Managing Technical Debt

Technical debt (TD) is a metaphor of bad software
design or immature artifacts of a software system. The metaphor has been quite intensively researched especially on how to identify the TD symptoms, (e.g., system deficiencies or architecture violations) explicitly. Although the TD identification is quite important in the TD management process, a systematic management of TD and how to reduce it should also be considered important in each release of the development project. Otherwise, the software becomes more and more unmaintainable. In this paper, we introduce a framework to manage and reduce the TD of software systems. As it is based on quantification and a cost-benefit analysis, it is called Cost-Benefit based Technical Debt Management (CoBeTDM). CoBeTDM defines explicit phases focusing on the most important aspects of TD management: identification, monitoring, and prioritization. Overall, CoBeTDM should support managers to take the right decisions regarding the software evolution and the reduction of the collected TD at the right time.

The management of technical debt and the use of productivity games are important aspects of developing software projects. A productivity game was created in the form of a competitive source control plug-in that rewards technical debt-reducing actions. The plug-in was tested by simulating source control usage with in a small sample project. Analysis showed that the plug-in appropriately assigned scores to developers for debt-reducing and debt-increasing actions. The plug-in has potential practical applications in the management of technical debt in workplace environments. The approach described in this paper is promising, and in future work we plan to test the Build Game plug-in with a wider variety of existing and simulated projects. Additional research is also planned to investigate the impact of the Build Game plug-in on workplace productivity.

Social debt is analogous to technical debt in many ways: it represents the state of software development organisations as the result of “accumulated” decisions. In the case of social debt, decisions are about people and their interactions. Our objective was to study the causality around social debt in practice. In so doing, we conducted exploratory qualitative research in a large software company. We found many forces together causing social debt; we represented them in a framework, and captured anti-patterns that led to the debt in the first place. Finally, we elicited best practices that technicians adopted to pay back some of the accumulated debt. We learned that social debt is strongly correlated with technical debt and both forces should be reckoned with together during the software process.

Hasty software development can produce immediate implementations with source code unnecessarily complex and hardly readable. These small kinds of software decay generate a technical debt that could be big enough to seriously affect future maintenance activities. This work presents an analysis technique for identifying architectural technical debt related to nonuniformity of naming patterns; the technique is based on term frequency over package hierarchies. The proposal has been evaluated on projects of two popular organizations, Apache and Eclipse. The results have shown that most of the projects have frequent occurrences of the proposed naming patterns, and using a graph model and aggregated data could enable the elaboration of simple queries for debt identification. The technique has features that favor its applicability on emergent architectures and agile software development.