Proceedings of the 20th International Systems and Software Product Line Conference 2016
DOI: 10.1145/2934466.2946046
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Search-based test case selection of cyber-physical system product lines for simulation-based validation

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Cited by 30 publications
(24 citation statements)
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“…results and findings? (Q8) Conejero et al (2012) 2012 Journal IST and requirements maintainability S119 On the value of user preferences in Sayyad et al (2013) 2013 Conference ICSE search-based software engineering: A case study in software product lines S120 Ontology-based feature modeling: An Dermeval et al (2015) 2015 Journal Expert Systems empirical study in changing scenarios with Applications S121 Optimized feature selection towards Lian and Zhang (2015) 2015 Conference SANER functional and non-functional requirements in Software Product Lines S122 Optimizing software product line Federle et al (2015) 2015 Conference SSBSE architectures with OPLA-tool S123 PACOGEN: Automatic Generation of Pairwise Hervieu et al (2011) 2011 Conference ISSRE Test Configurations from Feature Models S124 Potential synergies of theorem proving and Thum et al (2014) 2014 Conference SPLC model checking for software product lines S125 Practical minimization of pairwisecovering test Hervieu et al (2016) 2017 Journal IST configurations using constraint programming S126 Practical pairwise testing for Marijan et al (2013) 2013 Conference SPLC software product lines S127 Preference-based Feature Model Configuration Stein et al (2014) 2014 Conference SPLC with Multiple Stakeholders S128 Preserving architectural styles in Mariani et al (2016) 2016 Journal JSS the search based design of software product line architectures S129 Product Line Variability Modeling Based Nie et al (2012) 2012 Conference COMPSAC on Model Difference and Merge S130 Product-line maintenance with Thum et al (2016) 2016 Conference SPLC emergent contract interfaces S131 Reasoning about edits to feature models Thum et al (2009Thum et al ( ) 2009 Conference ICSE S132 Reasoning about product-line evolution Burdek et al (2016) Conference SBCARS Product Lines: An Empirical Study S137 RiPLE-HC: JavaScript systems meets 2016 Conference SPLC SPL composition S138 RiPLE-TE: A process for testing Machado et al (2011) 2011 Conference SEKE Software Product Lines S139 Scalable prediction of non-functional properties Siegmund et al (2013) 2013 Journal IST in software product lines: Footprint and memory consumption S140 Scoping automation in software product lines Ianzen et al (2015) 2015 Conference ICEIS S141 Search Based Design of Layered Mariani et al (2015) 2015 Conference COMPSAC Product Line Architectures S142 Search-based Test Case Selection Arrieta et al (2016) 2016 Conference SPLC of Cyber-physical System Product Lines for Simulation-based Va...…”
Section: Discussionmentioning
confidence: 99%
“…results and findings? (Q8) Conejero et al (2012) 2012 Journal IST and requirements maintainability S119 On the value of user preferences in Sayyad et al (2013) 2013 Conference ICSE search-based software engineering: A case study in software product lines S120 Ontology-based feature modeling: An Dermeval et al (2015) 2015 Journal Expert Systems empirical study in changing scenarios with Applications S121 Optimized feature selection towards Lian and Zhang (2015) 2015 Conference SANER functional and non-functional requirements in Software Product Lines S122 Optimizing software product line Federle et al (2015) 2015 Conference SSBSE architectures with OPLA-tool S123 PACOGEN: Automatic Generation of Pairwise Hervieu et al (2011) 2011 Conference ISSRE Test Configurations from Feature Models S124 Potential synergies of theorem proving and Thum et al (2014) 2014 Conference SPLC model checking for software product lines S125 Practical minimization of pairwisecovering test Hervieu et al (2016) 2017 Journal IST configurations using constraint programming S126 Practical pairwise testing for Marijan et al (2013) 2013 Conference SPLC software product lines S127 Preference-based Feature Model Configuration Stein et al (2014) 2014 Conference SPLC with Multiple Stakeholders S128 Preserving architectural styles in Mariani et al (2016) 2016 Journal JSS the search based design of software product line architectures S129 Product Line Variability Modeling Based Nie et al (2012) 2012 Conference COMPSAC on Model Difference and Merge S130 Product-line maintenance with Thum et al (2016) 2016 Conference SPLC emergent contract interfaces S131 Reasoning about edits to feature models Thum et al (2009Thum et al ( ) 2009 Conference ICSE S132 Reasoning about product-line evolution Burdek et al (2016) Conference SBCARS Product Lines: An Empirical Study S137 RiPLE-HC: JavaScript systems meets 2016 Conference SPLC SPL composition S138 RiPLE-TE: A process for testing Machado et al (2011) 2011 Conference SEKE Software Product Lines S139 Scalable prediction of non-functional properties Siegmund et al (2013) 2013 Journal IST in software product lines: Footprint and memory consumption S140 Scoping automation in software product lines Ianzen et al (2015) 2015 Conference ICEIS S141 Search Based Design of Layered Mariani et al (2015) 2015 Conference COMPSAC Product Line Architectures S142 Search-based Test Case Selection Arrieta et al (2016) 2016 Conference SPLC of Cyber-physical System Product Lines for Simulation-based Va...…”
Section: Discussionmentioning
confidence: 99%
“…3. A black-box output diversity algorithm, that adapts the output uniqueness (Alshahwan and Harman [113]) and uses a notion of output diversity over continuous control signals. 4.…”
Section: Model-based and Dynamic Test Case Selectionmentioning
confidence: 99%
“…A search-based method uses heuristics to explore the input space of the target and automatically generate test cases. Both Ali and Yule [2] and Arrieta et al [3][4] use genetic algorithms to generate and select test cases. Matinnejad et al [25] applied different search algorithms for testing automotive embedded systems, including random search, adaptive random search, a hill-climbing algorithm, and a simulated annealing algorithm.…”
Section: Robotic System Testingmentioning
confidence: 99%