Reusing Code from StackOverflow: The Effect on Technical Debt

Abstract

Software reuse is a well-established software engineering process that aims at improving development productivity. Although reuse can be performed in a systematic way (e.g., through product lines), in practice, reuse is performed in many cases opportunistically, i.e., copying small code chunks either from the web or in-house developed projects. Knowledge sharing communities and especially StackOverflow constitute the primary source of code-related information for amateur and professional software developers. Despite the obvious benefit of increased productivity, reuse can have a mixed effect on the quality of the resulting code depending on the properties of the reused solutions. An efficient concept for capturing a wide-range of internal software qualities is the metaphor of Technical Debt which expresses the impact of shortcuts in software development on its maintenance costs. In this paper, we present the results of an empirical study on the relation between the existence of reusing code retrieved from StackOverflow on the technical debt of the target system. In particular, we study several open-source projects and identify non-trivial pieces of code that exhibit a perfect or near-perfect match with code provided in the context of answers in StackOverflow. Then, we compare the technical debt density of the reused fragments, obtained as the ratio of inefficiencies identified by SonarQube over the lines of reused code, to the technical debt density of the target codebase. The results provide insights to the potential impact of small-scale code reuse on technical debt and highlight the benefits of assessing code quality before committing changes to a repository.

Systematic Exploration and Classification of Useful Comments in Stack Overflow

“…Furthermore, it was stated that the approach might be inadequate in recommending comments for the code segment from proprietary or legacy projects [4]. The value of comments revolves around many important aspects such as improving the source code, analyzing the code further, and facilitating code reuse [4] [17] [18] [19]. During the Exploration of the means of which comments have an effect on answer updates, comments and answer updates which involve code segments were only being taken into consideration.…”

analyzeR: A SonarQube plugin for analyzing object-oriented R Packages

“…SonarQube was combined with Arcan to study Architectural Debt and opportunistic code reuse in Java projects, determining that 'cyclic dependency' is a typical smell [32]. SonarQube was also applied to StackOverflow's Java code snippets, determining that reused code tends to exhibit ''a substantially lower TD density'' [33]. A large-scale analysis based on GitHub's annual report analyzed SonarQube's coding violations and mapped them to the most common code smells by Fowler [34]; this enabled estimating developers' profiles according to coding maturity and TD tolerance, among other points.…”

Investigating the Interaction between Energy Consumption, Quality of Service, Reliability, Security, and Maintainability of Computer Systems and Networks

“…platform and FITTED framework [2], (ii) TD Evaluation of New Code, which is responsible for assessing the TD of the newly added code and prevent the new code from being committed to the software repository if its value is high, and (iii) TD Refactorings Identification, which is responsible for suggesting code-, architecture-, and designlevel refactorings that are expected to improve the TD of the analysed application. A multitude of novel features have been developed within the course of the SDK4ED project with respect to the aforementioned solutions (i.e., services) [1,2,4,5,8,9,16,23,35,37,39].…”