Debugging‐workflow‐aware software reliability growth analysis. (29th June 2017)

• Record Type: Journal Article
• Authors: Cinque, Marcello; Cotroneo, Domenico; Pecchia, Antonio; Pietrantuono, Roberto; Russo, Stefano
• Is Part Of: Software testing, verification & reliability. Volume 27:Number 7(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-06-29
• Subjects: debugging -- release planning -- reliability models -- software reliability -- SRGM; Computer software -- Testing -- Periodicals; Computer software -- Verification -- Periodicals; Computer software -- Reliability -- Periodicals; 005.14
• DOI: 10.1002/stvr.1638
• Languages: English
• ISSNs: 0960-0833

Abstract

Summary: Software reliability growth models support the prediction/assessment of product quality, release time, and testing/debugging cost. Several software reliability growth model extensions 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 software 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 management 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. Abstract : The debugging‐workflow‐aware software reliability growth method (SRGM) uses issue tracking data–a valuable yet often unexploited asset for project managers–to improve the best release time prediction and the product reliability estimate, as well as to spot bottlenecks in the debugging workflow possibly distorting SRGM‐based inferences. Debugging‐workflow‐aware SRGM applied to industrial projects reveals a severe impact on release time prediction and quality estimation caused by neglecting debugging. This pragmatic approach supports a more effective use in the industrial practice of software reliability analysis based on reliability growth models.