combinatorial Interaction Testing, Feature Models, Integer linear programming, Integer nonlinear programming, Pairwise Testing, prioritization, Software Product Lines @inproceedings{Ferrer2017, title = {Hybrid algorithms based on integer programming for the search of prioritized test data in software product lines}, author = {Javier Ferrer and Francisco Chicano and Enrique Alba}, editor = {Giovanni Squillero and Kevin Sim}, url = {http://dx.doi.org/10.1007/978-3-319-55792-2_1}, doi = {10.1007/978-3-319-55792-2_1}, issn = {16113349}, year = {2017}, date = {2017-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {10200 LNCS}, pages = {3--19}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {In Software Product Lines (SPLs) it is not possible, in general, to test all products of the family. The number of products denoted by a SPL is very high due to the combinatorial explosion of features. For this reason, some coverage criteria have been proposed which try to test at least all feature interactions without the necessity to test all products, e.g., all pairs of features (pairwise coverage). In addition, it is desirable to first test products composed by a set of priority features. This problem is known as the Prioritized Pairwise Test Data Generation Problem. In this work we propose two hybrid algorithms using Integer Programming (IP) to generate a prioritized test suite. The first one is based on an integer linear formulation and the second one is based on a integer quadratic (nonlinear) formulation. We compare these techniques with two state-of- the-art algorithms, the Parallel Prioritized Genetic Solver (PPGS) and a greedy algorithm called prioritized-ICPL. Our study reveals that our hybrid nonlinear approach is clearly the best in both, solution quality and computation time. Moreover, the nonlinear variant (the fastest one) is 27 and 42 times faster than PPGS in the two groups of instances analyzed in this work. © Springer International Publishing AG 2017.}, keywords = {Combinatorial Interaction Testing, Feature Models, Integer linear programming, Integer nonlinear programming, Pairwise Testing, prioritization, Software Product Lines}, pubstate = {published}, tppubtype = {inproceedings} } In Software Product Lines (SPLs) it is not possible, in general, to test all products of the family. The number of products denoted by a SPL is very high due to the combinatorial explosion of features. For this reason, some coverage criteria have been proposed which try to test at least all feature interactions without the necessity to test all products, e.g., all pairs of features (pairwise coverage). In addition, it is desirable to first test products composed by a set of priority features. This problem is known as the Prioritized Pairwise Test Data Generation Problem. In this work we propose two hybrid algorithms using Integer Programming (IP) to generate a prioritized test suite. The first one is based on an integer linear formulation and the second one is based on a integer quadratic (nonlinear) formulation. We compare these techniques with two state-of- the-art algorithms, the Parallel Prioritized Genetic Solver (PPGS) and a greedy algorithm called prioritized-ICPL. Our study reveals that our hybrid nonlinear approach is clearly the best in both, solution quality and computation time. Moreover, the nonlinear variant (the fastest one) is 27 and 42 times faster than PPGS in the two groups of instances analyzed in this work. © Springer International Publishing AG 2017. |
Camero, Andres; Arellano-Verdejo, Javier; Cintrano, Christian; Alba, Enrique Tile map size optimization for real world routing by using differential evolution Inproceedings 2017 IEEE Congress on Evolutionary Computation (CEC), pp. 1482–1488, IEEE, 2017, ISBN: 978-1-5090-4601-0. @inproceedings{Camero2017, title = {Tile map size optimization for real world routing by using differential evolution}, author = {Andres Camero and Javier Arellano-Verdejo and Christian Cintrano and Enrique Alba}, doi = {10.1109/CEC.2017.7969478}, isbn = {978-1-5090-4601-0}, year = {2017}, date = {2017-06-01}, booktitle = {2017 IEEE Congress on Evolutionary Computation (CEC)}, pages = {1482--1488}, publisher = {IEEE}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Saborido, Rubén Looking to the Future: Performance Metrics of Apps in Mobile Marketplaces Miscellaneous 2017. Abstract | Links | BibTeX | Tags: @misc{saborido_looking_2017, title = {Looking to the Future: Performance Metrics of Apps in Mobile Marketplaces}, author = {Rubén Saborido}, url = {https://sites.google.com/site/cser2017fall/}, year = {2017}, date = {2017-05-01}, address = {McGill University, Montreal (Canada)}, abstract = {The Android market is a place where developers offer paid and/or free apps. Ads-supported apps use more resources (energy, CPU, memory, and data over the network) than their paid versions, but this information is not available in the official marketplace although it is a major concern for users wanting to increase battery life. Due to the constraints of hardware, developers have to meticulously manage the limited resources available in mobile devices. For this reason Android SDK offers specific data structure implementations which are supposed to be more efficient than the traditional ones offered by Java. However, precise information about the performance of these implementations is also lacking in the official documentation. We claim and show that the availability of performance metrics in mobile app marketplaces is useful for users, but it also enables developers to compare their apps performance to their competitors even before they release an app.}, keywords = {}, pubstate = {published}, tppubtype = {misc} } The Android market is a place where developers offer paid and/or free apps. Ads-supported apps use more resources (energy, CPU, memory, and data over the network) than their paid versions, but this information is not available in the official marketplace although it is a major concern for users wanting to increase battery life. Due to the constraints of hardware, developers have to meticulously manage the limited resources available in mobile devices. For this reason Android SDK offers specific data structure implementations which are supposed to be more efficient than the traditional ones offered by Java. However, precise information about the performance of these implementations is also lacking in the official documentation. We claim and show that the availability of performance metrics in mobile app marketplaces is useful for users, but it also enables developers to compare their apps performance to their competitors even before they release an app. |
Saborido, Ruben Assisting Developers and Users in Developing and Choosing Efficient Mobile Device Apps PhD Thesis 2017. Abstract | Links | BibTeX | Tags: @phdthesis{saborido_assisting_2017, title = {Assisting Developers and Users in Developing and Choosing Efficient Mobile Device Apps}, author = {Ruben Saborido}, url = {https://publications.polymtl.ca/2846/}, year = {2017}, date = {2017-01-01}, abstract = {Mobile device applications (apps) play nowadays a central role in our life. Although energy consumption affects battery life of mobile devices and limits device use, we use them almost anywhere, all the time, and for almost everything. With the exponential growth of the market of mobile device apps in recent years, developers have witnessed a radical change in the landscape of software development. Mobile apps introduce new challenges in software design and implementation due to the constraints of internal resources (such as battery, CPU, and memory), as well as external resources (as data usage). Thus, traditional non-functional requirements, such as functionality and maintainability, have been overshadowed by performance. Researchers are actively investigating the role of coding practices on energy consumption. However, CPU, memory, and network usages are also important performance metrics. Although the hardware of mobile devices has considerably improved in recent years, emerging market users own low-devices and have limited access to data connection. Therefore, developers should manage resources mindfully because emerging markets own a significant share of the new users coming on-line for the first time. Thus, the performance of mobile device apps is a very important topic. Recent studies suggest that software engineers can help reduce energy consumption by considering the energy impacts of their design and implementation decisions. But developers’decisions also have an impact on CPU, memory, and network usages. So that, developers must take into account performance when evolving the design of mobile device apps. The problem is that mobile device app developers have no support to understand the impact of their decisions on their apps performance. This problem is also true for mobile device users who install apps ignoring if there exist more efficient alternatives. In this dissertation we help developers and users to know more about the impact of their decisions on the performance of apps they develop and consume, respectively. Thus, we want to assist developers and users in developing and choosing, respectively, efficient mobile device apps. We provide observations, techniques, and guidelines to help developers make informed decisions to improve the performance of their apps. We also propose an approach to complement mobile device app marketplaces to assist developers and users to search for efficient apps. Our contribution is a valuable step towards efficient software engineering for mobile device apps and a benefit for mobile device users who want to use efficient apps.}, keywords = {}, pubstate = {published}, tppubtype = {phdthesis} } Mobile device applications (apps) play nowadays a central role in our life. Although energy consumption affects battery life of mobile devices and limits device use, we use them almost anywhere, all the time, and for almost everything. With the exponential growth of the market of mobile device apps in recent years, developers have witnessed a radical change in the landscape of software development. Mobile apps introduce new challenges in software design and implementation due to the constraints of internal resources (such as battery, CPU, and memory), as well as external resources (as data usage). Thus, traditional non-functional requirements, such as functionality and maintainability, have been overshadowed by performance. Researchers are actively investigating the role of coding practices on energy consumption. However, CPU, memory, and network usages are also important performance metrics. Although the hardware of mobile devices has considerably improved in recent years, emerging market users own low-devices and have limited access to data connection. Therefore, developers should manage resources mindfully because emerging markets own a significant share of the new users coming on-line for the first time. Thus, the performance of mobile device apps is a very important topic. Recent studies suggest that software engineers can help reduce energy consumption by considering the energy impacts of their design and implementation decisions. But developers’decisions also have an impact on CPU, memory, and network usages. So that, developers must take into account performance when evolving the design of mobile device apps. The problem is that mobile device app developers have no support to understand the impact of their decisions on their apps performance. This problem is also true for mobile device users who install apps ignoring if there exist more efficient alternatives. In this dissertation we help developers and users to know more about the impact of their decisions on the performance of apps they develop and consume, respectively. Thus, we want to assist developers and users in developing and choosing, respectively, efficient mobile device apps. We provide observations, techniques, and guidelines to help developers make informed decisions to improve the performance of their apps. We also propose an approach to complement mobile device app marketplaces to assist developers and users to search for efficient apps. Our contribution is a valuable step towards efficient software engineering for mobile device apps and a benefit for mobile device users who want to use efficient apps. |
2016 |
Dahi, Zakaria Abdelmoiz; Mezioud, Chaker ; Draa, Amer A quantum-inspired genetic algorithm for solving the antenna positioning problem Journal Article Swarm Evol. Comput., 31 , pp. 24–63, 2016. @article{DBLP:journals/swevo/DahiMD16, title = {A quantum-inspired genetic algorithm for solving the antenna positioning problem}, author = {Zakaria Abdelmoiz Dahi and Chaker Mezioud and Amer Draa}, url = {https://doi.org/10.1016/j.swevo.2016.06.003}, doi = {10.1016/j.swevo.2016.06.003}, year = {2016}, date = {2016-01-01}, journal = {Swarm Evol. Comput.}, volume = {31}, pages = {24--63}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Chicano, Francisco; Blum, Christian; Ochoa, Gabriela Editorial for the Special Issue on Combinatorial Optimization Problems Journal Article Evolutionary Computation Journal, 24 , 2016, ISSN: 1063-6560. @article{291, title = {Editorial for the Special Issue on Combinatorial Optimization Problems}, author = {Francisco Chicano and Christian Blum and Gabriela Ochoa}, doi = {10.1162/EVCO_e_00192}, issn = {1063-6560}, year = {2016}, date = {2016-12-01}, journal = {Evolutionary Computation Journal}, volume = {24}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Saborido, Rubén; Ruiz, Ana B; Bermúdez, José D; Vercher, Enriqueta; Luque, Mariano Evolutionary Multi-objective Optimization Algorithms for Fuzzy Portfolio Selection Journal Article Appl. Soft Comput., 39 (C), pp. 48–63, 2016, ISSN: 1568-4946. Links | BibTeX | Tags: Evolutionary multi-objective optimization, LR-fuzzy numbers, Pareto optimal solutions, Portfolio selection, Possibility distributions @article{saborido_evolutionary_2016, title = {Evolutionary Multi-objective Optimization Algorithms for Fuzzy Portfolio Selection}, author = {Rubén Saborido and Ana B Ruiz and José D Bermúdez and Enriqueta Vercher and Mariano Luque}, url = {http://dx.doi.org/10.1016/j.asoc.2015.11.005}, doi = {10.1016/j.asoc.2015.11.005}, issn = {1568-4946}, year = {2016}, date = {2016-01-01}, journal = {Appl. Soft Comput.}, volume = {39}, number = {C}, pages = {48--63}, keywords = {Evolutionary multi-objective optimization, LR-fuzzy numbers, Pareto optimal solutions, Portfolio selection, Possibility distributions}, pubstate = {published}, tppubtype = {article} } |
Whitley, Darrell L; Chicano, Francisco; Goldman, Brian W Gray Box Optimization for Mk Landscapes (NK Landscapes and MAX-kSAT) Journal Article Evolutionary Computation, 24 , pp. 491 - 519, 2016, ISSN: 1063-6560. @article{289, title = {Gray Box Optimization for Mk Landscapes (NK Landscapes and MAX-kSAT)}, author = {Darrell L Whitley and Francisco Chicano and Brian W Goldman}, url = {http://www.mitpressjournals.org/doi/10.1162/EVCO_a_00184}, doi = {10.1162/EVCO_a_00184}, issn = {1063-6560}, year = {2016}, date = {2016-01-01}, journal = {Evolutionary Computation}, volume = {24}, pages = {491 - 519}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Ferrer, Javier; García-Nieto, José; Alba, Enrique; Chicano, Francisco Intelligent testing of traffic light programs: Validation in smart mobility scenarios Journal Article Mathematical Problems in Engineering, 2016 , pp. 1–19, 2016, ISSN: 15635147. Abstract | Links | BibTeX | Tags: @article{Ferrer2016a, title = {Intelligent testing of traffic light programs: Validation in smart mobility scenarios}, author = {Javier Ferrer and José García-Nieto and Enrique Alba and Francisco Chicano}, url = {http://www.hindawi.com/journals/mpe/2016/3871046/}, doi = {10.1155/2016/3871046}, issn = {15635147}, year = {2016}, date = {2016-01-01}, journal = {Mathematical Problems in Engineering}, volume = {2016}, pages = {1--19}, abstract = {textcopyright 2016 Javier Ferrer et al. In smart cities, the use of intelligent automatic techniques to find efficient cycle programs of traffic lights is becoming an innovative front for traffic flow management. However, this automatic programming of traffic lights requires a validation process of the generated solutions, since they can affect the mobility (and security) of millions of citizens. In this paper, we propose a validation strategy based on genetic algorithms and feature models for the automatic generation of different traffic scenarios checking the robustness of traffic light cycle programs. We have concentrated on an extensive urban area in the city of Malaga (in Spain), in which we validate a set of candidate cycle programs generated by means of four optimization algorithms: Particle Swarm Optimization for Traffic Lights, Differential Evolution for Traffic Lights, random search, and Sumo Cycle Program Generator. We can test the cycles of traffic lights considering the different states of the city, weather, congestion, driver expertise, vehicle's features, and so forth, but prioritizing the most relevant scenarios among a large and varied set of them. The improvement achieved in solution quality is remarkable, especially for C O 2 emissions, in which we have obtained a reduction of 126.99% compared with the experts' solutions.}, keywords = {}, pubstate = {published}, tppubtype = {article} } textcopyright 2016 Javier Ferrer et al. In smart cities, the use of intelligent automatic techniques to find efficient cycle programs of traffic lights is becoming an innovative front for traffic flow management. However, this automatic programming of traffic lights requires a validation process of the generated solutions, since they can affect the mobility (and security) of millions of citizens. In this paper, we propose a validation strategy based on genetic algorithms and feature models for the automatic generation of different traffic scenarios checking the robustness of traffic light cycle programs. We have concentrated on an extensive urban area in the city of Malaga (in Spain), in which we validate a set of candidate cycle programs generated by means of four optimization algorithms: Particle Swarm Optimization for Traffic Lights, Differential Evolution for Traffic Lights, random search, and Sumo Cycle Program Generator. We can test the cycles of traffic lights considering the different states of the city, weather, congestion, driver expertise, vehicle's features, and so forth, but prioritizing the most relevant scenarios among a large and varied set of them. The improvement achieved in solution quality is remarkable, especially for C O 2 emissions, in which we have obtained a reduction of 126.99% compared with the experts' solutions. |
Dahi, Zakaria Abdelmoiz; Mezioud, Chaker ; Draa, Amer On the efficiency of the binary flower pollination algorithm: Application on the antenna positioning problem Journal Article Appl. Soft Comput., 47 , pp. 395–414, 2016. @article{DBLP:journals/asc/DahiMD16, title = {On the efficiency of the binary flower pollination algorithm: Application on the antenna positioning problem}, author = {Zakaria Abdelmoiz Dahi and Chaker Mezioud and Amer Draa}, url = {https://doi.org/10.1016/j.asoc.2016.05.051}, doi = {10.1016/j.asoc.2016.05.051}, year = {2016}, date = {2016-01-01}, journal = {Appl. Soft Comput.}, volume = {47}, pages = {395--414}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Tinos, Renato; Liang, Zhao; Chicano, Francisco; Whitley, Darrell A New Evaluation Function for Clustering: The NK Internal Validation Criterion Conference Proceedings of the Genetic and Evolutionary Computation Conference 2016, ACM ACM, New York, NY, USA, 2016, ISBN: 978-1-4503-4206-3. Links | BibTeX | Tags: clustering, evolutionary combinatorial optimization, NK landscape, partition crossover @conference{286, title = {A New Evaluation Function for Clustering: The NK Internal Validation Criterion}, author = {Renato Tinos and Zhao Liang and Francisco Chicano and Darrell Whitley}, url = {http://doi.acm.org/10.1145/2908812.2908831}, doi = {10.1145/2908812.2908831}, isbn = {978-1-4503-4206-3}, year = {2016}, date = {2016-01-01}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference 2016}, publisher = {ACM}, address = {New York, NY, USA}, organization = {ACM}, keywords = {clustering, evolutionary combinatorial optimization, NK landscape, partition crossover}, pubstate = {published}, tppubtype = {conference} } |
Cintrano, Christian; Stolfi, Daniel H; Toutouh, Jamal; Chicano, Francisco; Alba, Enrique Smart Cities - First International Conference, Smart-CT 2016, Málaga, Spain, June 15-17, 2016, Proceedings, 2016. @conference{292, title = {CTPATH: A Real World System to Enable Green Transportation by Optimizing Environmentaly Friendly Routing Paths}, author = {Christian Cintrano and Daniel H Stolfi and Jamal Toutouh and Francisco Chicano and Enrique Alba}, url = {http://dx.doi.org/10.1007/978-3-319-39595-1_7}, doi = {10.1007/978-3-319-39595-1_7}, year = {2016}, date = {2016-01-01}, booktitle = {Smart Cities - First International Conference, Smart-CT 2016, Málaga, Spain, June 15-17, 2016, Proceedings}, keywords = {}, pubstate = {published}, tppubtype = {conference} } |
Chicano, Francisco; 'i, Miguel Ángel Dom; 'i, Isabel Mar; é, Jos; Alba, Enrique Jornada de Ingenier'ia del Software y Bases de Datos, Salamanca, Spain, 2016, ISBN: 978-84-9012-627-1. Abstract | Links | BibTeX | Tags: optimización combinatoria, Optimización multi-objetivo, problema de selección de requisitos, Programación lineal entera @conference{288, title = {Dos estrategias de b'usqueda anytime basadas en programación lineal entera para resolver el problema de selección de requisitos}, author = {Francisco Chicano and Miguel Ángel Dom 'i and Isabel Mar{'i}a del Á and Jos é and Enrique Alba}, url = {http://hdl.handle.net/11705/JISBD/2016/041}, isbn = {978-84-9012-627-1}, year = {2016}, date = {2016-01-01}, booktitle = {Jornada de Ingenier'ia del Software y Bases de Datos}, address = {Salamanca, Spain}, abstract = { El problema de selección de requisitos (o Next Release Problem, NRP) consiste en seleccionar el subconjunto de requisitos que se va a desarrollar en la siguiente versión de una aplicación software. Esta selección se debe hacer de tal forma que maximice la satisfacción de las partes interesadas a la vez que se minimiza el esfuerzo empleado en el desarrollo y se cumplen un conjunto de restricciones. Trabajos recientes han abordado la formulación bi-objetivo de este problema usando técnicas exactas basadas en resolutores SAT y resolutores de programación lineal entera. Ambos se enfrentan a dificultades cuando las instancias tienen un gran tama~no, sin embargo la programación lineal entera (ILP) parece ser más efectiva que los resolutores SAT. En la práctica, no es necesario calcular todas las soluciones del frente de Pareto (que pueden llegar a ser muchas) y basta con obtener un buen n'umero de soluciones eficientes bien distribuidas en el espacio objetivo. Las estrategias de b'usqueda basadas en ILP que se han utilizado en el pasado para encontrar un frente bien distribuido en cualquier instante de tiempo solo buscan soluciones soportadas. En este trabajo proponemos dos estrategias basadas en ILP que son capaces de encontrar el frente completo con suficiente tiempo y que, además, tienen la propiedad de aportar un conjunto de soluciones bien distribuido en el frente objetivo en cualquier momento de la b'usqueda. },keywords = {optimización combinatoria, Optimización multi-objetivo, problema de selección de requisitos, Programación lineal entera}, pubstate = {published}, tppubtype = {conference} } <p>El problema de selección de requisitos (o Next Release Problem, NRP) consiste en seleccionar el subconjunto de requisitos que se va a desarrollar en la siguiente versión de una aplicación software. Esta selección se debe hacer de tal forma que maximice la satisfacción de las partes interesadas a la vez que se minimiza el esfuerzo empleado en el desarrollo y se cumplen un conjunto de restricciones. Trabajos recientes han abordado la formulación bi-objetivo de este problema usando técnicas exactas basadas en resolutores SAT y resolutores de programación lineal entera. Ambos se enfrentan a dificultades cuando las instancias tienen un gran tama~no, sin embargo la programación lineal entera (ILP) parece ser más efectiva que los resolutores SAT. En la práctica, no es necesario calcular todas las soluciones del frente de Pareto (que pueden llegar a ser muchas) y basta con obtener un buen n'umero de soluciones eficientes bien distribuidas en el espacio objetivo. Las estrategias de b'usqueda basadas en ILP que se han utilizado en el pasado para encontrar un frente bien distribuido en cualquier instante de tiempo solo buscan soluciones soportadas. En este trabajo proponemos dos estrategias basadas en ILP que son capaces de encontrar el frente completo con suficiente tiempo y que, además, tienen la propiedad de aportar un conjunto de soluciones bien distribuido en el frente objetivo en cualquier momento de la b'usqueda.</p> |
Chicano, Francisco; Whitley, Darrell; Tinos, Renato Efficient Hill Climber for Constrained Pseudo-Boolean Optimization Problems Conference Proceedings of the Genetic and Evolutionary Computation Conference 2016, ACM ACM, New York, NY, USA, 2016, ISBN: 978-1-4503-4206-3. Links | BibTeX | Tags: constraint handling, hamming ball hill climber, local search, Multi-objective optimization, vector MK landscapes @conference{285, title = {Efficient Hill Climber for Constrained Pseudo-Boolean Optimization Problems}, author = {Francisco Chicano and Darrell Whitley and Renato Tinos}, url = {http://hdl.handle.net/10630/11979}, doi = {10.1145/2908812.2908869}, isbn = {978-1-4503-4206-3}, year = {2016}, date = {2016-01-01}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference 2016}, publisher = {ACM}, address = {New York, NY, USA}, organization = {ACM}, keywords = {constraint handling, hamming ball hill climber, local search, Multi-objective optimization, vector MK landscapes}, pubstate = {published}, tppubtype = {conference} } |
Chicano, Francisco; Whitley, Darell; ó, Renato Tin Efficient Hill Climber for Multi-Objective Pseudo-Boolean Optimization Conference 16th European Conference on Evolutionary Computation for Combinatorial Optimization (LNCS 9595), Springer Springer, 2016, ISBN: 978-3-319-30697-1. @conference{229, title = {Efficient Hill Climber for Multi-Objective Pseudo-Boolean Optimization}, author = {Francisco Chicano and Darell Whitley and Renato Tin ó}, url = {http://hdl.handle.net/10630/11122}, doi = {10.1007/978-3-319-30698-8_7}, isbn = {978-3-319-30697-1}, year = {2016}, date = {2016-01-01}, booktitle = {16th European Conference on Evolutionary Computation for Combinatorial Optimization (LNCS 9595)}, publisher = {Springer}, organization = {Springer}, keywords = {}, pubstate = {published}, tppubtype = {conference} } |
Morales, Rodrigo; Sabane, Aminata; Musavi, Pooya; Khomh, Foutse; Chicano, Francisco; Antoniol, Giuliano Finding the Best Compromise Between Design Quality and Testing Effort During Refactoring Conference 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering, IEEE Press IEEE Press, Osaka, Japan, 2016. @conference{230, title = {Finding the Best Compromise Between Design Quality and Testing Effort During Refactoring}, author = {Rodrigo Morales and Aminata Sabane and Pooya Musavi and Foutse Khomh and Francisco Chicano and Giuliano Antoniol}, doi = {10.1109/SANER.2016.23}, year = {2016}, date = {2016-01-01}, booktitle = {23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering}, publisher = {IEEE Press}, address = {Osaka, Japan}, organization = {IEEE Press}, keywords = {}, pubstate = {published}, tppubtype = {conference} } |
Ben-Smida, Houssem E; Krichen, Saoussen; Chicano, Francisco; Alba, Enrique Mixed Integer Linear Programming Formulation for the Taxi Sharing Problem Conference Smart Cities - First International Conference, Smart-CT 2016, Málaga, Spain, June 15-17, 2016, Proceedings, 2016. @conference{293, title = {Mixed Integer Linear Programming Formulation for the Taxi Sharing Problem}, author = {Houssem E Ben-Smida and Saoussen Krichen and Francisco Chicano and Enrique Alba}, url = {http://dx.doi.org/10.1007/978-3-319-39595-1_11}, doi = {10.1007/978-3-319-39595-1_11}, year = {2016}, date = {2016-01-01}, booktitle = {Smart Cities - First International Conference, Smart-CT 2016, Málaga, Spain, June 15-17, 2016, Proceedings}, keywords = {}, pubstate = {published}, tppubtype = {conference} } |
Cintrano, Christian; Stolfi, Daniel H; Toutouh, Jamal; Chicano, Francisco; Alba, Enrique CTPATH: A Real World System to Enable Green Transportation by Optimizing Environmentaly Friendly Routing Paths Book Chapter Smart Cities: First International Conference, Smart-CT 2016, Málaga, Spain, June 15-17, 2016, Proceedings, pp. 63–75, Springer International Publishing, Cham, 2016, ISBN: 978-3-319-39595-1. @inbook{Cintrano2016a, title = {CTPATH: A Real World System to Enable Green Transportation by Optimizing Environmentaly Friendly Routing Paths}, author = {Christian Cintrano and Daniel H Stolfi and Jamal Toutouh and Francisco Chicano and Enrique Alba}, doi = {10.1007/978-3-319-39595-1_7, %editor = Enrique Alba and Francisco Chicano and Luque, Gabriel}, isbn = {978-3-319-39595-1}, year = {2016}, date = {2016-01-01}, booktitle = {Smart Cities: First International Conference, Smart-CT 2016, Málaga, Spain, June 15-17, 2016, Proceedings}, pages = {63--75}, publisher = {Springer International Publishing}, address = {Cham}, keywords = {}, pubstate = {published}, tppubtype = {inbook} } |
Lopez-Herrejon, Roberto E; Ferrer, Javier; Chicano, Francisco; Egyed, Alexander; Alba, Enrique Evolutionary Computation for Software Product Line Testing: An Overview and Open Challenges Incollection Studies in Computational Intelligence, 617 , pp. 59–87, 2016, ISSN: 1860949X. Abstract | Links | BibTeX | Tags: Feature Models, Feature set, Product line testing, Reverse engineering, search based software engineering, Software Product Lines, Variability modeling @incollection{Lopez-Herrejon2016, title = {Evolutionary Computation for Software Product Line Testing: An Overview and Open Challenges}, author = {Roberto E Lopez-Herrejon and Javier Ferrer and Francisco Chicano and Alexander Egyed and Enrique Alba}, url = {http://link.springer.com/10.1007/978-3-319-25964-2_4}, doi = {10.1007/978-3-319-25964-2_4}, issn = {1860949X}, year = {2016}, date = {2016-01-01}, booktitle = {Studies in Computational Intelligence}, volume = {617}, pages = {59--87}, abstract = {textcopyright Springer International Publishing Switzerland 2016. Because of economical, technological and marketing reasons today's software systems are more frequently being built as families where each product variant implements a different combination of features. Software families are commonly called Software Product Lines (SPLs) and over the past three decades have been the subject of extensive research and application. Among the benefits of SPLs are: increased software reuse, faster and easier product customization, and reduced time to market. However, testing SPLs is specially challenging as the number of product variants is usually large making it infeasible to test every single variant. In recent years there has been an increasing interest in applying evolutionary computation techniques for SPL testing. In this chapter, we provide a concise overview of the state of the art and practice in SPL testing with evolutionary techniques as well as to highlight open questions and areas for future research.}, keywords = {Feature Models, Feature set, Product line testing, Reverse engineering, search based software engineering, Software Product Lines, Variability modeling}, pubstate = {published}, tppubtype = {incollection} } textcopyright Springer International Publishing Switzerland 2016. Because of economical, technological and marketing reasons today's software systems are more frequently being built as families where each product variant implements a different combination of features. Software families are commonly called Software Product Lines (SPLs) and over the past three decades have been the subject of extensive research and application. Among the benefits of SPLs are: increased software reuse, faster and easier product customization, and reduced time to market. However, testing SPLs is specially challenging as the number of product variants is usually large making it infeasible to test every single variant. In recent years there has been an increasing interest in applying evolutionary computation techniques for SPL testing. In this chapter, we provide a concise overview of the state of the art and practice in SPL testing with evolutionary techniques as well as to highlight open questions and areas for future research. |
Bravo, Yesnier; Ferrer, Javier; Luque, Gabriel; Alba, Enrique Smart Mobility by Optimizing the Traffic Lights: A New Tool for Traffic Control Centers Incollection Lecture Notes in Computer Science, 9704 , pp. 147–156, 2016, ISSN: 16113349. Abstract | Links | BibTeX | Tags: Multi-objective optimization, smart mobility, Traffic lights planning @incollection{Bravo2016, title = {Smart Mobility by Optimizing the Traffic Lights: A New Tool for Traffic Control Centers}, author = {Yesnier Bravo and Javier Ferrer and Gabriel Luque and Enrique Alba}, url = {http://link.springer.com/10.1007/978-3-319-39595-1_15}, doi = {10.1007/978-3-319-39595-1_15}, issn = {16113349}, year = {2016}, date = {2016-01-01}, booktitle = {Lecture Notes in Computer Science}, volume = {9704}, pages = {147--156}, abstract = {Urban traffic planning is a fertile area of Smart Cities to improve efficiency, environmental care, and safety, since the traffic jams and congestion are one of the biggest sources of pollution and noise. Traffic lights play an important role in solving these problems since they control the flow of the vehicular network at the city. However, the increasing number of vehicles makes necessary to go from a local control at one single intersection to a holistic approach considering a large urban area, only possible using advanced computational resources and techniques. Here we propose HITUL, a system that supports the decisions of the traffic control managers in a large urban area. HITUL takes the real traffic conditions and compute optimal traffic lights plans using bio-inspired techniques and micro-simulations. We compare our system against plans provided by experts. Our solutions not only enable continuous traffic flows but reduce the pollution. A case study of Málaga city allows us to validate the approach and show its benefits for other cities as well.}, keywords = {Multi-objective optimization, smart mobility, Traffic lights planning}, pubstate = {published}, tppubtype = {incollection} } Urban traffic planning is a fertile area of Smart Cities to improve efficiency, environmental care, and safety, since the traffic jams and congestion are one of the biggest sources of pollution and noise. Traffic lights play an important role in solving these problems since they control the flow of the vehicular network at the city. However, the increasing number of vehicles makes necessary to go from a local control at one single intersection to a holistic approach considering a large urban area, only possible using advanced computational resources and techniques. Here we propose HITUL, a system that supports the decisions of the traffic control managers in a large urban area. HITUL takes the real traffic conditions and compute optimal traffic lights plans using bio-inspired techniques and micro-simulations. We compare our system against plans provided by experts. Our solutions not only enable continuous traffic flows but reduce the pollution. A case study of Málaga city allows us to validate the approach and show its benefits for other cities as well. |
Dahi, Zakaria Abdelmoiz; Mezioud, Chaker ; Alba, Enrique A Novel Adaptive Genetic Algorithm for Mobility Management in Cellular Networks Inproceedings -, Francisco Martínez; Troncoso, Alicia ; Quintián, Héctor ; Corchado, Emilio (Ed.): Hybrid Artificial Intelligent Systems - 11th International Conference, HAIS 2016, Seville, Spain, April 18-20, 2016, Proceedings, pp. 225–237, Springer, 2016. @inproceedings{DBLP:conf/hais/DahiMA16, title = {A Novel Adaptive Genetic Algorithm for Mobility Management in Cellular Networks}, author = {Zakaria Abdelmoiz Dahi and Chaker Mezioud and Enrique Alba}, editor = {Francisco Martínez{-}Álvarez and Alicia Troncoso and Héctor Quintián and Emilio Corchado}, url = {https://doi.org/10.1007/978-3-319-32034-2_19}, doi = {10.1007/978-3-319-32034-2_19}, year = {2016}, date = {2016-01-01}, booktitle = {Hybrid Artificial Intelligent Systems - 11th International Conference, HAIS 2016, Seville, Spain, April 18-20, 2016, Proceedings}, volume = {9648}, pages = {225--237}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Ferrer, Javier; Chicano, Francisco; Lopez-Herrejon, Roberto E; Alba, Enrique Aplicando programación lineal entera a la búsqueda de conjuntos de productos de prueba priorizados para líneas de productos software Inproceedings Jornadas de Ingeniería del Software y Bases de Datos (JISBD), 2016. BibTeX | Tags: Líneas de productos software, Prioridades, Programación lineal, Programación lineal entera, Pruebas de interacción combinatoria @inproceedings{Ferrer2016, title = {Aplicando programación lineal entera a la búsqueda de conjuntos de productos de prueba priorizados para líneas de productos software}, author = {Javier Ferrer and Francisco Chicano and Roberto E Lopez-Herrejon and Enrique Alba}, year = {2016}, date = {2016-01-01}, booktitle = {Jornadas de Ingeniería del Software y Bases de Datos (JISBD)}, keywords = {Líneas de productos software, Prioridades, Programación lineal, Programación lineal entera, Pruebas de interacción combinatoria}, pubstate = {published}, tppubtype = {inproceedings} } |
Saborido, Ruben; Beltrame, Giovanni; Khomh, Foutse; Alba, Enrique; Antoniol, Giulio Optimizing User Experience in Choosing Android Applications Inproceedings Proceedings of the 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER), pp. 438–448, Osaka (Japan), 2016. @inproceedings{saborido_optimizing_2016, title = {Optimizing User Experience in Choosing Android Applications}, author = {Ruben Saborido and Giovanni Beltrame and Foutse Khomh and Enrique Alba and Giulio Antoniol}, year = {2016}, date = {2016-01-01}, booktitle = {Proceedings of the 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER)}, pages = {438--448}, address = {Osaka (Japan)}, abstract = {Why is my cell phone battery already low? How did I use almost all the data of my monthly Internet plan? Is my recently released new application more efficient than similar competing applications? These are not easy questions to answer. Different applications implementing similar or identical functionalities may have different energy consumptions. In this paper, we present a recommendation system aimed at helping users and developers alike. We help users to choose optimal sets of applications belonging to different categories (eg. browsers, e-mails, cameras) while minimizing energy consumption, transmitted data, and maximizing application rating. We also help developers by showing the relative placement of their application's efficiency with respect to selected others. When the optimal set of applications is computed, it is leveraged to position a given application with respect to the optimal, median and worst application in its category (eg. browsers). Out of eight categories we selected 144 applications, manually defined typical execution scenarios, collected the relevant data, and computed the Pareto optimal front solving a multi-objective optimization problem. We report evidence that, on the one hand, ratings do not correlate with energy efficiency and data frugality. On the other hand, we show that it is possible to help developers understanding how far is a new Android application power consumption and network usage with respect to optimal applications in the same category. From the user perspective, we show that choosing optimal sets of applications, power consumption and network usage can be reduced by 16.61% and 40.17%, respectively, in comparison to choosing the set of applications that maximizes only the rating.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Why is my cell phone battery already low? How did I use almost all the data of my monthly Internet plan? Is my recently released new application more efficient than similar competing applications? These are not easy questions to answer. Different applications implementing similar or identical functionalities may have different energy consumptions. In this paper, we present a recommendation system aimed at helping users and developers alike. We help users to choose optimal sets of applications belonging to different categories (eg. browsers, e-mails, cameras) while minimizing energy consumption, transmitted data, and maximizing application rating. We also help developers by showing the relative placement of their application's efficiency with respect to selected others. When the optimal set of applications is computed, it is leveraged to position a given application with respect to the optimal, median and worst application in its category (eg. browsers). Out of eight categories we selected 144 applications, manually defined typical execution scenarios, collected the relevant data, and computed the Pareto optimal front solving a multi-objective optimization problem. We report evidence that, on the one hand, ratings do not correlate with energy efficiency and data frugality. On the other hand, we show that it is possible to help developers understanding how far is a new Android application power consumption and network usage with respect to optimal applications in the same category. From the user perspective, we show that choosing optimal sets of applications, power consumption and network usage can be reduced by 16.61% and 40.17%, respectively, in comparison to choosing the set of applications that maximizes only the rating. |
Vercher, Enriqueta; Ruiz, Ana B; Bermúdez, José D; Saborido, Rubén; Luque, Mariano Selección de Carteras Eficientes Mediante Algoritmos Evolutivos de Optimización Multi-objetivo Inproceedings Actas de la XVII conferencia de la asociación Española para la inteligencia artificial, Salamanca (Spain), 2016, ISBN: 978-84-9012-632-5. BibTeX | Tags: @inproceedings{vercher_enriqueta_seleccion_2016, title = {Selección de Carteras Eficientes Mediante Algoritmos Evolutivos de Optimización Multi-objetivo}, author = {Enriqueta Vercher and Ana B Ruiz and José D Bermúdez and Rubén Saborido and Mariano Luque}, isbn = {978-84-9012-632-5}, year = {2016}, date = {2016-09-01}, booktitle = {Actas de la XVII conferencia de la asociación Española para la inteligencia artificial}, address = {Salamanca (Spain)}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Saborido, Rubén Helping Users and Developers to Choose and Develop Efficient Apps Miscellaneous 2016. Abstract | Links | BibTeX | Tags: @misc{saborido_helping_2016, title = {Helping Users and Developers to Choose and Develop Efficient Apps}, author = {Rubén Saborido}, url = {http://plow.soccerlab.polymtl.ca/6th-plow/}, year = {2016}, date = {2016-01-01}, address = {École Polytechnique de Montréal, Montreal (Canada)}, abstract = {We briefly introduce some approaches to help mobile device users and developers to choose and develop, respectively, efficient applications. This talk was given after an introduction to sustainable software development. After this and other presentation, students will follow hands-on lectures and labs on the challenges of collecting and analysing energy consumption data.}, keywords = {}, pubstate = {published}, tppubtype = {misc} } We briefly introduce some approaches to help mobile device users and developers to choose and develop, respectively, efficient applications. This talk was given after an introduction to sustainable software development. After this and other presentation, students will follow hands-on lectures and labs on the challenges of collecting and analysing energy consumption data. |
2015 |
Ruiz, Ana B; Luque, Mariano; Ruiz, Francisco; Saborido, Rubén Expert Systems with Applications, 42 (21), pp. 7466 – 7482, 2015, ISSN: 0957-4174. Abstract | Links | BibTeX | Tags: Interactive procedure @article{ruiz_combined_2015, title = {A combined interactive procedure using preference-based evolutionary multiobjective optimization. Application to the efficiency improvement of the auxiliary services of power plants}, author = {Ana B Ruiz and Mariano Luque and Francisco Ruiz and Rubén Saborido}, url = {http://www.sciencedirect.com/science/article/pii/S0957417415003723}, doi = {http://dx.doi.org/10.1016/j.eswa.2015.05.036}, issn = {0957-4174}, year = {2015}, date = {2015-01-01}, journal = {Expert Systems with Applications}, volume = {42}, number = {21}, pages = {7466 -- 7482}, abstract = {Abstract While the auxiliary services required for the operation of power plants are not the main components of the plant, their energy consumption is often significant, and it can be reduced by implementing a series of improvement strategies. However, the cost of implementing these changes can be very high, and has to be evaluated. Indeed, a further economic analysis should be considered in order to maximize the profitability of the investment. In this paper, we propose a multiobjective optimization problem to determine the most suitable strategies to maximize the energy saving, to minimize the economic investment and to maximize the Internal Rate of Return of the investment. Solving this real-life multiobjective optimization problem with a decision maker presents several challenges and difficulties and we have developed a novel interactive procedure which combines three different approaches in order to make use of the main advantages of each method. The idea is to start with the approximation of the Pareto optimal set, in order to gain a global understanding of the trade-offs among the objectives, using evolutionary multiobjective optimization; next step is aiding the decision maker to explore the efficient set and to identify the subset of solutions which fits her/his preferences, for which interactive multiple criteria decision making methodologies are used; and finally we concentrate the search for new solutions into the most interesting part of the efficient set with the help of a preference-based evolutionary algorithm. This allows us to build a flexible scheme that is progressively adapted to the decision maker’s reactions until (s)he finds the most preferred solution. The interactive combined procedure proposed is applied in practice for solving the problem of the auxiliary services with a real decision maker, extracting interesting insights about the efficiency improvement of the auxiliary services. With this practical application, we show the usefulness of the interactive procedure proposed, and we highlight the importance of an understandable feedback and an adaptive process.}, keywords = {Interactive procedure}, pubstate = {published}, tppubtype = {article} } Abstract While the auxiliary services required for the operation of power plants are not the main components of the plant, their energy consumption is often significant, and it can be reduced by implementing a series of improvement strategies. However, the cost of implementing these changes can be very high, and has to be evaluated. Indeed, a further economic analysis should be considered in order to maximize the profitability of the investment. In this paper, we propose a multiobjective optimization problem to determine the most suitable strategies to maximize the energy saving, to minimize the economic investment and to maximize the Internal Rate of Return of the investment. Solving this real-life multiobjective optimization problem with a decision maker presents several challenges and difficulties and we have developed a novel interactive procedure which combines three different approaches in order to make use of the main advantages of each method. The idea is to start with the approximation of the Pareto optimal set, in order to gain a global understanding of the trade-offs among the objectives, using evolutionary multiobjective optimization; next step is aiding the decision maker to explore the efficient set and to identify the subset of solutions which fits her/his preferences, for which interactive multiple criteria decision making methodologies are used; and finally we concentrate the search for new solutions into the most interesting part of the efficient set with the help of a preference-based evolutionary algorithm. This allows us to build a flexible scheme that is progressively adapted to the decision maker’s reactions until (s)he finds the most preferred solution. The interactive combined procedure proposed is applied in practice for solving the problem of the auxiliary services with a real decision maker, extracting interesting insights about the efficiency improvement of the auxiliary services. With this practical application, we show the usefulness of the interactive procedure proposed, and we highlight the importance of an understandable feedback and an adaptive process. |
Ruiz, Ana Belén; Saborido, Rubén; Luque, Mariano A preference-based evolutionary algorithm for multiobjective optimization: the weighting achievement scalarizing function genetic algorithm Journal Article Journal of Global Optimization, 62 (1), pp. 101–129, 2015, ISSN: 1573-2916. Abstract | Links | BibTeX | Tags: @article{ruiz_preference-based_2015, title = {A preference-based evolutionary algorithm for multiobjective optimization: the weighting achievement scalarizing function genetic algorithm}, author = {Ana Belén Ruiz and Rubén Saborido and Mariano Luque}, url = {http://dx.doi.org/10.1007/s10898-014-0214-y}, doi = {10.1007/s10898-014-0214-y}, issn = {1573-2916}, year = {2015}, date = {2015-01-01}, journal = {Journal of Global Optimization}, volume = {62}, number = {1}, pages = {101--129}, abstract = {When solving multiobjective optimization problems, preference-based evolutionary multiobjective optimization (EMO) algorithms introduce preference information into an evolutionary algorithm in order to focus the search for objective vectors towards the region of interest of the Pareto optimal front. In this paper, we suggest a preference-based EMO algorithm called weighting achievement scalarizing function genetic algorithm (WASF-GA), which considers the preferences of the decision maker (DM) expressed by means of a reference point. The main purpose of WASF-GA is to approximate the region of interest of the Pareto optimal front determined by the reference point, which contains the Pareto optimal objective vectors that obey the preferences expressed by the DM in the best possible way. The proposed approach is based on the use of an achievement scalarizing function (ASF) and on the classification of the individuals into several fronts. At each generation of WASF-GA, this classification is done according to the values that each solution takes on the ASF for the reference point and using different weight vectors. These vectors of weights are selected so that the vectors formed by their inverse components constitute a well-distributed representation of the weight vectors space. The efficiency and usefulness of WASF-GA is shown in several test problems in comparison to other preference-based EMO algorithms. Regarding a metric based on the hypervolume, we can say that WASF-GA has outperformed the other algorithms considered in most of the problems.}, keywords = {}, pubstate = {published}, tppubtype = {article} } When solving multiobjective optimization problems, preference-based evolutionary multiobjective optimization (EMO) algorithms introduce preference information into an evolutionary algorithm in order to focus the search for objective vectors towards the region of interest of the Pareto optimal front. In this paper, we suggest a preference-based EMO algorithm called weighting achievement scalarizing function genetic algorithm (WASF-GA), which considers the preferences of the decision maker (DM) expressed by means of a reference point. The main purpose of WASF-GA is to approximate the region of interest of the Pareto optimal front determined by the reference point, which contains the Pareto optimal objective vectors that obey the preferences expressed by the DM in the best possible way. The proposed approach is based on the use of an achievement scalarizing function (ASF) and on the classification of the individuals into several fronts. At each generation of WASF-GA, this classification is done according to the values that each solution takes on the ASF for the reference point and using different weight vectors. These vectors of weights are selected so that the vectors formed by their inverse components constitute a well-distributed representation of the weight vectors space. The efficiency and usefulness of WASF-GA is shown in several test problems in comparison to other preference-based EMO algorithms. Regarding a metric based on the hypervolume, we can say that WASF-GA has outperformed the other algorithms considered in most of the problems. |
Chicano, Francisco; Sutton, Andrew M; Whitley, Darrell L; Alba, Enrique Fitness Probability Distribution of Bit-Flip Mutation Journal Article Evolutionary Computation, 23 , pp. 217-248, 2015, ISSN: 1063-6560. @article{181, title = {Fitness Probability Distribution of Bit-Flip Mutation}, author = {Francisco Chicano and Andrew M Sutton and Darrell L Whitley and Enrique Alba}, url = {http://www.mitpressjournals.org/doi/abs/10.1162/EVCO_a_00130}, doi = {10.1162/EVCO_a_00130}, issn = {1063-6560}, year = {2015}, date = {2015-01-01}, journal = {Evolutionary Computation}, volume = {23}, pages = {217-248}, chapter = {217}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Saborido, Rubén; Arnaoudova, Venera; Beltrame, Giovanni; Khomh, Foutse; Antoniol, Giuliano On the impact of sampling frequency on software energy measurements. Journal Article PeerJ PrePrints, 3 , pp. e1219, 2015. @article{saborido_impact_2015, title = {On the impact of sampling frequency on software energy measurements.}, author = {Rubén Saborido and Venera Arnaoudova and Giovanni Beltrame and Foutse Khomh and Giuliano Antoniol}, url = {http://dblp.uni-trier.de/db/journals/peerjpre/peerjpre3.html#SaboridoABKA15}, year = {2015}, date = {2015-01-01}, journal = {PeerJ PrePrints}, volume = {3}, pages = {e1219}, keywords = {dblp}, pubstate = {published}, tppubtype = {article} } |
Luque, Mariano; Ruiz, Ana B; Saborido, Rubén; Marcenaro-Gutiérrez, Óscar D On the use of the $$L_p$$ L p distance in reference point-based approaches for multiobjective optimization Journal Article Annals of Operations Research, 235 (1), pp. 559–579, 2015, ISSN: 1572-9338. Abstract | Links | BibTeX | Tags: @article{luque_use_2015, title = {On the use of the $$L_p$$ L p distance in reference point-based approaches for multiobjective optimization}, author = {Mariano Luque and Ana B Ruiz and Rubén Saborido and Óscar D Marcenaro-Gutiérrez}, url = {http://dx.doi.org/10.1007/s10479-015-2008-0}, doi = {10.1007/s10479-015-2008-0}, issn = {1572-9338}, year = {2015}, date = {2015-01-01}, journal = {Annals of Operations Research}, volume = {235}, number = {1}, pages = {559--579}, abstract = {Reference point-based methods are very useful techniques for solving multiobjective optimization problems. In these methods, the most commonly used achievement scalarizing functions are based on the Tchebychev distance (minmax approach), which generates every Pareto optimal solution in any multiobjective optimization problem, but does not allow compensation among the deviations to the reference values given that it minimizes the value of the highest deviation. At the same time, for any $$1 textbackslashbackslashle p textbackslashbackslashle textbackslashbackslashinfty $$ 1 ≤ p ≤ ∞ , compromise programming minimizes the $$L_p$$ L p distance to the ideal objective vector from the feasible objective region. Although the ideal objective vector can be replaced by a reference point, achievable reference points are not supported by this approach, and special care must be taken in the unachievable case. In this paper, for $$1 textbackslashbackslashle p textless textbackslashbackslashinfty $$ 1 ≤ p textless ∞ , we propose a new scheme based on the $$L_p$$ L p distance, in which different single-objective optimization problems are designed and solved depending on the achievability of the reference point. The formulation proposed allows different compensation degrees among the deviations to the reference values. It is proven that, in the achievable case, any optimal solution obtained is efficient, and, in the unachievable one, it is at least weakly efficient, although it is assured to be efficient if an augmentation term is added to the new formulation. Besides, we suggest an interactive algorithm where the new formulation is embedded. Finally, we show the empirical advantages of the new formulation by its application to both numerical problems and a real multiobjective optimization problem, for achievable and unachievable reference points.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Reference point-based methods are very useful techniques for solving multiobjective optimization problems. In these methods, the most commonly used achievement scalarizing functions are based on the Tchebychev distance (minmax approach), which generates every Pareto optimal solution in any multiobjective optimization problem, but does not allow compensation among the deviations to the reference values given that it minimizes the value of the highest deviation. At the same time, for any $$1 textbackslashbackslashle p textbackslashbackslashle textbackslashbackslashinfty $$ 1 ≤ p ≤ ∞ , compromise programming minimizes the $$L_p$$ L p distance to the ideal objective vector from the feasible objective region. Although the ideal objective vector can be replaced by a reference point, achievable reference points are not supported by this approach, and special care must be taken in the unachievable case. In this paper, for $$1 textbackslashbackslashle p textless textbackslashbackslashinfty $$ 1 ≤ p textless ∞ , we propose a new scheme based on the $$L_p$$ L p distance, in which different single-objective optimization problems are designed and solved depending on the achievability of the reference point. The formulation proposed allows different compensation degrees among the deviations to the reference values. It is proven that, in the achievable case, any optimal solution obtained is efficient, and, in the unachievable one, it is at least weakly efficient, although it is assured to be efficient if an augmentation term is added to the new formulation. Besides, we suggest an interactive algorithm where the new formulation is embedded. Finally, we show the empirical advantages of the new formulation by its application to both numerical problems and a real multiobjective optimization problem, for achievable and unachievable reference points. |
Ferrer, Javier; Kruse, Peter M; Chicano, Francisco; Alba, Enrique Search based algorithms for test sequence generation in functional testing Journal Article Information and Software Technology, 58 , pp. 419–432, 2015, ISSN: 09505849. Abstract | Links | BibTeX | Tags: Ant Colony Optimization, Classification Tree Method, functional, Functional testing, Genetic Algorithm, search based software engineering, sequence, Test sequence generation @article{Ferrer2014, title = {Search based algorithms for test sequence generation in functional testing}, author = {Javier Ferrer and Peter M Kruse and Francisco Chicano and Enrique Alba}, url = {http://www.sciencedirect.com/science/article/pii/S0950584914001827}, doi = {10.1016/j.infsof.2014.07.014}, issn = {09505849}, year = {2015}, date = {2015-01-01}, journal = {Information and Software Technology}, volume = {58}, pages = {419--432}, abstract = {Context: The generation of dynamic test sequences from a formal specification, complementing traditional testing methods in order to find errors in the source code. Objective: In this paper we extend one specific combinatorial test approach, the Classification Tree Method (CTM), with transition information to generate test sequences. Although we use CTM, this extension is also possible for any combinatorial testing method. Method: The generation of minimal test sequences that fulfill the demanded coverage criteria is an NP-hard problem. Therefore, search-based approaches are required to find such (near) optimal test sequences. Results: The experimental analysis compares the search-based technique with a greedy algorithm on a set of 12 hierarchical concurrent models of programs extracted from the literature. Our proposed search-based approaches (GTSG and ACOts) are able to generate test sequences by finding the shortest valid path to achieve full class (state) and transition coverage. Conclusion: The extended classification tree is useful for generating of test sequences. Moreover, the experimental analysis reveals that our search-based approaches are better than the greedy deterministic approach, especially in the most complex instances. All presented algorithms are actually integrated into a professional tool for functional testing.}, keywords = {Ant Colony Optimization, Classification Tree Method, functional, Functional testing, Genetic Algorithm, search based software engineering, sequence, Test sequence generation}, pubstate = {published}, tppubtype = {article} } Context: The generation of dynamic test sequences from a formal specification, complementing traditional testing methods in order to find errors in the source code. Objective: In this paper we extend one specific combinatorial test approach, the Classification Tree Method (CTM), with transition information to generate test sequences. Although we use CTM, this extension is also possible for any combinatorial testing method. Method: The generation of minimal test sequences that fulfill the demanded coverage criteria is an NP-hard problem. Therefore, search-based approaches are required to find such (near) optimal test sequences. Results: The experimental analysis compares the search-based technique with a greedy algorithm on a set of 12 hierarchical concurrent models of programs extracted from the literature. Our proposed search-based approaches (GTSG and ACOts) are able to generate test sequences by finding the shortest valid path to achieve full class (state) and transition coverage. Conclusion: The extended classification tree is useful for generating of test sequences. Moreover, the experimental analysis reveals that our search-based approaches are better than the greedy deterministic approach, especially in the most complex instances. All presented algorithms are actually integrated into a professional tool for functional testing. |
Harman, Mark; Chicano, Francisco Search Based Software Engineering (SBSE) Journal Article Journal of Systems and Software, 103 , pp. 266, 2015. @article{223, title = {Search Based Software Engineering (SBSE)}, author = {Mark Harman and Francisco Chicano}, url = {http://dx.doi.org/10.1016/j.jss.2015.01.051}, doi = {10.1016/j.jss.2015.01.051}, year = {2015}, date = {2015-01-01}, journal = {Journal of Systems and Software}, volume = {103}, pages = {266}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Chicano, Francisco; Arito, Franco; Alba, Enrique Descomposición en Landscapes Elementales del Problema de Dise~no de Redes de Radio con Aplicaciones Conference Congreso Espa~nol sobre Metaheur'isticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2015), 2015, ISBN: 978-84-697-2150-6. Abstract | Links | BibTeX | Tags: @conference{217, title = {Descomposición en Landscapes Elementales del Problema de Dise~no de Redes de Radio con Aplicaciones}, author = {Francisco Chicano and Franco Arito and Enrique Alba}, url = {http://hdl.handle.net/10630/8794}, isbn = {978-84-697-2150-6}, year = {2015}, date = {2015-02-01}, booktitle = {Congreso Espa~nol sobre Metaheur'isticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2015)}, abstract = { En este trabajo se presenta la descomposición en landscapes elementales de un problema de optimización combinatoria: el problema de Dise~no de Redes de Radio. La teor'ia de landscapes provee un marco formal en el cual un problema de optimización combinatoria puede ser caracterizado teóricamente como una suma de un tipo especial de landscape llamado landscape elemental. La descomposición de la función objetivo de un problema en sus componentes elementales aporta conocimiento adicional sobre el problema que puede utilizarse para realizar cálculos exactos sobre ciertos aspectos del problema o dise~nar algoritmos eficientes para resolverlo. Además de la descomposición del problema, se presentan algunas de las posibles aplicaciones de esta descomposición. },keywords = {}, pubstate = {published}, tppubtype = {conference} } <p>En este trabajo se presenta la descomposición en landscapes elementales de un problema de optimización combinatoria: el problema de Dise~no de Redes de Radio. La teor'ia de landscapes provee un marco formal en el cual un problema de optimización combinatoria puede ser caracterizado teóricamente como una suma de un tipo especial de landscape llamado landscape elemental. La descomposición de la función objetivo de un problema en sus componentes elementales aporta conocimiento adicional sobre el problema que puede utilizarse para realizar cálculos exactos sobre ciertos aspectos del problema o dise~nar algoritmos eficientes para resolverlo. Además de la descomposición del problema, se presentan algunas de las posibles aplicaciones de esta descomposición.</p> |
Chicano, Francisco; á, Francisco Dur Mutantes como apoyo para la valoración de pruebas Conference Jornadas sobre la ense~nanza universitaria de la informática, 2015, ISBN: 978-84-8158-711-1. @conference{225, title = {Mutantes como apoyo para la valoración de pruebas}, author = {Francisco Chicano and Francisco Dur á}, url = {http://hdl.handle.net/10630/10097}, isbn = {978-84-8158-711-1}, year = {2015}, date = {2015-07-01}, booktitle = {Jornadas sobre la ense~nanza universitaria de la informática}, keywords = {}, pubstate = {published}, tppubtype = {conference} } |
é, Rub; Chicano, Francisco Optimización multi-objetivo basada en preferencias para la planificación de proyectos software Conference Congreso Espa~nol sobre Metaheur'isticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2015), 2015, ISBN: 978-84-697-2150-6. Abstract | Links | BibTeX | Tags: @conference{218, title = {Optimización multi-objetivo basada en preferencias para la planificación de proyectos software}, author = {Rub é and Francisco Chicano}, url = {http://hdl.handle.net/10630/8792}, isbn = {978-84-697-2150-6}, year = {2015}, date = {2015-02-01}, booktitle = {Congreso Espa~nol sobre Metaheur'isticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2015)}, abstract = { En este trabajo se presenta una herramienta software, denominada Interactive SPS o iSPS, que permite resolver, de forma interactiva, instancias del problema de Planificación de Proyectos Software (SPS) haciendo uso de algoritmos evolutivos basados en punto de referencia. La finalidad de la herramienta es ayudar al director de proyectos software en la toma de decisiones, teniendo en cuenta sus preferencias para aproximar una región concreta del frente óptimo de Pareto. Para mostrar la utilidad de este enfoque preferencial sobre el problema SPS, se ilustra su aplicación con un ejemplo paso a paso en el que se aplica el algoritmo iWASFGA a una instancia concreta del problema. },keywords = {}, pubstate = {published}, tppubtype = {conference} } <p>En este trabajo se presenta una herramienta software, denominada Interactive SPS o iSPS, que permite resolver, de forma interactiva, instancias del problema de Planificación de Proyectos Software (SPS) haciendo uso de algoritmos evolutivos basados en punto de referencia. La finalidad de la herramienta es ayudar al director de proyectos software en la toma de decisiones, teniendo en cuenta sus preferencias para aproximar una región concreta del frente óptimo de Pareto. Para mostrar la utilidad de este enfoque preferencial sobre el problema SPS, se ilustra su aplicación con un ejemplo paso a paso en el que se aplica el algoritmo iWASFGA a una instancia concreta del problema.</p> |
2018 |
Studying Solutions of the p-Median Problem for the Location of Public Bike Stations Inproceedings Advances in Artificial Intelligence, pp. 198–208, Springer International Publishing, Cham, 2018, ISBN: 978-3-030-00374-6. |
Un primer enfoque para medir la calidad de FIWARE Inproceedings JISBD 2018, 2018. |
2017 |
A 0-1 bat algorithm for cellular network optimisation: a systematic study on mapping techniques Journal Article Int. J. Reason. based Intell. Syst., 9 (1), pp. 22–42, 2017. |
A Mobile Application and Academic Portal to Support Professionals Working with People Having Severe Intellectual or Developmental Disabilities Journal Article Procedia - Social and Behavioral Sciences, 237 , pp. 568 - 575, 2017, ISSN: 18770428. |
Global WASF-GA: An Evolutionary Algorithm in Multiobjective Optimization to Approximate the Whole Pareto Optimal Front Journal Article Evolutionary Computation, 25 (2), pp. 309–349, 2017. |
On the use of developerstextquoteright context for automatic refactoring of software anti-patterns Journal Article Journal of Systems and Software, 128 , pp. 236-251, 2017, ISSN: 0164-1212. |
Preface to the Special Issue on Theory of Genetic and Evolutionary Computation Journal Article Algorithmica, 78 , pp. 558 - 560, 2017, ISSN: 0178-4617. |
Preference-based Evolutionary Multi-objective Optimization for Solving Fuzzy Portfolio Selection Problems Journal Article Revista Electrónica de Comunicaciones y Trabajos de ASEPUMA. Rect@, 18 (1), pp. 1–15, 2017. |
Springer International Publishing, Cham, 2017, ISSN: 2194-5357. |
Bi-objective Shortest Path Problem in Real Road Networks Book Springer International Publishing, Cham, 2017, ISSN: 0302-9743. |
Helping Android Users to Find the Most Efficient Apps Conference 24th International Conference on Multiple Criteria Decision Making, Ottawa (Canada), 2017. |
the Genetic and Evolutionary Computation ConferenceProceedings of the Genetic and Evolutionary Computation Conference on - GECCO textquoteright17, ACM Press ACM Press, Berlin, GermanyNew York, New York, USA, 2017, ISBN: 9781450349208. |
Robust Bi-objective Shortest Path Problem in Real Road Networks Incollection International Conference on Smart Cities, Smart-CT 2017, pp. 128–136, Springer, Cham, 2017, ISBN: 978-3-319-59513-9. |
Comprehension of Ads-supported and Paid Android Applications: Are They Different? Inproceedings Proceedings of the 25th International Conference on Program Comprehension (ICPC), pp. 143–153, IEEE, Buenos Aires, Argentina, 2017. |
Distributed genetic algorithms on portable devices for smart cities Inproceedings International Conference on Smart Cities, pp. 51–62, Springer 2017. |
Hybrid algorithms based on integer programming for the search of prioritized test data in software product lines Inproceedings Squillero, Giovanni; Sim, Kevin (Ed.): Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 3–19, Springer International Publishing, Cham, 2017, ISSN: 16113349. |
Tile map size optimization for real world routing by using differential evolution Inproceedings 2017 IEEE Congress on Evolutionary Computation (CEC), pp. 1482–1488, IEEE, 2017, ISBN: 978-1-5090-4601-0. |
Looking to the Future: Performance Metrics of Apps in Mobile Marketplaces Miscellaneous 2017. |
Assisting Developers and Users in Developing and Choosing Efficient Mobile Device Apps PhD Thesis 2017. |
2016 |
A quantum-inspired genetic algorithm for solving the antenna positioning problem Journal Article Swarm Evol. Comput., 31 , pp. 24–63, 2016. |
Editorial for the Special Issue on Combinatorial Optimization Problems Journal Article Evolutionary Computation Journal, 24 , 2016, ISSN: 1063-6560. |
Evolutionary Multi-objective Optimization Algorithms for Fuzzy Portfolio Selection Journal Article Appl. Soft Comput., 39 (C), pp. 48–63, 2016, ISSN: 1568-4946. |
Gray Box Optimization for Mk Landscapes (NK Landscapes and MAX-kSAT) Journal Article Evolutionary Computation, 24 , pp. 491 - 519, 2016, ISSN: 1063-6560. |
Intelligent testing of traffic light programs: Validation in smart mobility scenarios Journal Article Mathematical Problems in Engineering, 2016 , pp. 1–19, 2016, ISSN: 15635147. |
On the efficiency of the binary flower pollination algorithm: Application on the antenna positioning problem Journal Article Appl. Soft Comput., 47 , pp. 395–414, 2016. |
A New Evaluation Function for Clustering: The NK Internal Validation Criterion Conference Proceedings of the Genetic and Evolutionary Computation Conference 2016, ACM ACM, New York, NY, USA, 2016, ISBN: 978-1-4503-4206-3. |
Smart Cities - First International Conference, Smart-CT 2016, Málaga, Spain, June 15-17, 2016, Proceedings, 2016. |
Jornada de Ingenier'ia del Software y Bases de Datos, Salamanca, Spain, 2016, ISBN: 978-84-9012-627-1. |
Efficient Hill Climber for Constrained Pseudo-Boolean Optimization Problems Conference Proceedings of the Genetic and Evolutionary Computation Conference 2016, ACM ACM, New York, NY, USA, 2016, ISBN: 978-1-4503-4206-3. |
Efficient Hill Climber for Multi-Objective Pseudo-Boolean Optimization Conference 16th European Conference on Evolutionary Computation for Combinatorial Optimization (LNCS 9595), Springer Springer, 2016, ISBN: 978-3-319-30697-1. |
Finding the Best Compromise Between Design Quality and Testing Effort During Refactoring Conference 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering, IEEE Press IEEE Press, Osaka, Japan, 2016. |
Mixed Integer Linear Programming Formulation for the Taxi Sharing Problem Conference Smart Cities - First International Conference, Smart-CT 2016, Málaga, Spain, June 15-17, 2016, Proceedings, 2016. |
CTPATH: A Real World System to Enable Green Transportation by Optimizing Environmentaly Friendly Routing Paths Book Chapter Smart Cities: First International Conference, Smart-CT 2016, Málaga, Spain, June 15-17, 2016, Proceedings, pp. 63–75, Springer International Publishing, Cham, 2016, ISBN: 978-3-319-39595-1. |
Evolutionary Computation for Software Product Line Testing: An Overview and Open Challenges Incollection Studies in Computational Intelligence, 617 , pp. 59–87, 2016, ISSN: 1860949X. |
Smart Mobility by Optimizing the Traffic Lights: A New Tool for Traffic Control Centers Incollection Lecture Notes in Computer Science, 9704 , pp. 147–156, 2016, ISSN: 16113349. |
A Novel Adaptive Genetic Algorithm for Mobility Management in Cellular Networks Inproceedings -, Francisco Martínez; Troncoso, Alicia ; Quintián, Héctor ; Corchado, Emilio (Ed.): Hybrid Artificial Intelligent Systems - 11th International Conference, HAIS 2016, Seville, Spain, April 18-20, 2016, Proceedings, pp. 225–237, Springer, 2016. |
Aplicando programación lineal entera a la búsqueda de conjuntos de productos de prueba priorizados para líneas de productos software Inproceedings Jornadas de Ingeniería del Software y Bases de Datos (JISBD), 2016. |
Optimizing User Experience in Choosing Android Applications Inproceedings Proceedings of the 23rd IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER), pp. 438–448, Osaka (Japan), 2016. |
Selección de Carteras Eficientes Mediante Algoritmos Evolutivos de Optimización Multi-objetivo Inproceedings Actas de la XVII conferencia de la asociación Española para la inteligencia artificial, Salamanca (Spain), 2016, ISBN: 978-84-9012-632-5. |
Helping Users and Developers to Choose and Develop Efficient Apps Miscellaneous 2016. |
2015 |
Expert Systems with Applications, 42 (21), pp. 7466 – 7482, 2015, ISSN: 0957-4174. |
A preference-based evolutionary algorithm for multiobjective optimization: the weighting achievement scalarizing function genetic algorithm Journal Article Journal of Global Optimization, 62 (1), pp. 101–129, 2015, ISSN: 1573-2916. |
Fitness Probability Distribution of Bit-Flip Mutation Journal Article Evolutionary Computation, 23 , pp. 217-248, 2015, ISSN: 1063-6560. |
On the impact of sampling frequency on software energy measurements. Journal Article PeerJ PrePrints, 3 , pp. e1219, 2015. |
On the use of the $$L_p$$ L p distance in reference point-based approaches for multiobjective optimization Journal Article Annals of Operations Research, 235 (1), pp. 559–579, 2015, ISSN: 1572-9338. |
Search based algorithms for test sequence generation in functional testing Journal Article Information and Software Technology, 58 , pp. 419–432, 2015, ISSN: 09505849. |
Search Based Software Engineering (SBSE) Journal Article Journal of Systems and Software, 103 , pp. 266, 2015. |
Descomposición en Landscapes Elementales del Problema de Dise~no de Redes de Radio con Aplicaciones Conference Congreso Espa~nol sobre Metaheur'isticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2015), 2015, ISBN: 978-84-697-2150-6. |
Mutantes como apoyo para la valoración de pruebas Conference Jornadas sobre la ense~nanza universitaria de la informática, 2015, ISBN: 978-84-8158-711-1. |
Optimización multi-objetivo basada en preferencias para la planificación de proyectos software Conference Congreso Espa~nol sobre Metaheur'isticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2015), 2015, ISBN: 978-84-697-2150-6. |