Dual analysis for helping developers to find collaborators based on co‐changed files: An empirical study

Abstract

Summary Software developers must collaborate at all stages of the software life‐cycle to create successful complex software systems. To enable this collaboration, social coding platforms, for example, GitHub, include an increasing number of tools to support collaboration. However, for large projects with hundreds of dynamic developers, such as several successful open–source projects, it can be complex to find developers with the same interest and familiarity and thus, gain suitable collaborations and new insights. In this context, resources and efforts may be wasted, discouraging many developers from contributing. Moreover, it can be costly to manage many contributions, which is another challenge for the maintainer who wants to take advantage of this small, timid, but valuable contribution made by a volunteer developer in a short time. In this context, this paper presents an empirical study aiming to evaluate two strategies to recommend collaborators based on co‐changed files. Inspired in the TF–IDF (Term Frequency–Inverse Document Frequency) weighting scheme established in the Information Retrieval field, these strategies first estimate the importance of relevant files modified by developers and use these estimates to represent each developer “profile”. As a second step, they estimate the similarity between developers using the Cosine metric, providing top‐ranked developers according to this measure as recommendations. We evaluated these strategies based on an extensive survey with 102 real–world developers. We observed that developers have interest and familiarity with the co‐changed files for all strategies evaluated. These considerations are of relevance because many opportunities for contributions to the project are linked to coding. Thus, theses results may indicate one less barrier for improving collaboration among developers. Overall, the strategies present an acceptance rate of up to 81%, contributing to the discovery of further collaborators.

Experiences and challenges from developing cyber‐physical systems in industry‐academia collaboration

“…36 As a consequence, the CPSs require to be continuously updated and improved to meet these quality attributes. 21 Constantino et al 22 investigate a means of evaluating collaborative compatibility through examining co-changed files. They evaluate two strategies and through interviews conclude that they can predict suitable collaborators based on their previous history in development.…”

A User Evaluation of a Collaborator Recommender based on Co-Changed Files

“…For Strategy 2, the number of changed lines of code (LoC) was extracted. This metric computes the sum of code lines added and removed by a developer in a specific file [Constantino et al, 2023a]. Figure 1 presents an [Constantino et al, 2023a].…”

“…Inspired by these previous work [Canfora et al, 2012; Thongtanunam et al, 2015, we recommend collaborators based on a set of files that have been mutually edited to increase engagement in the project and enhance the opportunities for collaborations, not only core members, code-reviewers, or mentors but also all active collaborators of the project that need some help. In this work, we have denominated these mutually edited files as co-changed files [Constantino et al, 2023a; Constantino andFigueiredo, 2023].…”

“…In previous work, we presented a prototype-tool named CoopFinder 2 [Constantino and Figueiredo, 2022], which supports two developer recommendation strategies. In another previous work [Constantino et al, 2023a], we evaluated these developer recommendation strategies based on cochanged files from the point of view of who receives the recommendations. We observed that these strategies helped developers and maintainers find opportunities for collaborations.…”

Recommending Collaborators Based on Co–Changed Files: A Controlled Experiment

“…Inspired by these previous work [Canfora et al 2012, Thongtanunam et al 2015, we recommend collaborators based on a set of files that have been mutually edited to increase engagement in the project and enhance the opportunities for collaborations, not only core members, code-reviewers, or mentors but also any developer in the project. In this work, we have denominated these mutually edited files as co-changed files [Constantino et al 2023].…”