Unit testing focused on MC/DC criterion is essential in development of safety-critical systems. H... more Unit testing focused on MC/DC criterion is essential in development of safety-critical systems. However design of test data that meet the MC/DC criterion needs detailed manual analysis of branching in units under test by test engineers. To deal with this problem we propose a new test data generation approach based on reinforcement learning, which utilize analogy with a game, in which a gamer, the test engineer, plays in an environment, a unit under test, and tries to achieve the highest possible reward, MC/DC coverage. We evaluated our approach for two different granularity levels, test suite and test case, and for two different action types allowed to the gamer, discrete and continuous action spaces. Preliminary results shows that the proposed approach could solve path explosion problem of symbolic approaches and that the proposed approach achieves at least comparable results to the current state-of-the-art search-based test data generation approaches.
Unit testing focused on the Modified Condition/Decision Coverage (MC/DC) criterion is essential i... more Unit testing focused on the Modified Condition/Decision Coverage (MC/DC) criterion is essential in development of safety-critical systems as recommended by international standards. Designing unit tests for such specific software is time-consuming task which can be partially automated by test data generation methods. Special attention is given to search-based methods which are often used for problems where traditional methods like symbolic execution fall short. However, no publicly available dataset for evaluation of such methods taking into account specifics of the MC/DC criterion, which is esential for safety-critical systems. In this paper we present an analysis of software of safety-critical systems and we postulate to find a fitting open source project which could serve as a synthesized dataset for future evaluations of search-based test data generation methods for the MC/DC criterion.
Unit testing focused on MC/DC criterion is essential in development of safety-critical systems. H... more Unit testing focused on MC/DC criterion is essential in development of safety-critical systems. However design of test data that meet the MC/DC criterion needs detailed manual analysis of branching in units under test by test engineers. To deal with this problem we propose a new test data generation approach based on reinforcement learning, which utilize analogy with a game, in which a gamer, the test engineer, plays in an environment, a unit under test, and tries to achieve the highest possible reward, MC/DC coverage. We evaluated our approach for two different granularity levels, test suite and test case, and for two different action types allowed to the gamer, discrete and continuous action spaces. Preliminary results shows that the proposed approach could solve path explosion problem of symbolic approaches and that the proposed approach achieves at least comparable results to the current state-of-the-art search-based test data generation approaches.
Unit testing focused on the Modified Condition/Decision Coverage (MC/DC) criterion is essential i... more Unit testing focused on the Modified Condition/Decision Coverage (MC/DC) criterion is essential in development of safety-critical systems as recommended by international standards. Designing unit tests for such specific software is time-consuming task which can be partially automated by test data generation methods. Special attention is given to search-based methods which are often used for problems where traditional methods like symbolic execution fall short. However, no publicly available dataset for evaluation of such methods taking into account specifics of the MC/DC criterion, which is esential for safety-critical systems. In this paper we present an analysis of software of safety-critical systems and we postulate to find a fitting open source project which could serve as a synthesized dataset for future evaluations of search-based test data generation methods for the MC/DC criterion.
Uploads
Papers by Ján Čegiň