Development and analysis of mutationtesting based test generation techniques using meta heuristic approaches

Abstract

Development and analysis of mutation testing based newlinetest generation techniques using meta-heuristic newlineapproaches newlineshweta rani newline(roll no. 90021011215) newlinethesis supervisor: dr. bharti suri newlineprofessor newlineuniversity school of information, communication and technology newlineguru gobind singh indraprastha university, newlinesector 16c, dwarka, new delhi-110078, india newlinesoftware testing is an essential activity of the software development process and builds newlinethe confidence that the developed software is correct and satisfies the quality standards. newlinehowever, if the software is not tested exhaustively and adequately, it may lead to software newlinefailure. besides its importance, software testing is very costly and labor-intensive. it is newlinealso not possible to demonstrate that errors are not present in the program. therefore, newlinetest data is one of the primary requirements of software testing. test data should be newlineadequate to reveal the faults during development and before releasing the software. the newlineprimary concern is how one can design the test data. there are infinite combinations of newlineinputs, and choosing the effective one is quite cumbersome. this test data generation is newlinea search optimization problem and can be overcome using meta-heuristic optimization newlinealgorithms. we use these algorithms to optimize the process of test generation. these newlinemeta-heuristic algorithms usually begin with a random solution that is evolved until the newlineimproved solution meets some predetermined testing criteria. newlinein this thesis, mutation coverage is selected as a testing criterion. it is related to mutation newlinetesting and indicates how many mutants are covered by the evolved test data. mutants newlineare artificial faults and are very close to real faults. these are created following the newlineprinciple of mutation testing. a test case while executing with a mutant ... newline