A Quality Perspective of Software Evolvability Using Semantic Analysis

Software development and maintenance are highly distributed processes that involve a multitude of supporting tools and resources. Knowledge relevant to these resources is typically dispersed over a wide range of artifacts, representation formats, and abstraction levels. In order to stay competitive, organizations are often required to assess and provide evidence that their software meets the expected requirements. In our research, we focus on assessing non-functional quality requirements, specifically evolvability, through semantic modeling of relevant software artifacts. We introduce our SE-Advisor that supports the integration of knowledge resources typically found in software ecosystems by providing a unified ontological representation. We further illustrate how our SE-Advisor takes advantage of this unified representation to support the analysis and assessment of different types of quality attributes related to the evolvability of software ecosystems.

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