Abstract

Test sets which cover all branches of a library of five procedures which solve the triangle problem, have been produced automatically using genetic algorithms. The tests are derived from both the structure of the software and its formal specification in Z. In a wider context, more complex procedures such as a binary search and a generic quicksort have also been tested automatically from the structure of the software. The value of genetic algorithms lies in their ability to handle input data which may be of a complex data structure, and to execute branches whose predicate may be a complicated and unknown function of the input data. A disadvantage of genetic algorithms may be the computational effort required to reach a solution.

Full Text
Paper version not known

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 call

Disclaimer: 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.