47,839 research outputs found

    Version Control in Online Software Repositories

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    Software version control repositories provide a uniform and stable interface to manage documents and their version histories. Unfortunately, Open Source systems, for example, CVS, Subversion, and GNU Arch are not well suited to highly collaborative environments and fail to track semantic changes in repositories. We introduce document provenance as our Description Logic framework to track the semantic changes in software repositories and draw interesting results about their historic behaviour using a rule-based inference engine. To support the use of this framework, we have developed our own online collaborative tool, leveraging the fluency of the modern WikiWikiWeb

    Version Control in Online Software Repositories

    No full text
    Software version control repositories provide a uniform and stable interface to manage documents and their version histories. Unfortunately, Open Source systems, for example, CVS, Subversion, and GNU Arch are not well suited to highly collaborative environments and fail to track semantic changes in repositories. We introduce document provenance as our Description Logic framework to track the semantic changes in software repositories and draw interesting results about their historic behaviour using a rule-based inference engine. To support the use of this framework, we have developed our own online collaborative tool, leveraging the fluency of the modern WikiWikiWeb

    JISC Final Report: IncReASe (Increasing Repository Content through Automation and Services)

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    The IncReASe (Increasing Repository Content through Automation and Services) was an eighteen month project (subsequently extended to twenty months) to enhance White Rose Research Online (WRRO)1. WRRO is a shared repository of research outputs (primarily publications) from the Universities of Leeds, Sheffield and York; it runs on the EPrints open source repository platform. The repository was created in 2004 and had steady growth but, in common with many other similar repositories, had difficulty in achieving a ā€œcritical massā€ of content and in becoming truly embedded within researchersā€™ workflows. The main aim of the IncReASe project was to assess ingestion routes into WRRO with a view to lowering barriers to deposit. We reviewed the feasibility of bulk import of pre-existing metadata and/or full-text research outputs, hoping this activity would have a positive knock-on effect on repository growth and embedding. Prior to the project, we had identified researchersā€™ reluctance to duplicate effort in metadata creation as a significant barrier to WRRO uptake; we investigated how WRRO might share data with internal and external IT systems. This work included a review of how WRRO, as an institutional based repository, might interact with the subject repository of the Economic and Social Research Council (ESRC). The project addressed four main areas: (i) researcher behaviour: we investigated researcher awareness, motivation and workflow through a survey of archiving activity on the university web sites, a questionnaire and discussions with researchers (ii) bulk import: we imported data from local systems, including Yorkā€™s submission data for the 2008 Research Assessment Exercise (RAE), and developed an import plug-in for use with the arXiv2 repository (iii) interoperability: we looked at how WRRO might interact with university and departmental publication databases and ESRCā€™s repository. (iv) metadata: we assessed metadata issues raised by importing publication data from a variety of sources. A number of outputs from the project have been made available from the IncReASe project web site http://eprints.whiterose.ac.uk/increase/. The project highlighted the low levels of researcher awareness of WRRO - and of broader open access issues, including research fundersā€™ deposit requirements. We designed some new publicity materials to start to address this. Departmental publication databases provided a useful jumping off point for advocacy and liaison; this activity was helpful in promoting awareness of WRRO. Bulk import proved time consuming ā€“ both in terms of adjusting EPrints plug-ins to incorporate different datasets and in the staff time required to improve publication metadata. A number of deposit scenarios were developed in the context of our work with ESRC; we concentrated on investigating how a local deposit of a research paper and attendant metadata in WRRO might be used to populate ESRCā€™s repository. This work improved our understanding of researcher workflows and of the SWORD protocol as a potential (if partial) solution to the single deposit, multiple destination model we wish to develop; we think the prospect of institutional repository / ESRC data sharing is now a step closer. IncReASe experienced some staff recruitment difficulties. It was also necessary to adapt the project to the changing IT landscape at the three partner institutions ā€“ in particular, the introduction of a centralised publication management system at the University of Leeds. Although these factors had some impact on deliverables, the aims and objectives of the project were largely achieved

    SZZ Unleashed: An Open Implementation of the SZZ Algorithm -- Featuring Example Usage in a Study of Just-in-Time Bug Prediction for the Jenkins Project

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    Numerous empirical software engineering studies rely on detailed information about bugs. While issue trackers often contain information about when bugs were fixed, details about when they were introduced to the system are often absent. As a remedy, researchers often rely on the SZZ algorithm as a heuristic approach to identify bug-introducing software changes. Unfortunately, as reported in a recent systematic literature review, few researchers have made their SZZ implementations publicly available. Consequently, there is a risk that research effort is wasted as new projects based on SZZ output need to initially reimplement the approach. Furthermore, there is a risk that newly developed (closed source) SZZ implementations have not been properly tested, thus conducting research based on their output might introduce threats to validity. We present SZZ Unleashed, an open implementation of the SZZ algorithm for git repositories. This paper describes our implementation along with a usage example for the Jenkins project, and conclude with an illustrative study on just-in-time bug prediction. We hope to continue evolving SZZ Unleashed on GitHub, and warmly invite the community to contribute

    Kultivating Kultur: increasing arts research deposit

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    This paper presents research undertaken as part of the JISC-funded Kultivate project and discusses how it is encouraging arts research deposit in UK institutional repositories. It presents an overview of the current arts research repository landscape in the UK at time of writing (September 2011). Through community engagement with the Kultur II Group and technical enhancements to EPrints, Kultivate is sharing and supporting the application of best practice in the development of institutional repositories that are appropriate to the specific needs and behaviours of creative and visual arts researchers. The Kultur II Group is open to all specialist creative arts institutions, departments within larger multidisciplinary institutions, and researchers in the UK; members include repository managers and administrators, researchers, librarians, technical staff, academics, and research office staff

    git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories

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    Data from software repositories have become an important foundation for the empirical study of software engineering processes. A recurring theme in the repository mining literature is the inference of developer networks capturing e.g. collaboration, coordination, or communication from the commit history of projects. Most of the studied networks are based on the co-authorship of software artefacts defined at the level of files, modules, or packages. While this approach has led to insights into the social aspects of software development, it neglects detailed information on code changes and code ownership, e.g. which exact lines of code have been authored by which developers, that is contained in the commit log of software projects. Addressing this issue, we introduce git2net, a scalable python software that facilitates the extraction of fine-grained co-editing networks in large git repositories. It uses text mining techniques to analyse the detailed history of textual modifications within files. This information allows us to construct directed, weighted, and time-stamped networks, where a link signifies that one developer has edited a block of source code originally written by another developer. Our tool is applied in case studies of an Open Source and a commercial software project. We argue that it opens up a massive new source of high-resolution data on human collaboration patterns.Comment: MSR 2019, 12 pages, 10 figure
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