Introduction to the special issue on search based software engineering

Abstract

This special issue of Empirical Software Engineering consists of revised and extended versions of five selected papers originally presented at the 1st International Symposium on Search Based Software Engineering (SSBSE 2009). The symposium was held at Cumberland Lodge, Windsor, UK, in May 2009, and brought together the academic researchers and industrial practitioners that make up the international Search Based Software Engineering (SBSE) community for the first conference dedicated to the subject. Search Based Software Engineering is the application of search-based optimization techniques—for example, genetic algorithms, hill climbing, simulated annealing, taboo search, and ant colony optimization—to the solution of software engineering problems. Many such problems are often difficult or impossible to solve manually, and moreover, as modern software becomes more complex and adopts distributed and highly parallel architectures, are proving to be increasingly intractable using traditional automated techniques. In contrast, SBSE approaches can leverage sophisticated optimisation algorithms running on affordable computing infrastructure to solve these problems. SBSE approaches also demonstrate other advantages: they can be used to find acceptably good solutions when time, or resources, are limited, and—by utilizing multi-objective search algorithms—can derive a range of solutions that illustrate potential trade-offs between competing goals. For these reasons, both academic and industrial interest in SBSE is increasing rapidly. A recent survey,1 undertaken by the UK-based SEBASE project, indicated an exponential growth of