How do developers fix issues and pay back technical debt in the Apache ecosystem?

During software evolution technical debt (TD) follows a constant ebb and flow, being incurred and paid back, sometimes in the same day and sometimes ten years later. There have been several studies in the literature investigating how technical debt in source code accumulates during time and the consequences of this accumulation for software maintenance. However, to the best of our knowledge there are no large scale studies that focus on the types of issues that are fixed and the amount of TD that is paid back during software evolution. In this paper we present the results of a case study, in which we analyzed the evolution of fifty-seven Java open-source software projects by the Apache Software Foundation at the temporal granularity level of weekly snapshots. In particular, we focus on the amount of technical debt that is paid back and the types of issues that are fixed. The findings reveal that a small subset of all issue types is responsible for the largest percentage of TD repayment and thus, targeting particular violations the development team can achieve higher benefits

Does it matter who pays back Technical Debt? An empirical study of self-fixed TD

Context: Technical Debt (TD) can be paid back either by those that incurred it or by others. We call the former self-fixed TD, and it can be particularly effective, as developers are experts in their own code and are well-suited to fix the corresponding TD issues. Objective: The goal of our study is to investigate self-fixed technical debt, especially the extent in which TD is self-fixed, which types of TD are more likely to be self-fixed, whether the remediation time of self-fixed TD is shorter than non-self-fixed TD and how development behaviors are related to self-fixed TD. Method: We report on an empirical study that analyzes the self-fixed issues of five types of TD (i.e., Code, Defect, Design, Documentation and Test), captured via static analysis, in more than 44,000 commits obtained from 20 Python and 16 Java projects of the Apache Software Foundation. Results: The results show that about half of the fixed issues are self-fixed and that the likelihood of contained TD issues being self-fixed is negatively correlated with project size, the number of developers and total issues. Moreover, there is no significant difference of the survival time between self-fixed and non-self-fixed issues. Furthermore, developers are more keen to pay back their own TD when it is related to lower code level issues, e.g., Defect Debt and Code Debt. Finally, developers who are more dedicated to or knowledgeable about the project contribute to a higher chance of self-fixing TD. Conclusions: These results can benefit both researchers and practitioners by aiding the prioritization of TD remediation activities and refining strategies within development teams, and by informing the development of TD management tools

Evolution of technical debt remediation in Python: A case study on the Apache Software Ecosystem

In recent years, the evolution of software ecosystems and the detection of technical debt received significant attention by researchers from both industry and academia. While a few studies that analyze various aspects of technical debt evolution already exist, to the best of our knowledge, there is no large-scale study that focuses on the remediation of technical debt over time in Python projects -- i.e., one of the most popular programming languages at the moment. In this paper, we analyze the evolution of technical debt in 44 Python open-source software projects belonging to the Apache Software Foundation. We focus on the type and amount of technical debt that is paid back. The study required the mining of over 60K commits, detailed code analysis on 3.7K system versions, and the analysis of almost 43K fixed issues. The findings show that most of the repayment effort goes into testing, documentation, complexity and duplication removal. Moreover, more than half of the Python technical debt in the ecosystem is short-term being repaid in less than two months. In particular, the observations that a minority of rules account for the majority of issues fixed and spent effort, suggest that addressing those kinds of debt in the future is important for research and practice