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High-quality source code comments are valuable for software development and maintenance, however, code often contains low-quality comments or lacks them altogether. We name such source code comments as suboptimal comments. Such suboptimal comments create challenges in code comprehension and maintenance. Despite substantial research on low-quality source code comments, empirical knowledge about commenting practices that produce suboptimal comments and reasons that lead to suboptimal comments are lacking. We help bridge this knowledge gap by investigating (1)  independent comment changes (ICCs) —comment changes committed independently of code changes—which likely address suboptimal comments, (2) commenting guidelines, and (3) comment-checking tools and comment-generating tools, which are often employed to help commenting practice—especially to prevent suboptimal comments. We collect 24M+ comment changes from 4,392 open-source GitHub Java repositories and find that ICCs widely exist. The ICC ratio —proportion of ICCs among all comment changes—is ~15.5%, with 98.7% of the repositories having ICC. Our thematic analysis of 3,533 randomly sampled ICCs provides a three-dimensional taxonomy for what is changed (four comment categories and 13 subcategories), how it changed (six commenting activity categories), and what factors are associated with the change (three factors). We investigate 600 repositories to understand the prevalence, content, impact, and violations of commenting guidelines. We find that only 15.5% of the 600 sampled repositories have any commenting guidelines. We provide the first taxonomy for elements in commenting guidelines: where and what to comment are particularly important. The repositories without such guidelines have a statistically significantly higher ICC ratio, indicating the negative impact of the lack of commenting guidelines. However, commenting guidelines are not strictly followed: 85.5% of checked repositories have violations. We also systematically study how developers use two kinds of tools, comment-checking tools and comment-generating tools, in the 4,392 repositories. We find that the use of Javadoc tool is negatively correlated with the ICC ratio, while the use of Checkstyle has no statistically significant correlation; the use of comment-generating tools leads to a higher ICC ratio. To conclude, we reveal issues and challenges in current commenting practice, which help understand how suboptimal comments are introduced. We propose potential research directions on comment location prediction, comment generation, and comment quality assessment; suggest how developers can formulate commenting guidelines and enforce rules with tools; and recommend how to enhance current comment-checking and comment-generating tools. 

Open source software ecosystems evolve ways to balance the workload among groups of participants ranging from core groups to peripheral groups. As ecosystems grow, it is not clear whether the mechanisms that previously made them work will continue to be relevant or whether new mechanisms will need to evolve. The impact of failure for critical ecosystems such as Linux is enormous, yet the understanding of why they function and are effective is limited. We, therefore, aim to understand how the Linux kernel sustains its growth, how to characterize the workload of maintainers, and whether or not the existing mechanisms are scalable. We quantify maintainers’ work through the files that are maintained, and the change activity and the numbers of contributors in those files. We find systematic differences among modules; these differences are stable over time, which suggests that certain architectural features, commercial interests, or module-specific practices lead to distinct sustainable equilibria. We find that most of the modules have not grown appreciably over the last decade; most growth has been absorbed by a few modules. We also find that the effort per maintainer does not increase, even though the community has hypothesized that required effort might increase. However, the distribution of work among maintainers is highly unbalanced, suggesting that a few maintainers may experience increasing workload. We find that the practice of assigning multiple maintainers to a file yields only a power of 1/2 increase in productivity. We expect that our proposed framework to quantify maintainer practices will help clarify the factors that allow rapidly growing ecosystems to be sustainable. 

Code contributions in Free/Libre and Open Source Software projects are controlled to maintain high-quality of software. Alternatives to patch-based code contribution tools such as mailing lists and issue trackers have been developed with the pull request systems being the most visible and widely available on GitHub. Is the code contribution process more effective with pull request systems? To answer that, we quantify the effectiveness via the rates contributions are accepted and ignored, via the time until the first response and final resolution and via the numbers of contributions. To control for the latent variables, our study includes a project that migrated from an issue tracker to the GitHub pull request system and a comparison between projects using mailing lists and pull request systems. Our results show pull request systems to be associated with reduced review times and larger numbers of contributions. However, not all the comparisons indicate substantially better accept or ignore rates in pull request systems. These variations may be most simply explained by the differences in contribution practices the projects employ and may be less affected by the type of tool. Our results clarify the importance of understanding the role of tools in effective management of the broad network of potential contributors and may lead to strategies and practices making the code contribution more satisfying and efficient from both contributors' and maintainers' perspectives.