To early discover faults in source code, test case ordering has to be properly chosen. To this aim test prioritization techniques can be used. Several of these techniques leave out the execution cost of test cases and exploit a single objective function (e.g., code or requirements coverage). In this paper, we present a multi-objective test prioritization technique that determines sequences of test cases that maximize the number of discovered faults that are both technical and business critical. The technique uses the information related to the code and requirements coverage, as well as the execution cost of each test case. The approach also uses recovered traceability links among source code and system requirements via the Latent Semantic Indexing technique. We evaluated our proposal against both a random prioritization technique and two single-objective prioritization techniques on two Java applications. The results indicate that our proposal outperforms the baseline techniques and that additional improvements are still possible. © 2012 IEEE.
A multi-objective technique to prioritize test cases based on Latent Semantic Indexing / Islam, Md. M.; Marchetto, A.; Susi, A.; Scanniello, G.. - (2012), pp. 21-30. (Intervento presentato al convegno 2012 16th European Conference on Software Maintenance and Reengineering, CSMR 2012 tenutosi a Szeged, hun nel 2012) [10.1109/CSMR.2012.13].
A multi-objective technique to prioritize test cases based on Latent Semantic Indexing
Marchetto A.;
2012-01-01
Abstract
To early discover faults in source code, test case ordering has to be properly chosen. To this aim test prioritization techniques can be used. Several of these techniques leave out the execution cost of test cases and exploit a single objective function (e.g., code or requirements coverage). In this paper, we present a multi-objective test prioritization technique that determines sequences of test cases that maximize the number of discovered faults that are both technical and business critical. The technique uses the information related to the code and requirements coverage, as well as the execution cost of each test case. The approach also uses recovered traceability links among source code and system requirements via the Latent Semantic Indexing technique. We evaluated our proposal against both a random prioritization technique and two single-objective prioritization techniques on two Java applications. The results indicate that our proposal outperforms the baseline techniques and that additional improvements are still possible. © 2012 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione