
arXiv: 1604.01450
Technical Debt is a term used to classify non-optimal solutions during software development. These solutions cause several maintenance problems and hence they should be avoided or at least documented. Although there are a considered number of studies that focus on the identification of Technical Debt, we focus on the identification of Technical Debt in pull requests. Specifically, we conduct an investigation to reveal the different types of Technical Debt that can lead to the rejection of pull requests. From the analysis of 1,722 pull requests, we classify Technical Debt in seven categories namely design, documentation, test, build, project convention, performance, or security debt. Our results indicate that the most common category of Technical Debt is design with 39.34%, followed by test with 23.70% and project convention with 15.64%. We also note that the type of Technical Debt influences on the size of push request discussions, e.g., security and project convention debts instigate more discussion than the other types.
Software Engineering (cs.SE), Social and Information Networks (cs.SI), FOS: Computer and information sciences, Computer Science - Software Engineering, Computer Science - Social and Information Networks
Software Engineering (cs.SE), Social and Information Networks (cs.SI), FOS: Computer and information sciences, Computer Science - Software Engineering, Computer Science - Social and Information Networks
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 14 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
