Technical Debt Prioritization: State of the Art. A Systematic Literature Review

Background. Software companies need to manage and refactor Technical Debt issues. Therefore, it is necessary to understand if and when refactoring Technical Debt should be prioritized with respect to developing features or fixing bugs. Objective. The goal of this study is to investigate the existing body of knowledge in software engineering to understand what Technical Debt prioritization approaches have been proposed in research and industry. Method. We conducted a Systematic Literature Review among 384 unique papers published until 2018, following a consolidated methodology applied in Software Engineering. We included 38 primary studies. Results. Different approaches have been proposed for Technical Debt prioritization, all having different goals and optimizing on different criteria. The proposed measures capture only a small part of the plethora of factors used to prioritize Technical Debt qualitatively in practice. We report an impact map of such factors. However, there is a lack of empirical and validated set of tools. Conclusion. We observed that technical Debt prioritization research is preliminary and there is no consensus on what are the important factors and how to measure them. Consequently, we cannot consider current research conclusive and in this paper, we outline different directions for necessary future investigations

Influence of developer factors on code quality: a data study

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Automatic source-code inspection tools help to assess, monitor and improve code quality. Since these tools only examine the software project’s codebase, they overlook other possible factors that may impact code quality and the assessment of the technical debt (TD). Our initial hypothesis is that human factors associated with the software developers, like coding expertise, communication skills, and experience in the project have some measurable impact on the code quality. In this exploratory study, we test this hypothesis on two large open source repositories, using TD as a code quality metric and the data that may be inferred from the version control systems. The preliminary results of our statistical analysis suggest that the level of participation of the developers and their experience in the project have a positive correlation with the amount of TD that they introduce. On the contrary, communication skills have barely any impact on TD.Peer ReviewedPostprint (author's final draft

An analysis of techniques and methods for technical debt management: a reflection from the architecture perspective

Technical debt is a metaphor referring to the consequences of weak software development. Managing technical debt is necessary in order to keep it under control, and several techniques have been developed with the goal of accomplishing this. However, available techniques have grown disperse and managers lack guidance. This paper covers this gap by providing a systematic mapping of available techniques and methods for technical debt management, covering architectural debt, and identifying existing gaps that prevent to manage technical debt efficiently

What do we know about succession in family businesses? Mapping current knowledge and unexplored territory

We review studies on succession in family businesses that have been done since Handler’s (1994) seminal literature review on the topic in an effort to synthesize existing research and outline paths for future studies. We offer three contributions. First, we select succession studies that adhere to established methodological standards. Second, we review these studies based on the perspective that succession is a process comprising five stages across three levels of analysis. Finally, we outline current gaps in our knowledge and ask researchers to adopt a more holistic approach when studying succession