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A Baseline Method For Search-Based Software Engineering

Date of Publication: 
September 2010
Authors: 
Associated Research Groups: 
Publication Files: 
Abstract: 
Background: Search-based Software Engineering (SBSE) uses a variety of techniques such as evolutionary algorithms or meta-heuristic searches but lacks a standard baseline method. Aims: The KEYS2 algorithm meets the criteria of a baseline. It is fast, stable, easy to understand, and presents results that are competitive with standard techniques. Method: KEYS2 operates on the theory that a small sub-set of variables control the majority of the search space. It uses a greedy search and a Bayesian ranking heuristic to fix the values of these variables, which rapidly forces the search towards stable high-scoring areas. Results: KEYS2 is faster than standard techniques, presents competitive results (assessed with a rank-sum test), and offers stable solutions. Conclusions: KEYS2 is a valid candidate to serve as a baseline technique for SBSE research.
Venue: 
PROMISE '10 Proceedings of the 6th International Conference on Predictive Models in Software Engineering
bibtex: 
@conference{gay2010baseline, title={{A baseline method for search-based software engineering}}, author={Gay, G.}, booktitle={Proceedings of the 6th International Conference on Predictive Models in Software Engineering}, pages={1--11}, year={2010}, organization={ACM} }