Premium
Automatically detecting equivalent mutants and infeasible paths
Author(s) -
Offutt A. Jefferson,
Pan Jie
Publication year - 1997
Publication title -
software testing, verification and reliability
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.216
H-Index - 49
eISSN - 1099-1689
pISSN - 0960-0833
DOI - 10.1002/(sici)1099-1689(199709)7:3<165::aid-stvr143>3.0.co;2-u
Subject(s) - computer science , path (computing) , mutation testing , process (computing) , software testing , mutation , software , reliability (semiconductor) , test case , reliability engineering , programming language , machine learning , engineering , biochemistry , chemistry , power (physics) , physics , regression analysis , quantum mechanics , gene
Mutation testing is a technique for testing software units that has great potential for improving the quality of testing, and thereby increasing the ability to assure the high reliability of critical software. It will be shown that recent advances in mutation research have brought a practical mutation testing system closer to reality. One recent advance is a partial solution to the problem of automatically detecting equivalent mutant programs. Equivalent mutants are currently detected by hand, which makes it very expensive and time‐consuming. The problem of detecting equivalent mutants is a specific instance of a more general problem, commonly called the feasible path problem , which says that for certain structural testing criteria some of the test requirements are infeasible in the sense that the semantics of the program imply that no test case satisfies the test requirements. Equivalent mutants, unreachable statements in path testing techniques, and infeasible DU‐pairs in data flow testing are all instances of the feasible path problem. This paper presents a technique that uses mathematical constraints, originally developed for test data generation, to detect some equivalent mutants and infeasible paths automatically. © 1997 John Wiley & Sons, Ltd.