The Community for Technology Leaders
2013 2nd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE) (2013)
San Francisco, CA, USA
May 25, 2013 to May 26, 2013
ISBN: 978-1-4673-6437-9
pp: 21-27
Abdel Salam Sayyad , Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown, WV USA
Hany Ammar , Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown, WV USA
ABSTRACT
The Search-Based Software Engineering (SBSE) community is increasingly recognizing the inherit “multiobjectiveness” in Software Engineering problems. The old ways of aggregating all objectives into one may very well be behind us. We perform a well-deserved literature survey of SBSE papers that used multiobjective search to find Pareto-optimal solutions, and we pay special attention to the chosen algorithms, tools, and quality indicators, if any. We conclude that the SBSE field has seen a trend of adopting the Multiobjective Evolutionary Optimization Algorithms (MEOAs) that are widely used in other fields (such as NSGA-II and SPEA2) without much scrutiny into the reason why one algorithm should be preferred over the others. We also find that the majority of published work only tackled two-objective problems (or formulations of problems), leaving much to be desired in terms of exploiting the power of MEOAs to discover solutions to intractable problems characterized by many trade-offs and complex constraints.
INDEX TERMS
Search-Based Software Engineering, Multiobjective Optimization, Pareto-Optimal Solutions
CITATION

A. S. Sayyad and H. Ammar, "Pareto-optimal search-based software engineering (POSBSE): A literature survey," 2013 2nd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE), San Francisco, CA, USA, 2013, pp. 21-27.
doi:10.1109/RAISE.2013.6615200
92 ms
(Ver 3.3 (11022016))