Abstract
Specification-based testing methods generate test data without the knowledge of the structure of the program. However, the quality of these test data are not well ensured to detect bugs when non-functional changes are introduced to the program. To generate test data effectively, we propose a new method that combines formal specifications with the genetic algorithm (GA). In this method, formal specifications are reformed by GA in order to be used to generate input values that can kill as many mutants of the target program as possible. Two classic examples are presented to demonstrate how the method works. The result shows that the proposed method can help effectively generate test cases to kill the program mutants, which contributes to the further maintenance of software.
Highlights
Regression testing is an important technique to ensure that previously tested software still performs in the same way after it is changed or integrated with other software [1,2,3]
We mainly use formal specifications in pre- and postconditions, such as Vienna Development Method (VDM) [13], a formal method that has been developed over past years [14,15], and Structured-Object-Oriented Formal Language (SOFL) [16], which has the potential of practical use in industry and serves as a solid foundation to develop a method of functional scenario-based test data generation [17]
To overcome the shortcomings of the existing specification-based testing (SBT) methods, we propose a new method for test data generation in this paper
Summary
Regression testing is an important technique to ensure that previously tested software still performs in the same way after it is changed or integrated with other software [1,2,3]. The proposed method introduces dummy variables into some specified constraints in the specification, and makes use of the constraints over both input and output variables to guide the test data generation, in contrast to the conventional SBT methods that concerns only constraints over input variables. This method features the combination of three techniques, SBT, mutation testing, and GA. It is to obtain the enhanced (mutated) formal specifications by using a GA so that input data generated from these specifications are more likely to kill different kinds of mutants of the target program under test.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
