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 problems. 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 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.

SBSE problems can be divided into two types:

SBSE converts a software engineering problem into a computational search problem that can be tackled with a metaheuristic. This involves defining a search space, or the set of possible solutions. This space is typically too large to be explored exhaustively, suggesting a metaheuristic approach. A metric (also called a fitness function, cost function, objective function or quality measure) is then used to measure the quality of potential solutions. Many software engineering problems can be reformulated as a computational search problem.

The term "search-based application", in contrast, refers to using search-engine technology, rather than search techniques, in another industrial application.

One of the earliest attempts to apply optimization to a software engineering problem was reported by Webb Miller and David Spooner in 1976 in the area of software testing. In 1992, S. Xanthakis and his colleagues applied a search technique to a software engineering problem for the first time. The term SBSE was first used in 2001 by Harman and Jones. The research community grew to include more than 800 authors by 2013, spanning approximately 270 institutions in 40 countries.

Search-based software engineering is applicable to almost all phases of the software development process. Software testing has been one of the major applications. Search techniques have been applied to other software engineering activities, for instance, requirements analysis, design, refactoring, development, and maintenance.

Requirements engineering is the process by which the needs of a software's users and environment are determined and managed. Search-based methods have been used for requirements selection and optimisation with the goal of finding the best possible subset of requirements that matches user requests amid constraints such as limited resources and interdependencies between requirements. This problem is often tackled as a multiple-criteria decision-making problem and, generally involves presenting the decision maker with a set of good compromises between cost and user satisfaction as well as the requirements risk.

Identifying a software bug (or a code smell) and then debugging (or refactoring) the software is largely a manual and labor-intensive endeavor, though the process is tool-supported. One objective of SBSE is to automatically identify and fix bugs (for example via mutation testing).