Validating class integration test order generation systems with Metamorphic Testing
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
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Detail(s)
Original language | English |
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Article number | 106507 |
Journal / Publication | Information and Software Technology |
Volume | 132 |
Online published | 16 Dec 2020 |
Publication status | Published - Apr 2021 |
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Abstract
Context: Previous studies proposed different kinds of approaches for class integration test order generation, and corresponding systems can be implemented based on these approaches. Such class integration test order generation systems can facilitate the process of software integration testing if they are implemented correctly. Objective: However, a test oracle problem exists in the class integration test order generation systems. Since these approaches for class integration test order generation normally deliver a local optimum rather than a global optimum, there are no practically feasible ways to validate their generated class integration test orders, that is, these implementation systems are untestable.
Method: To address the test oracle problem, we apply Metamorphic Testing (MT) to validate class integration test order generation systems. Metamorphic Relations (MRs), which are the key components of MT, reason about relations between test outputs of a system. Five effective MRs are developed to ensure the quality of the class integration test order generation systems. In these proposed MRs, follow-up test inputs are generated by modifying classes or class dependencies in the source test inputs while some characteristics of the source test outputs are preserved, for example, the same class integration test order or the equal stubbing cost. Faults can be detected in systems if an individual MR is violated for certain tests.
Results: Failure detection of MT has been successfully demonstrated in empirical experiments on three systems implementing different typical class integration test order generation approaches. More than 84% of faulty programs can be detected by all MRs, for three class integration test order generation systems under investigation.
Conclusion: The experimental results show that the proposed MRs are able to systematically and effectively detect faults in class integration test order generation systems. This study explores a new application domain in MT and further extends its applications in Software Engineering.
Method: To address the test oracle problem, we apply Metamorphic Testing (MT) to validate class integration test order generation systems. Metamorphic Relations (MRs), which are the key components of MT, reason about relations between test outputs of a system. Five effective MRs are developed to ensure the quality of the class integration test order generation systems. In these proposed MRs, follow-up test inputs are generated by modifying classes or class dependencies in the source test inputs while some characteristics of the source test outputs are preserved, for example, the same class integration test order or the equal stubbing cost. Faults can be detected in systems if an individual MR is violated for certain tests.
Results: Failure detection of MT has been successfully demonstrated in empirical experiments on three systems implementing different typical class integration test order generation approaches. More than 84% of faulty programs can be detected by all MRs, for three class integration test order generation systems under investigation.
Conclusion: The experimental results show that the proposed MRs are able to systematically and effectively detect faults in class integration test order generation systems. This study explores a new application domain in MT and further extends its applications in Software Engineering.
Research Area(s)
- Class integration test order generation, Integration testing, Metamorphic Relations, Metamorphic Testing
Citation Format(s)
Validating class integration test order generation systems with Metamorphic Testing. / Zhang, Miao; Keung, Jacky Wai; Chen, Tsong Yueh et al.
In: Information and Software Technology, Vol. 132, 106507, 04.2021.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review