Nature-Inspired Approaches to Test Suite Minimization for Regression Testing
Anu Bajaj, Om Prakash Sangwan · 2020
Regression testing is performed to check whether the changes introduced any faults or vulnerabilities. This chapter focuses on test suite minimization approaches that use nature-inspired algorithms. It briefly introduces the test suite minimization problem and nature-inspired algorithms. The chapter describes the research work performed in this field, and addresses the research questions and future directions with the help of the observations and findings of the related studies. Test suite minimization finds subsets of test suites to remove redundant and obsolete test cases. Physics- and chemistry-inspired algorithms have also proven their efficiency in solving regression testing problems, such as broader applicability of genetic algorithms (GAs) in prioritizing test cases. The chapter explains nature-inspired algorithms used in reducing the test suite size. Various researchers have used nature-inspired algorithms for solving the regression test suite minimization. Test suite reduction with optimization algorithms leads to a dramatic decrease in suite size, which may miss useful test cases and, subsequently, fault detection rate.