| 2020 | |
| [1] | , "Technical Debt Aware Estimations in Software Engineering: A Systematic Mapping Study", In e-Informatica Software Engineering Journal, vol. 14, no. 1, pp. 61–76, 2020.
DOI: 10.37190/e-Inf200102. Download article (PDF)Get article BibTeX file |
Authors
Paweł Klimczyk, Lech Madeyski
Abstract
Context: The Technical Debt metaphor has grown in popularity. More software is being created and has to be maintained. Agile methodologies, in particular Scrum, are widely used by development teams around the world. Estimation is an often practised step in sprint planning. The subject matter of this paper is the impact technical debt has on estimations.
Objective: The goal of this research is to identify estimation problems and their solutions due to previously introduced technical debt in software projects.
Method: The Systematic mapping study (SMS) method was applied in the research. Papers were selected from the popular digital databases (IEEE, ACM, Scopus, etc.) using defined search criteria. Afterwards, a snowballing procedure was performed and the final publication set was filtered using inclusion/exclusion criteria.
Results: 42 studies were selected and evaluated. Five categories of problems and seven proposed solutions to the problems have been extracted from the papers. Problems include items related to business perspective (delivery pressure or lack of technical debt understanding by business decision-makers) and technical perspective (difficulties in forecasting architectural technical debt impact or limits of source code analysis). Solutions were categorized in: more sophisticated decision-making tools for business managers, better tools for estimation support and technical debt management tools on an architectural-level, portfolio approach to technical debt, code audit and technical debt reduction routine conducted every sprint.
Conclusion: The results of this mapping study can help taking the appropriate approach in technical debt mitigation in organizations. However, the outcome of the conducted research shows that the problem of measuring technical debt impact on estimations has not yet been solved. We propose several directions for further investigation. In particular, we
would focus on more sophisticated decision-making tools.
Keywords
Software estimation, technical debt, project management, decision making, change impact
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