Evidence of software inspection on feature specification for software product lines

Abstract

In software product lines (SPL), scoping is a phase responsible for capturing, specifying and modeling features, and also their constraints, interactions and variations. The feature specification task, performed in this phase, is usually based on natural language, which may lead to lack of clarity, non-conformities and defects. Consequently, scoping analysts may introduce ambiguity, inconsistency, omissions and non-conformities. In this sense, this paper aims at gathering evidence about the effects of applying an inspection approach to feature specification for SPL. Data from a SPL reengineering project were analyzed in this work and the analysis indicated that the correction activity demanded more effort. Also, Pareto's principle showed that incompleteness and ambiguity reported higher non-conformity occurrences. Finally, the Poisson regression analysis showed that sub-domain risk information can be a good indicator for prioritization of sub-domains in the inspection activity.

Highlights We characterized the software inspection activity on features specifications in an industrial SPL project. The inspection activity reported incompleteness as the main non-conformity type found on features specifications. Correction was the most burdensome SPL Inspection task.Optional features presented higher non-conformity density than mandatory features.The risk attribute enabled to build a predictive model for estimating non-conformities in features specifications.