Analyzing variability of software artifacts is important for increasing reuse and improving development of similar software products, as is the case in the area of Software Product Line Engineering (SPLE). Current approaches suggest analyzing the variability of certain types of artifacts, most notably requirements. However, as the specification of requirements may be incomplete or generalized, capturing the differences between the intended software behaviors may be limited, neglecting essential parts, such as behavior preconditions. Thus, we suggest in this paper utilizing testing artifacts in order to comprehensively analyze the variability of the corresponding requirements. The suggested approach, named SOVA R-TC, which is based on Bunge’s ontological model, uses the information stored and managed in Application Lifecycle Management (ALM) environments. It extracts the behavior transformations from the requirements and the test cases and presents them in the form of initial states (preconditions) and final states (post-conditions or expected results). It further compares the behavior transformations of different software products and proposes how to analyze their variability based on cross-phase artifacts.
CITATION STYLE
Steinberger, M., & Reinhartz-Berger, I. (2016). Comprehensive variability analysis of requirements and testing artifacts. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9694, pp. 461–475). Springer Verlag. https://doi.org/10.1007/978-3-319-39696-5_28
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