Estimation and Prediction of technical debt: a proposal
Alvine Boaye Belle

TL;DR
This paper discusses the importance of accurately estimating and predicting technical debt in software development to improve management and reduce costs, highlighting current limitations and proposing future research directions.
Contribution
It identifies gaps in existing techniques for estimating and predicting technical debt and proposes research to enhance these methods and assess their economic impact.
Findings
Current estimation techniques focus mainly on requirements, code, and tests.
Technical debt prediction is underexplored but crucial for cost savings.
Improved methods could help companies avoid significant financial losses.
Abstract
Technical debt is a metaphor used to convey the idea that doing things in a "quick and dirty" way when designing and constructing a software leads to a situation where one incurs more and more deferred future expenses. Similarly to financial debt, technical debt requires payment of interest in the form of the additional development effort that could have been avoided if the quick and dirty design choices have not been made. Technical debt applies to all the aspects of software development, spanning from initial requirements analysis to deployment, and software evolution. Technical debt is becoming very popular from scientific and industrial perspectives. In particular, there is an increase in the number of related papers over the years. There is also an increase in the number of related tools and of their adoption in the industry, especially since technical debt is very pricey and…
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Taxonomy
TopicsSoftware Engineering Research · Software Reliability and Analysis Research · Open Source Software Innovations
