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{{Short description|Application of metaheuristic search techniques to software engineering}}
{{Use dmy dates|date=December 2020}}
'''Search-based software engineering''' ('''SBSE''') applies [[metaheuristic]] search techniques such as [[genetic algorithms]], [[simulated annealing]] and [[tabu search]] to [[software engineering]] problems. Many activities in [[software engineering]] can be stated as [[Optimization (mathematics)|optimization]] problems. [[Optimization (mathematics)|Optimization]] techniques of [[operations research]] such as [[linear programming]] or [[dynamic programming]] are often impractical for large scale [[software engineering]] problems because of their [[Computational complexity theory|computational complexity]] or their assumptions on the problem structure. Researchers and practitioners use [[metaheuristic]] search techniques, which impose little assumptions on the problem structure, to find near-optimal or "good-enough" solutions<ref>{{Cite journal |last=Mohan |first=M. |last2=Greer |first2=D. |date=2019-08-01 |title=Using a many-objective approach to investigate automated refactoring |url=https://www.sciencedirect.com/science/article/pii/S0950584919300916 |journal=Information and Software Technology |volume=112 |pages=83–101 |doi=10.1016/j.infsof.2019.04.009 |issn=0950-5849}}</ref>.
SBSE problems can be divided into two types:
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