Abstract
Technical debt is a concept used to describe the lack of good practices during software development, leading to several problems and costs. Identification and management strategies can help reduce these difficulties. In a previous study, Alves et al. (2016) analyzed the research landscape of such strategies from 2010 to 2014. This paper replicates and updates their study to explore the evolution of technical debt identification and management research landscape over a decade, including literature from 2010 until 2022. We analyzed 117 papers from the ACM Digital Library, IEEE Xplore, Science Direct, and Springer Link. Newly suggested strategies include automatically identifying admitted debt in comments, commits, and source code. Between 2015 and 2022, more empirical evaluations have been performed, and the general research focus has changed to a more holistic approach. Therefore, the research area evolved and reached a new level of maturity compared to previous results from Alves et al. (2016). Not only are code aspects considered for technical debt, but other aspects have also been investigated (e.g., models for the development process).
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