Tools for the Study of the Usual Data Sources found in Libre Software Projects

Robles, Gregório; González-Barahona, Jesús M.; Izquierdo-Cortázar, Daniel; Erlandson, Benjamin E.

doi:10.4018/9781605660608.ch070

Cited by 6 publications

(10 citation statements)

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“…We have then obtained the meta-data from those repositories where a UML file has been identified by means of using the CVSAnalY tool [124] (step 3). Section 3.4.4 discusses tool's settings and the meta-data structure.…”

Section: Methodsmentioning

confidence: 99%

“…We downloaded all repositories where at least one (real) UML file was identified and extracted its metadata with the help of CVSAnalY [124]. 100 repositories from the initial list could not be retrieved, due to various reasons, from some giving errors to others having changed to private repositories.…”

Section: Metadata Extraction and Queryingmentioning

confidence: 99%

“…For all projects that contain a UML file, development meta-data from the repositories has been retrieved. Therefore, we use perceval, an evolution of the well-known CVSanalY software [124], that allows to obtain these data in JSON files, allowing to perform the data extraction process in parallel. It took the five instances of the tool over 4 weeks to complete this task.…”

Section: Extracting Meta-datamentioning

confidence: 99%

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An Automated Approach for Classifying Reverse-Engineered and Forward-Engineered UML Class Diagrams

Osman

Ho-Quang

Chaudron

2018

2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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Context: In modern software development, software modeling is considered to be an essential part of the software architecture and design activities. The Unified Modeling Language (UML) has become the de facto standard for software modeling in industry. Surprisingly, there are only a few empirical studies on the practices and impacts of UML modeling in software development. This is mainly due to the lack of empirical data on real-life software systems that use UML modeling. Objective: This PhD thesis contributes to this matter by describing a method to build and curate a big corpus of open-source-software (OSS) projects that contain UML models. Subsequently, this thesis offers observations on the practices and impacts of using UML modeling in these OSS projects. Method: We combine techniques from repository mining and image classification in order to successfully identify more than 24.000 open source projects on GitHub that together contain more than 93.000 UML models. Machine learning techniques are also used to enrich the corpus with annotations. Finally, various empirical studies, including a case study, a user study, a large-scale survey and an experiment, have been carried out across this set of projects. Result: The results show that UML is generally perceived to be helpful to new contributors. The most important motivation for using UML seems to be to facilitate collaboration. In particular, teams use UML during communication and planning of joint implementation efforts. Our study also shows that the use of UML modeling has a positive impact on software quality, i.e. it correlates with lower defect proneness. Further, we find out that visualisation of design concepts, such as class role-stereotypes, helps developers to perform better in software comprehension tasks.

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Section: Methodsmentioning

confidence: 99%

Section: Metadata Extraction and Queryingmentioning

confidence: 99%

Section: Extracting Meta-datamentioning

confidence: 99%

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An Automated Approach for Classifying Reverse-Engineered and Forward-Engineered UML Class Diagrams

Osman

Ho-Quang

Chaudron

2018

2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

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“…Step 1: Retrieval of mailing list data. We use MLStats (Mailing Lists Stats) [13] to retrieve mail messages from the development mailing lists. MLStats produces a structured MySQL database, from which we use the following tables:…”

Section: Data Retrievalmentioning

confidence: 99%

“…Step 2: Retrieval of Git information. We use CVSAnalY [13], a tool that retrieves and organizes data from source code management systems and stores it in a MySQL database. From it, we use the following tables:…”

Section: Data Retrievalmentioning

confidence: 99%

Using Metrics to Track Code Review Performance

Izquierdo-Cortázar¹,

Sekitoleko²,

González-Barahona

et al. 2017

Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering

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During 2015, some members of the Xen Project Advisory Board became worried about the performance of their code review process. The Xen Project is a free, open source software project developing one of the most popular virtualization platforms in the industry. They use a pre-commit peer review process similar to that in the Linux kernel, based on email messages. They had observed a large increase over time in the number of messages related to code review, and were worried about how this could be a signal of problems with their code review process. To address these concerns, we designed and conducted, with their continuous feedback, a detailed analysis focused on finding these problems, if any. During the study, we dealt with the methodological problems of Linux-like code review, and with the deeper issue of finding metrics that could uncover the problems they were worried about. For having a benchmark, we run the same analysis on a similar project, which uses very similar code review practices: the Linux Netdev (Netdev) project. As a result, we learned how in fact the Xen Project had some problems, but at the moment of the analysis those were already under control. We found as well how different the Xen and Netdev projects were behaving with respect to code review performance, despite being so similar from many points of view. In this paper we show the results of both analyses, and propose a comprehensive methodology, fully automated, to study Linux-style code review. We discuss also the problems of getting significant metrics to track improvements or detect problems in this kind of code review.

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Herding Cats: A Case Study of Release Management in an Open Collaboration Ecosystem

Poo-Caamaño

Singer

Knauss

et al. 2016

IFIP Advances in Information and Communication Technology

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Part 1: Full PapersInternational audienceRelease management in large-scale software development projects requires significant communication and coordination. It is particularly challenging in Free and Open Source Software (FOSS) ecosystems, in which hundreds of loosely connected developers and their projects need to be coordinated to release software to a schedule. To better understand this process and its challenges, we analyzed over two and half years of communication in the GNOME ecosystem and studied developers’ interactions. We cataloged communication channels, categorized high level communication and coordination activities in one of them, and triangulated our results by interviewing developers. We found that a release schedule, influence instead of direct control, and diversity are factors that impact positively the release process in the GNOME ecosystem. Our results can help organizations build better large-scale teams and show that research focused on individual projects might miss important parts of the picture

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Tools for the Study of the Usual Data Sources found in Libre Software Projects

Cited by 6 publications

References 0 publications

An Automated Approach for Classifying Reverse-Engineered and Forward-Engineered UML Class Diagrams

An Automated Approach for Classifying Reverse-Engineered and Forward-Engineered UML Class Diagrams

Using Metrics to Track Code Review Performance

Herding Cats: A Case Study of Release Management in an Open Collaboration Ecosystem

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