Graduate Research and Discovery Symposium (GRADS)

Document Type


Publication Date

Spring 2015


Increasingly, software producing organizations utilize a common software platform, joining an ecosystem; however, little expertise exists on selecting which platform to use when presented a number of different platforms. While technical debt can be used to examine the quality of a software platform by the organization that produces the software, a single discrete data point does not provide sufficient context for analysis. In this paper, we seek to resolve this difficulty by applying linear regression analysis to technical debt data collected by the SonarQube static analyzer. We apply this method to a case study on Cytoscape network analysis platform to perform a pedagogical investigation on the longitudinal technical debt found in that platform. We present our case study on the longitudinal technical debt in the form of arguments for and against the adoption of the Cytoscape network analysis platform, utilizing the data and analysis generated from our method.