Software reliability growth models support the prediction/assessment of product quality, release time, and testing/debugging cost. Several software reliability growth model exten-sions take into account the bug correction process. However, their estimates may be significantly inaccurate when debugging fails to fully fit modelling assumptions. This paper proposes debugging-workflow-aware software reliability growth method (DWA-SRGM), a method for reliability growth analysis leveraging the debugging data usually managed by companies in bug tracking systems. On the basis of a characterization of the debugging workflow within the soft- ware project under consideration (in terms of bug features and treatment phases), DWA-SRGM pinpoints the factors impacting the estimates and to spot bottlenecks, thus supporting process improvement decisions. Two industrial case studies are presented, a customer relationship man- agement system and an enterprise resource planning system, whose defects span a period of about 17 and 13 months, respectively. DWA-SRGM revealed effective to obtain more realistic estimates and to capitalize on the awareness of critical factors for improving debugging.
Debugging-workflow-aware software reliability growth analysis
PECCHIA, ANTONIO;
2017-01-01
Abstract
Software reliability growth models support the prediction/assessment of product quality, release time, and testing/debugging cost. Several software reliability growth model exten-sions take into account the bug correction process. However, their estimates may be significantly inaccurate when debugging fails to fully fit modelling assumptions. This paper proposes debugging-workflow-aware software reliability growth method (DWA-SRGM), a method for reliability growth analysis leveraging the debugging data usually managed by companies in bug tracking systems. On the basis of a characterization of the debugging workflow within the soft- ware project under consideration (in terms of bug features and treatment phases), DWA-SRGM pinpoints the factors impacting the estimates and to spot bottlenecks, thus supporting process improvement decisions. Two industrial case studies are presented, a customer relationship man- agement system and an enterprise resource planning system, whose defects span a period of about 17 and 13 months, respectively. DWA-SRGM revealed effective to obtain more realistic estimates and to capitalize on the awareness of critical factors for improving debugging.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
