Methods and Tools for TD Estimation and Forecasting: A State-of-the-art Survey

Abstract

Technical debt (TD), a metaphor inspired by the financial debt of economic theory, indicates quality compromises that can yield short-term benefits in the software development process, but may negatively affect the long-term quality of software products. Numerous techniques, methods, and tools have been proposed over the years for estimating and managing TD, providing a variety of options to the developers and project managers of software applications. However, apart from managing TD, predicting its future value is equally important since this knowledge is expected to facilitate decision-making tasks regarding software implementation and maintenance, such as incurring or paying off TD instances. To this end, the purpose of the present study is to (i) summarize the work that has been conducted until today in the field of TD estimation and forecasting, and (ii) to identify existing open issues that have not been adequately addressed yet and require further research. The present survey led to two interesting observations. Firstly, none of the existing TD estimation methods and tools has reached a desired level of maturity, while a large volume of previously uninvestigated metrics and techniques exist that could potentially increase the completeness of TD estimation. Secondly, no notable contributions exist in the field of TD forecasting, indicating that it is a scarcely investigated field. The latter constitutes the main finding of the present literature review, since TD forecasting could lead to the development of practical decision-making mechanisms, which could assist developers and project managers in taking proactive actions regarding TD repayment.