Abstract
Technical debt is the debt in the software development incurred due to preference of short term deadlines over the strategic ones. Analysis of the factors effecting technical debt (TD) is need of the hour from business as well as technical context. Based on the state of the art described in the literature, we have tried to identify the most contributing factors effecting TD. For doing so various statistical tools and models are used. The paper studies different factors effecting technical debt specifically commit frequency, LOC, coverage, code smells and reputation of the contributor. To unveil affect of these variables, SonarQube tool is used to find the technical debt and related metrics. The dataset taken for the purpose is open source version control system from Github. It is proved through the study that as we increase the commit frequency, lines of code, coverage and code smells there is corresponding considerable change in the technical debt as well. While, the reputation factors viz., stars, followers and repositories do not affect technical debt so considerably. The regression model of reputation and TD is also developed.
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