Mutation testing is a powerful software engineering technique for fault finding. It works by injecting known faults (mutations) into software and seeing if the test suite finds them. It remains very expensive and the few valuable traditional mutants that resemble real faults are mixed in with many others that denote unrealistic faults. The expense and lack of realism inhibit industrial uptake of mutation testing. Genetic programming searches the space of complex faults to find realistic higher order mutants. Despite the much larger search space, we have found mutants composed of multiple changes to the C source code that challenge the tester and which cannot be represented in the first order space.

Mutation testing is a powerful software engineering technique for fault finding. It works by injecting known faults (mutations) into software and seeing if the test suite finds them. It remains very expensive and the few valuable traditional mutants that resemble real faults are mixed in with many others that denote unrealistic faults. The expense and lack of realism inhibit industrial uptake of mutation testing. Genetic programming searches the space of complex faults to find realistic higher order mutants. Despite the much larger search space, we have found mutants composed of multiple changes to the C source code that challenge the tester and which cannot be represented in the first order space.

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utation analysis is a program testing method which seeds a fault in a program and tries to identify it with test data, thus promoting the test efficiency. The paper investigates the application of mutation analysis in model-based testing for the modeling language of finite state machines (FSM). We describe a set of mutation operators for FSM based on the fault category; present an algorithm of selecting a test suite for the mutation testing of system models in FSM. In an experiment, other five methods of test suites generating and selecting for FSM are chosen to compare with the mutation testing method. The experiment shows that in respect of faults detecting in FSM, the mutation testing is more effective and efficient than the other FSM testing methods including D-method, W-method and T-method.

Buffer overflow (BOF) is one of the major vulnerabilities that lead to non-secure software. Testing an implementation for BOF vulnerabilities is challenging as the underlying reasons of buffer overflow vary widely. This paper presents a novel method for BOF test for ANSI C language, which uses program instrumentation and mutation test technology to test the BOF vulnerabilities, on the basis of analyzing the invariants for BOF vulnerabilities. The implementation shows that it can check the attack of BOF vulnerabilities adequately and accurately, in the circumstances of no large losses in performance.

With recent increased expectations for quality, and the growth of agile processes and test driven development, developers are expected to do more and more effective unittesting. Yet, our knowledge of when to use the variousunit level test criteria is incomplete. The paper presentsresults from a comparison of four unit level software testing criteria. Mutation testing, prime path coverage, edgepair coverage, and all-uses testing were compared on twobases: the number of seeded faults found and the numberof tests needed to satisfy the criteria. The comparisonused a collection of Java classes taken from varioussources and hand-seeded faults. Tests were designed andgenerated mostly by hand with help from tools that computetest requirements and muJava. The findings are that mutationtests detected more faults and the other three criteriawere very similar. The paper also presents a secondarymeasure, a cost benefit ratio, computed as the number oftests needed to detect each fault. Surprisingly, mutation required the fewest number of tests. The paper also discusses some specific faults that were not found and presents analysis for why not.

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