A Probabilistic Approach to Causal Analysis of Software Defects

• Marcos Kalinowski UFRJ
• Guilherme Horta Travassos UFRJ

DOI: https://doi.org/10.5753/sbqs.2012.15335

Abstract

Causal analysis of defects has been shown to be an efficient way to improve processes based on the product. In this thesis, a probabilistic approach to causal analysis, called DPPI (Defect Prevention-Based Process Improvement) was developed based on evidence obtained from four rounds of systematic literature review and feedback obtained from specialists in the field. DPPI represents an innovative approach that integrates cause and effect learning mechanisms (Bayesian networks) in the procedures for causal analysis of defects. In addition, to facilitate the use of these mechanisms in causal analysis meetings, the traditional cause and effect diagram has been extended to a probabilistic cause and effect diagram. DPPI was applied to a real project and evaluated through three rounds of an experimental study. The application to the real project indicated its viability and allowed to refine requirements for the construction of tooling support. The rounds of the experimental study provided evidence that the use of probabilistic cause and effect diagrams of DPPI increases the effectiveness and reduces the effort in identifying causes of defects, when compared to the identification of causes of defects without the use of diagrams.

Keywords: Probabilistic Approach, Causal Analysis, Software Defects

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