An Extended Abstract of ''Theoretical and Empirical Analyses of the Effectiveness of Metamorphic Relation Composition''
Fri 27 Aug 2021 04:10 - 04:20 - Testing—Test Generation 1 Chair(s): Shiva Nejati
The fault detection capability of metamorphic testing (MT) largely depends on the “quality” of metamorphic relations (MRs)[3]. Since MRs are often identified based on human judgment and, hence, the identification task may not be properly performed. Thus, systematic MR generation has long been an important research issue in MT. In addition, MT researchers are concerned about the cost-effectiveness of MT, in view of the extra overhead associated with executing the program with follow-up test cases. This gives rise to the issue of reducing the test cost of MT. MR composition [1, 2] can address both of these issues, by automatically composing existing MRs to form new ones and thereby reducing the number of follow-up test cases. Although this approach is intuitively sound, previous studies on MR composition have empirically shown that the fault detection capability of MRs may be reduced after composition [1, 2]. This has inspired us to conduct theoretical and empirical analyses to identify what characteristics components MRs should possess so that their corresponding composite MR has at least the same fault detection capability as the component MRs do.
Our analysis has found some characteristics of the component MRs, which are defined in terms of the bijectivity/injectivity of these component MRs’ input and output mappings. As such, these characteristics are easily verified by a tester. The existence of these characteristics in component MRs guarantees that the fault detection capability will not be jeopardized after MR composition. The validity of our findings has been formally proved, and their practicality has been checked via an empirical study. To promote the applicability of our results, we have also formulated convenient yet effective guidelines to help a tester determine whether or not MR composition should be used.
Thu 26 AugDisplayed time zone: Athens change
16:00 - 17:00 | Testing—Test Generation 1Journal First / Research Papers +12h Chair(s): Rachel Tzoref-Brill IBM Research, Myra Cohen Iowa State University | ||
16:00 10mPaper | Graph-Based Seed Object Synthesis for Search-Based Unit Testing Research Papers Yun Lin National University of Singapore, You Sheng Ong National University of Singapore, Jun Sun Singapore Management University, Gordon Fraser University of Passau, Jin Song Dong National University of Singapore DOI Pre-print | ||
16:10 10mPaper | An Extended Abstract of ''Theoretical and Empirical Analyses of the Effectiveness of Metamorphic Relation Composition'' Journal First Kun Qiu Hefei University of Technology, Zheng Zheng Beihang University, Tsong Yueh Chen Swinburne University of Technology, Pak-Lok Poon School of Engineering & Technology, Central Queensland University, Australia Link to publication DOI | ||
16:20 10mPaper | Output Sampling for Output Diversity in Automatic Unit Test Generation Journal First Hector Menendez Middlesex University London, Michele Boreale Università di Firenze, Daniele Gorla Department of Computer Science, Sapienza University of Rome, David Clark University College London | ||
16:30 30mLive Q&A | Q&A (Testing—Test Generation 1) Research Papers |
Fri 27 AugDisplayed time zone: Athens change
04:00 - 05:00 | Testing—Test Generation 1Research Papers / Journal First Chair(s): Shiva Nejati University of Ottawa | ||
04:00 10mPaper | Graph-Based Seed Object Synthesis for Search-Based Unit Testing Research Papers Yun Lin National University of Singapore, You Sheng Ong National University of Singapore, Jun Sun Singapore Management University, Gordon Fraser University of Passau, Jin Song Dong National University of Singapore DOI Pre-print | ||
04:10 10mPaper | An Extended Abstract of ''Theoretical and Empirical Analyses of the Effectiveness of Metamorphic Relation Composition'' Journal First Kun Qiu Hefei University of Technology, Zheng Zheng Beihang University, Tsong Yueh Chen Swinburne University of Technology, Pak-Lok Poon School of Engineering & Technology, Central Queensland University, Australia Link to publication DOI | ||
04:20 10mPaper | Output Sampling for Output Diversity in Automatic Unit Test Generation Journal First Hector Menendez Middlesex University London, Michele Boreale Università di Firenze, Daniele Gorla Department of Computer Science, Sapienza University of Rome, David Clark University College London | ||
04:30 30mLive Q&A | Q&A (Testing—Test Generation 1) Research Papers |