Main_Paper.tex

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\begin{document}

\title{A Framework for Estimating Interest on Technical Debt by Monitoring Developer Activity Related to Code Comprehension}

\author{
\IEEEauthorblockN{Vallary Singh}
\IEEEauthorblockA{%
    University of Delaware\\
    Newark, DE USA\\
    vallary@udel.edu}
\and
\IEEEauthorblockN{Will Snipes and Nicholas A. Kraft}
\IEEEauthorblockA{%
    ABB Corporate Research\\
    Raleigh, NC USA\\
    \{will.snipes, nicholas.a.kraft\}@us.abb.com}
}

\maketitle

\begin{abstract}
Evaluating technical debt related to code structure at a fine-grained level of detail is feasible using static code metrics to identify troublesome areas of a software code base.  However, estimating the interest payments at a similar level of detail is a manual process relying on developers to submit their estimates as they encounter instances of technical debt.  We propose a framework that continuously estimates interest payments using code comprehension metrics produced by a tool that monitors developer activities in the Integrated Development Environment.  We describe the framework and demonstrate how it is used to evaluate the presence of technical debt and interest payments accumulated for code in an industrial software product.
\end{abstract}

\begin{IEEEkeywords}
Technical debt; program comprehension; static analysis; software maintenance; code metrics; code smells
\end{IEEEkeywords}

\section{Introduction}
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\section{Framework}
\label{sec:DataFramework}
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\section{Analysis}
\label{sec:AnalysisResults}
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\section{Conclusions and Future Ideas}
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\vspace*{-4mm}
\section*{Acknowledgment}
The authors would like to thank ABB Corporate Research for supporting this work.

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