Got Issues? Who Cares About It? An Investigation of Issue Trackers of 10 5 Projects (original) (raw)
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Issue Tracking Systems: What Developers Want and Use
Proceedings of the 13th International Conference on Software Technologies
An Issue Tracking System (ITS) allows a developer to keep track of, prioritize, and assign multitudes of bugs, feature requests, and other development tasks such as testing. Despite ITSs play a significant role in day-today developers' activities, no previous study investigated what developers want and use in an ITS. The aim of this paper is twofold. First, we provide a feature matrix that maps six of the most used ITS to features, and second, we measure the developers' level of use and perceived importance of each feature. This knowledge has multiple benefits such as supporting the decision of the ITS to use and revealing promising areas of research and development. Specifically, quality improvement effort should target improving functionality in use, and development effort should target supporting functionalities needed. In this paper, we define and extract ten core ITS features and asked more than a hundred developers to rate their importance and use. Our results show that Advanced Search and Flexible Notifications are the most important features. Moreover, results show that no feature has been used by more than 90% of the respondents. Another interesting finding is that 27% of respondents rate Workflow Automation as a useful or required feature, despite having never used it themselves; this suggests the need to better training, exposure or of availability of ITS features. In conclusion, our results pave the way to significant research and development effort on ITS.
Communication, collaboration, and bugs: The social nature of issue tracking in software engineering
2010
ABSTRACT Issue tracking systems help organizations manage issue reporting, assignment, tracking, resolution, and archiving. Traditionally, it is the Software Engineering community that researches issue tracking systems, where software defects are reported and tracked as 'bug reports' within an archival database. Yet issue tracking is fundamentally a social process and, as such, it is important to understand the design and use of issue tracking systems from that perspective.
Exploring the use of labels to categorize issues in Open-Source Software projects
2015 IEEE 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER), 2015
Reporting bugs, asking for new features and in general giving any kind of feedback is a common way to contribute to an Open-Source Software (OSS) project. This feedback is generally reported in the form of new issues for the project, managed by the so-called issue-trackers. One of the features provided by most issue-trackers is the possibility to define a set of labels/tags to classify the issues and, at least in theory, facilitate their management. Nevertheless, there is little empirical evidence to confirm that taking the time to categorize new issues has indeed a beneficial impact on the project evolution. In this paper we analyze a population of more than three million of GitHub projects and give some insights on how labels are used in them. Our preliminary results reveal that, even if the label mechanism is scarcely used, using labels favors the resolution of issues. Our analysis also suggests that not all projects use labels in the same way (e.g., for some labels are only a way to prioritize the project while others use them to signal their temporal evolution as they move along in the development workflow). Further research is needed to precisely characterize these label "families" and learn more the ideal application scenarios for each of them. 978-1-4799-8469-5/15 c 2015 IEEE SANER 2015, Montréal, Canada Accepted for publication by IEEE. c 2015 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.
Does your Bug Tracking tool suit your needs? A Study on Open Source Bug Tracking tools
2017
Bug tracking tools are vital for managing bugs in any open source as well as proprietary commercial projects. Considering the significance of using an appropriate bug tracking tool, we assess the features offered by 31 open source bug tracking tools and their significance of usage in open source projects. We have categorized these tools into different classes based on their features. We have also conducted a developer survey by working with open source software practitioners to understand the effectiveness of these tools in their day-today software development. We also explored StackOverFlow-a developer Q&A forum to understand the developer experiences and challenges while using open source bug tracking tools. Our observations generated encouraging results that can used as a recommendation guide for open source software community to choose the best bug tracking tool based on their functional needs. Additionally, we have identified few features that are needed but not offered by most of these bug tracking tools.
Open Source Systems, 2020
In this work we are studying the sentiment in Open Source Software projects and more specifically in the process of bug reporting, to investigate the human factor, namely, the feedback from the community (end-users, developers, testers, etc.). One of the characteristics for which Open Source Software has gained attention, over the years, is the fact that it is continuously being tested and maintained by its community of volunteers. Sentiment analysis, a rapidly growing field, can enrich software evaluation with a social aspect. Results suggest that FLOSS projects’ bug reports can potentially constitute a rich emotionally - imbued information source.
Exploring the Characteristics of Issue-Related Behaviors in GitHub Using Visualization Techniques
IEEE Access
Feedback from software users, such as bug reports, is vital in the management of software projects. In GitHub, the feedback is typically expressed as new issues. Through filing issue reports, users may help identify and fix bugs, document software code, and enhance software quality via feature requests. In this paper, we aim at investigating some characteristics of issues to facilitate issue management and software management. We investigate the important degrees of behaviors that are related to issues in popular projects to assess the importance of issues in GitHub and analyze the effectiveness of issue labeling for issue handling. Then, we explore the patterns of issue commits over time in popular projects based on visual analysis and obtain the following results: we find that the behaviors that are related to issues play important roles in the GitHub. We also find that the time distribution of issue commits follows a three-period development model, which approximately corresponds to the project life cycle. These results may provide a new knowledge about issues that can help managers manage and allocate project resources more effectively and even reduce software failures. INDEX TERMS Open-source software community, project development model, visual analysis, issue commit, software management.
Predicting the Objective and Priority of Issue Reports in Software Repositories
2020
Software repositories such as GitHub host a large number of software entities. Developers collaboratively discuss, implement, use, and share these entities. Proper documentation plays an important role in successful software management and maintenance. Users exploit Issue Tracking Systems, a facility of software repositories, to keep track of issue reports, to manage the workload and processes, and finally, to document the highlight of their team’s effort. An issue report is a rich source of collaboratively-curate software knowledge, and can contain a reported problem, a request for new features, or merely a question about the software product. As the number of these issues increases, it becomes harder to manage them manually. GitHub provides labels for tagging issues, as a means of issue management. However, about half of the issues in GitHub’s top 1000 repositories do not have any labels. In this work, we aim at automating the process of managing issue reports for software teams. ...
Empirical validation of human factors on predicting issue resolution time in open source projects
Software developers often spend a significant portion of their resources resolving submitted evolution issue reports. Classification or prediction of issue lead time is useful for prioritizing evolution issues and supporting human resources allocation in software maintenance. However, the predictability of issue lead time is still a research gap that calls for more empirical investigation.In this paper, we empirically assess different types of issue lead time prediction models using human factor measures collected from issue tracking systems. We conduct an empirical investigation of three active open source projects. A machine learning based classification and statistical univariate and multivariate analyses are performed. The accuracy of classification models in ten-fold cross-validation varies from 75.56% to 91%. The R2 value of linear multivariate regression models ranges from 0.29 to 0.60. Correlation analysis confirms the effectiveness of collaboration measures, such as the number of stakeholders and number of comments, in prediction models. The measures of assignee past performance are also an effective indicator of issue lead time. The results indicate that the number of stakeholders and average past issue lead time are important variables in constructing prediction models of issue lead time. However, more variables should be explored to achieve better prediction performance.
On the Use of Issue Tracking Annotations for Improving Developer Activity Metrics
Advances in Software Engineering, 2011
Understanding and measuring how teams of developers collaborate on software projects can provide valuable insight into the software development process. Currently, researchers and practitioners measure developer collaboration with social networks constructed from version control logs. Version control change logs, however, do not tell the whole story. The collaborative problem-solving process is also documented in the issue tracking systems that record solutions to failures, feature requests, or other development tasks. We propose two ...
Improving developer activity metrics with issue tracking annotations
Proceedings - International Conference on Software Engineering, 2010
Understanding and measuring how groups of developers collaborate on software projects can provide valuable insight into software quality and the software development process. Current practices of measuring developer collaboration (e.g. with social network analysis) usually employ metrics based on version control change log data to determine who is working on which part of the system. Version control change logs, however, do not tell the whole story. Information about the collaborative problemsolving process is also documented in the issue tracking systems that record solutions to failures, feature requests, or other development tasks. To enrich the data gained from version control change logs, we propose two annotations to be used in issue tracking systems: solution originator and solution approver. We examined the online discussions of 602 issues from the OpenMRS healthcare web application, annotating which developers were the originators of the solution to the issue, or were the approvers of the solution. We used these annotations to augment the version control change logs and found 47 more contributors to the OpenMRS project than the original 40 found in the version control change logs. Applying social network analysis to the data, we found that central developers in a developer network have a high likelihood of being approvers. These results indicate that using our two issue tracking annotations identify project collaborators that version control change logs miss. However, in the absence of our annotations, developer network centrality can be used as an estimate of the project's solution approvers. This improvement in developer activity metrics provides a valuable connection between what we can measure in the project development artifacts and the team's problem-solving process.