Program based test adequacy criteria (TAC), such as statement, branch coverage and mutation give objectives for software testing. Many techniques and tools have been developed to improve each phase of the TAC-based software testing process. Nonetheless, The engineering effort required to integrate these tools and techniques into the software testing process limits their use and creates an overhead to the users. Especially for system testing with languages like C, where test cases are not always well structured in a framework. In response to these challenges, this paper presents Muteria, a TAC-based software testing framework. Muteria enables the integration of multiple software testing tools. Muteria abstracts each phase of the TAC-based software testing process to provide tool drivers interfaces for the implementation of tool drivers. Tool drivers enable Muteria to call the corresponding tools during the testing process. An initial set of drivers for KLEE, Shadow and SEMu test-generation tools, Gcov, and coverage.py code coverage tools, and Mart mutant generation tool for C and Python programming language were implemented with an average of 345 lines of Python code. Moreover, the user configuration file required to measure code coverage and mutation score on a sample C programs, using the Muteria framework, consists of less than 15 configuration variables. Users of the Muteria framework select, in a configuration file, the tools and TACs to measure. The Muteria framework uses the user configuration to run the testing process and report the outcome. Users interact with Muteria through its Application Programming Interface and Command Line Interface. Muteria can benefit to researchers as a laboratory to execute experiments, and to software practitioners.
CITATION STYLE
Chekam, T. T., Papadakis, M., & Le Traon, Y. (2020). Muteria: An extensible and flexible multi-criteria software testing framework. In Proceedings - 2020 IEEE/ACM 1st International Conference on Automation of Software Test, AST 2020 (pp. 97–100). Association for Computing Machinery. https://doi.org/10.1145/3387903.3389316
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