A software package evolves in time through various maintenance release steps whose effectiveness depends mainly on the number of faults left in the modules. Software testing is one of the most demanding and crucial phases to discover and reduce faults. In real environment, time available to test a software release is a given finite quantity. The purpose of this paper is to identify a criterion to estimate an efficient time repartition among software modules to enhance fault location in testing phase and to reduce corrective maintenance. The fundamental idea is to relate testing time to predicted risk level of the modules in the release under test. In our previous work we analyzed several kinds of risk prediction factors and their relationship with faults; moreover, we thoroughly investigated the behaviour of faults on each module through releases to find significant fault proneness tendencies. Starting from these two lines of analysis, in this paper we propose a new approach to optimize the use of available testing time in a software release. We tuned and tested our hypotheses on a large industrial environment.

Optimizing Test to Reduce Maintenance

PIGHIN, Maurizio;
2005

Abstract

A software package evolves in time through various maintenance release steps whose effectiveness depends mainly on the number of faults left in the modules. Software testing is one of the most demanding and crucial phases to discover and reduce faults. In real environment, time available to test a software release is a given finite quantity. The purpose of this paper is to identify a criterion to estimate an efficient time repartition among software modules to enhance fault location in testing phase and to reduce corrective maintenance. The fundamental idea is to relate testing time to predicted risk level of the modules in the release under test. In our previous work we analyzed several kinds of risk prediction factors and their relationship with faults; moreover, we thoroughly investigated the behaviour of faults on each module through releases to find significant fault proneness tendencies. Starting from these two lines of analysis, in this paper we propose a new approach to optimize the use of available testing time in a software release. We tuned and tested our hypotheses on a large industrial environment.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/848094
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