Popular Open Source Software Projects Research Articles

State‐of‐the‐practice in quality assurance in Java‐based open source software development

SummaryTo ensure the quality of software systems, software engineers can make use of a variety of quality assurance approaches, for example, software testing, modern code review, automated static analysis, and build automation. Each of these quality assurance practices have been studied in depth in isolation, but there is a clear knowledge gap when it comes to our understanding of how these approaches are being used in conjunction, or not. In our study, we broadly investigate whether and how these quality assurance approaches are being used in conjunction in the development of 1454 popular open source software projects on GitHub. Our study indicates that typically projects do not follow all quality assurance practices together with high intensity. In fact, we only observe weak correlation among some quality assurance practices. In general, our study provides a deeper understanding of how existing quality assurance approaches are currently being used in Java‐based open source software development. Besides, we specifically zoom in on the more mature projects in our dataset, and generally we observe that more mature projects are more intense in their application of the quality assurance practices, with more focus on their ASAT usage, and code reviewing, but no strong change in their CI usage.

TeReKG: A temporal collaborative knowledge graph framework for software team recommendation

Successful software development requires a cohesive team with the right mix of technical skills and the ability to collaborate effectively. However, forming a software team that can execute tasks with precision and efficiency requires a deep understanding of each member’s competence, experience, and cooperation history. Previously, automated software team selection has evaluated technical skills, cohesion, and cooperation history. However, the previous method had some limitations. Particularly, local features directly calculated from team members were subjective to the researchers’ views, and the method ignored the temporal aspect of open-source software development. To overcome these limitations, this paper proposes a knowledge-graph software team recommendation framework called TeReKG. This framework encapsulates temporal collaboration patterns and uses a temporal knowledge graph to encode software collaboration history, technical abilities, task dependencies, and project structure. TeReKG was against state-of-the-art team recommendation algorithms using three popular open-source software projects: Moodle, Apache, and Atlassian. The evaluation results show that TeReKG outperforms the state-of-the-art baselines in both single-role and team recommendation tasks. These findings demonstrate that knowledge graph embedding can be effectively utilized in automated recommendation tasks in software engineering. Additionally, this highlights the potential for knowledge graphs to capture global information that can benefit various software development applications, including impact prediction of software repositories, code clone detection, and source code retrieval.

Hierarchical and Hybrid Organizational Structures in Open-source Software Projects: A Longitudinal Study

Despite the absence of a formal process and a central command-and-control structure, developer organization in open-source software (OSS) projects are far from being a purely random process. Prior work indicates that, over time, highly successful OSS projects develop a hybrid organizational structure that comprises a hierarchical part and a non-hierarchical part. This suggests that hierarchical organization is not necessarily a global organizing principle and that a fundamentally different principle is at play below the lowest positions in the hierarchy. Given the vast proportion of developers are in the non-hierarchical part, we seek to understand the interplay between these two fundamentally differently organized groups, how this hybrid structure evolves, and the trajectory individual developers take through these structures over the course of their participation. We conducted a longitudinal study of the full histories of 20 popular OSS projects, modeling their organizational structures as networks of developers connected by communication ties and characterizing developers’ positions in terms of hierarchical (sub)structures in these networks. We observed a number of notable trends and patterns in the subject projects: (1) hierarchy is a pervasive structural feature of developer networks of OSS projects; (2) OSS projects tend to form hybrid organizational structures, consisting of a hierarchical and a non-hierarchical part; and (3) the positional trajectory of a developer starts loosely connected in the non-hierarchical part and then tightly integrate into the hierarchical part, which is associated with the acquisition of experience (tenure), in addition to coordination and coding activities. Our study (a) provides a methodological basis for further investigations of hierarchy formation, (b) suggests a number of hypotheses on prevalent organizational patterns and trends in OSS projects to be addressed in further work, and (c) may ultimately guide the governance of organizational structures.

The evolution of the code during review: an investigation on review changes

Code review is a software engineering practice in which reviewers manually inspect the code written by a fellow developer and propose any change that is deemed necessary or useful. The main goal of code review is to improve the quality of the code under review. Despite the widespread use of code review, only a few studies focused on the investigation of its outcomes, for example, investigating the code changes that happen to the code under review. The goal of this paper is to expand our knowledge on the outcome of code review while re-evaluating results from previous work. To this aim, we analyze changes that happened during the review process, which we define as review changes. Considering three popular open-source software projects, we investigate the types of review changes (based on existing taxonomies) and what triggers them; also, we study which code factors in a code review are most related to the number of review changes. Our results show that the majority of changes relate to evolvability concerns, with a strong prevalence of documentation and structure changes at type-level. Furthermore, differently from past work, we found that the majority of review changes are not triggered by reviewers’ comments. Finally, we find that the number of review changes in a code review is related to the size of the initial patch as well as the new lines of code that it adds. However, other factors, such as lines deleted or the author of the review patchset, do not always show an empirically supported relationship with the number of changes.

Prioritization of model smell refactoring using a covariance matrix-based adaptive evolution algorithm

The refactoring process enhances the software design by modifying the structure of design parts impaired with model smells without altering the overall software behavior. However, handling these smells without proper prioritization will not produce the anticipated effects. In this paper, we solve the prioritization of the model smell refactoring using a multi-objective optimization (MOO) algorithm called the multi-objective (MO) covariance matrix adaptation evolution strategy (MO CMA-ES). Our formulation relies on the refactoring of unified modeling language (UML) class diagrams to mitigate the negative effect of design smells. We treat the prioritization problem as a real-valued MOO where we propose novel data encoding procedures. We use two conflicting objectives, quality, and maintainability , to balance the refactoring. We first build a new solution representation that guarantees smell fixing and eliminates the rejection limitation. Furthermore, we suggest a custom mapping scheme to properly encode real-valued quantities using unique representations. For performance evaluation purposes, we developed a large custom dataset with more than 30,000 class records, using seven popular open-source software projects. A novel relative coverage metric is proposed to mitigate the limitations associated with the standard coverage. For benchmarking purposes, we also consider an improved version of the nondominated sorting genetic algorithm (NSGA-II(. The reported performance scores confirm the superiority of the MO CMA-ES algorithm over NSGA-II. The former successfully identified the refactoring sequences that lead to the best improvements in software quality and maintainability while it is able to fix all identified design smells. These improvements are quantified in terms of hypervolume, coverage, spacing metrics, and execution time. The MO CMA-ES attained the highest average maximum quality score of 1149 while keeping the average maintainability at the lowest score of 13.8. In all experiment settings, the proposed solution leads to longer refactoring sequences at no additional computational cost.

Measuring and Modeling Group Dynamics in Open-Source Software Development: A Tensor Decomposition Approach

Many open-source software projects depend on a few core developers, who take over both the bulk of coordination and programming tasks. They are supported by peripheral developers, who contribute either via discussions or programming tasks, often for a limited time. It is unclear what role these peripheral developers play in the programming and communication efforts, as well as the temporary task-related sub-groups in the projects. We mine code-repository data and mailing-list discussions to model the relationships and contributions of developers in a social network and devise a method to analyze the temporal collaboration structures in communication and programming, learning about the strength and stability of social sub-groups in open-source software projects. Our method uses multi-modal social networks on a series of time windows. Previous work has reduced the network structure representing developer collaboration to networks with only one type of interaction, which impedes the simultaneous analysis of more than one type of interaction. We use both communication and version-control data of open-source software projects and model different types of interaction over time. To demonstrate the practicability of our measurement and analysis method, we investigate 10 substantial and popular open-source software projects and show that, if sub-groups evolve, modeling these sub-groups helps predict the future evolution of interaction levels of programmers and groups of developers. Our method allows maintainers and other stakeholders of open-source software projects to assess instabilities and organizational changes in developer interaction and can be applied to different use cases in organizational analysis, such as understanding the dynamics of a specific incident or discussion.

Dual Channel Among Task and Contribution on OSS Communities: An Empirical Study

Open Source Software (OSS) community has attracted a large number of distributed developers to work together, e.g. reporting and discussing issues as well as submitting and reviewing code. OSS developers create links among development units (e.g. issues and pull requests in GitHub), share their opinions and promote the resolution of development units. Although previous work has examined the role of links in recommending high-priority tasks and reducing resource waste, the understanding of the actual usage of links in practice is still limited. To address the research gap, we conduct an empirical study based on the 5W1H model and data mining from five popular OSS projects on GitHub. We find that links originating from a PR are more common than the other three types of links, and links are more frequently created in Documentation. We also find that average duration between development units’ create time in a link is half a year. We observed that link behaviors are very complex and the duration of link increases with the complexity of link structure. We also observe that the reasons of link are very different, especially in P–P and I–I. Finally, future works are discussed in conclusion.

Customer reviews as the measure of software quality

Open Source Software (OSS) has become ubiquitous nowadays. It is crucial for the OSS project managers as well as developers to understand users' perception of quality to remain consistent with producing good quality software. To understand users' point of view, like many studies in the commercial product/service sectors which rely upon customer reviews to understand customer behaviour, the authors' main focus is to analyse user ratings and reviews of OSS projects that may represent user satisfaction for that particular software application. We have analysed 41,428 customer reviews (obtained from SourceForge.net) of 886 most popular OSS projects belonging to a specific domain and programming language. The results indicate that overall user ratings and reviews of the popular OSS projects contain a very positive sentiment and more frequent occurrence of emotions like joy, anticipation, and trust as compared to disgust, fear, and surprise. Further, we have examined that the affectiveness of customer reviews with respect to OSS popularity and quality aspects along with their programming languages and problem domains. The results show a stronger association of review affectiveness with the number of reviews than with the number of downloads of the OSS projects, and more downloads do not mean more reviews.

What Are They Talking About? Analyzing Code Reviews in Pull-Based Development Model

Code reviews in pull-based model are open to community users on GitHub. Various participants are taking part in the review discussions and the review topics are not only about the improvement of code contributions but also about project evolution and social interaction. A comprehensive understanding of the review topics in pull-based model would be useful to better organize the code review process and optimize review tasks such as reviewer recommendation and pull-request prioritization. In this paper, we first conduct a qualitative study on three popular open-source software projects hosted on GitHub and construct a fine-grained two-level taxonomy covering four level-1 categories (code correctness, pull-request decision-making, project management, and social interaction) and 11 level-2 subcategories (e.g., defect detecting, reviewer assigning, contribution encouraging). Second, we conduct preliminary quantitative analysis on a large set of review comments that were labeled by TSHC (a two-stage hybrid classification algorithm), which is able to automatically classify review comments by combining rule-based and machine-learning techniques. Through the quantitative study, we explore the typical review patterns. We find that the three projects present similar comments distribution on each subcategory. Pull-requests submitted by inexperienced contributors tend to contain potential issues even though they have passed the tests. Furthermore, external contributors are more likely to break project conventions in their early contributions.

Understanding the Causes of Architecture Changes Using OSS Mailing Lists

The causes of architecture changes can tell about why architecture changes, and this knowledge can be captured to prevent architecture knowledge vaporization and architecture degeneration. But the causes are not always known, especially in open source software (OSS) development. This makes it very hard to understand the underlying reasons for the architecture changes and design appropriate modifications. Architecture information is communicated in development mailing lists of OSS projects. To explore the possibility of identifying and understanding the causes of architecture changes, we conducted an empirical study to analyze architecture information (i.e. architectural threads) communicated in the development mailing lists of two popular OSS projects: Hibernate and ArgoUML, verified architecture changes with source code, and identified the causes of architecture changes from the communicated architecture information. The main findings of this study are: (1) architecture information communicated in OSS mailing lists does lead to architecture changes in code; (2) the major cause for architecture changes in both Hibernate and ArgoUML is preventative changes, and the causes of architecture changes are further classified to functional requirement, external quality requirement, and internal quality requirement using the coding techniques of grounded theory; (3) more than 45% of architecture changes in both projects happened before the first stable version was released.

Predicting Consistency-Maintenance Requirement of Code Clonesat Copy-and-Paste Time

Code clones have always been a double edged sword in software development. On one hand, it is a very convenient way to reuse existing code, and to save coding effort. On the other hand, since developers may need to ensure consistency among cloned code segments, code clones can lead to extra maintenance effort and even bugs. Recently studies on the evolution of code clones show that only some of the code clones experience consistent changes during their evolution history. Therefore, if we can accurately predict whether a code clone will experience consistent changes, we will be able to provide useful recommendations to developers onleveraging the convenience of some code cloning operations, while avoiding other code cloning operations to reduce future consistency maintenance effort. In this paper, we define a code cloning operation as consistency-maintenance-required if its generated code clones experience consistent changes in the software evolution history, and we propose a novel approach that automatically predicts whether a code cloning operation requires consistency maintenance at the time point of performing copy-and-paste operations. Our insight is that whether a code cloning operation requires consistency maintenance may relate to the characteristics of the code to be cloned and the characteristics of its context. Based on a number of attributes extracted from the cloned code and the context of the code cloning operation, we use Bayesian Networks, a machine-learning technique, to predict whether an intended code cloning operation requires consistency maintenance. We evaluated our approach on four subjects—two large-scale Microsoft software projects, and two popular open-source software projects—under two usage scenarios: 1) recommend developers to perform only the cloning operations predicted to be very likely to be consistency-maintenance-free, and 2) recommend developers to perform all cloning operations unless they are predicted very likely to be consistency-maintenance-required. In the first scenario, our approach is able to recommend developers to perform more than 50 percent cloning operations with a precision of at least 94 percent in the four subjects. In the second scenario, our approach is able to avoid 37 to 72 percent consistency-maintenance-required code clones by warning developers on only 13 to 40 percent code clones, in the four subjects.

A Preventive Risk Analysis for Managing Distributed Software Projects based on Deliverable

In a distributed software development environment, software projects are geographically distributed with minimal face-toface interaction between team members. Recent software functions are delegated to popular open source software projects: -examples like Mozilla Firefox, Google Chromium, Android and the Apache OpenOffice Suite, etc. So the managers must know how to perform distributed projects and its team. Most of software risk management is done throughout the whole project from inception to commissioning. The aim of this study is to understand the need for the risk assessment and management based on deliverable for both agile and traditional methods of software development process. In this study, the authors propose a model, where the protective risk analysis can be done based on the deliverables, so that require mitigations can be provided. Mitigation factors can be also based on the seriousness of the deliverable