Abstract

Software engineering is about understanding and making the right tradeoffs. Many software engineering tasks-such as test case generation, design, sprint planning, and refactoring-boil down to understanding tradeoffs including concretely expressing the attributes to optimize and elements and decisions that will maximize their intended outcomes. Consequently, many software engineering problems can be formulated as search problems. Driven by these observations, Harman and Jones in 2001 emphasized the importance of concentrated research on the application of search-based techniques in software engineering and coined the subfield of search-based software engineering (SBSE) in software engineering research.1 During the two decades that followed, SBSE has seen a significant amount of increased research where metaheuristic algorithms are used to create recommendations for software engineering tasks.

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