Ten Simple Rules for Taking Advantage of Git and Github
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Gitmate Let's Write Good Code!
GitMate Let's Write Good Code! Artwork by Ankit, published under CC0. Vision Today's world is driven by software. We are able to solve increasingly complex problems with only a few lines of code. However, with increasing complexity, code quality becomes an issue that needs to be dealt with to ensure that the software works as intended. Code reviews have become a popular tool to keep the quality up and problems solvable. They make out at least 30% of the amount of time spent on the development of a software product. Static code analysis and code reviews are converging areas. Still, they are still treated seperately and thus their full synergetic potential remains unused. With GitMate, we want to reinvent the code review process. Our product will integrate static code analysis directly into the code review process to reduce the number of bugs while leaving more time for the development of your favorite features. Our product, the interactive code review bot "GitMate", is not only an easily usable static code analyser, but also actively supports the development process without any overhead for the developer. GitMate is as easy to use and interact with as a collegue next door and unique in its capabilities to even fix bugs by itself. It thereby reduces the amount of work of the reviewer, allowing him to focus on semantic problems that cannot be solved automatically. Product GitMate is a code review bot. It uses coala [1] to perform static code analysis on GitHub Pull Requests [2]. It searches committed changes for possible problems and drops comments right in the GitHub review user interface, effectively following the same workflow of a human reviewer. -
Mining DEV for Social and Technical Insights About Software Development
Mining DEV for social and technical insights about software development Maria Papoutsoglou∗y, Johannes Wachszx, Georgia M. Kapitsakiy ∗Aristotle University of Thessaloniki, Greece yUniversity of Cyprus, Cyprus zVienna University of Economics and Business, Austria xComplexity Science Hub Vienna, Austria [email protected]; [email protected]; [email protected] Abstract—Software developers are social creatures: they com- On more socially oriented platforms like Twitter, which limits municate, collaborate, and promote their work in a variety of post lengths to 280 characters, discussions about software mix channels. Twitter, GitHub, Stack Overflow, and other platforms with an endless variety of other content. offer developers opportunities to network and exchange ideas. Researchers analyze content on these sites to learn about trends To address this gap we present a novel source of long-form and topics in software engineering. However, insight mined text data created by people working in software called DEV from the text of Stack Overflow questions or GitHub issues (https://dev.to). DEV is “a community of software developers is highly focused on detailed and technical aspects of software getting together to help one another out,” focused especially development. In this paper, we present a relatively new online on facilitating cooperation and learning. Content on DEV community for software developers called DEV. On DEV users write long-form posts about their experiences, preferences, and resembles blog and Medium posts and, at a glance, covers working life in software, zooming out from specific issues and files everything from programming language choice to technical to reflect on broader topics. -
Open Source in the Enterprise
Open Source in the Enterprise Andy Oram and Zaheda Bhorat Beijing Boston Farnham Sebastopol Tokyo Open Source in the Enterprise by Andy Oram and Zaheda Bhorat Copyright © 2018 O’Reilly Media. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online edi‐ tions are also available for most titles (http://oreilly.com/safari). For more information, contact our corporate/institutional sales department: 800-998-9938 or [email protected]. Editor: Michele Cronin Interior Designer: David Futato Production Editor: Kristen Brown Cover Designer: Karen Montgomery Copyeditor: Octal Publishing Services, Inc. July 2018: First Edition Revision History for the First Edition 2018-06-18: First Release The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Open Source in the Enterprise, the cover image, and related trade dress are trademarks of O’Reilly Media, Inc. The views expressed in this work are those of the authors, and do not represent the publisher’s views. While the publisher and the authors have used good faith efforts to ensure that the informa‐ tion and instructions contained in this work are accurate, the publisher and the authors disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. Use of the information and instructions contained in this work is at your own risk. If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights. -
CI/CD Pipelines Evolution and Restructuring: a Qualitative and Quantitative Study
CI/CD Pipelines Evolution and Restructuring: A Qualitative and Quantitative Study Fiorella Zampetti,Salvatore Geremia Gabriele Bavota Massimiliano Di Penta University of Sannio, Italy Università della Svizzera Italiana, University of Sannio, Italy {name.surname}@unisannio.it Switzerland [email protected] [email protected] Abstract—Continuous Integration and Delivery (CI/CD) • some parts of the pipelines become unnecessary and can pipelines entail the build process automation on dedicated ma- be removed, or some others (e.g., testing environments) chines, and have been demonstrated to produce several advan- become obsolete and should be upgraded/replaced; tages including early defect discovery, increased productivity, and faster release cycles. The effectiveness of CI/CD may depend on • performance bottlenecks need to be resolved, e.g., by the extent to which such pipelines are properly maintained to parallelizing or restructuring some pipeline jobs; or cope with the system and its underlying technology evolution, • in general, the pipeline needs to be adapted to cope with as well as to limit bad practices. This paper reports the results the evolution of the underlying software and systems, of a study combining a qualitative and quantitative evaluation including technological changes (e.g., changes of archi- on CI/CD pipeline restructuring actions. First, by manually analyzing and coding 615 pipeline configuration change commits, tectures, operating systems, or library upgrades). we have crafted a taxonomy of 34 CI/CD pipeline restructuring We report the results of an empirical qualitative and quanti- actions, either improving extra-functional properties or changing tative study investigating how CI/CD pipelines of open source the pipeline’s behavior. -
The Open Source Way 2.0
THE OPEN SOURCE WAY 2.0 Contributors Version 2.0, 2020-12-16: This release contains opinions Table of Contents Presenting the Open Source Way . 2 The Shape of Things (I.e., Assumptions We Are Making) . 2 Structure of This Guide. 4 A Community of Practice Always Rebuilding Itself . 5 Getting Started. 6 Community 101: Understanding, Joining, or Forming a New Community . 6 New Project Checklist . 14 Creating an Open Source Product Strategy . 16 Attracting Users . 19 Communication Norms in Open Source Software Projects . 20 To Build Diverse Open Source Communities, Make Them Inclusive First . 36 Guiding Participants . 48 Why Do People Participate in Open Source Communities?. 48 Growing Contributors . 52 From Users to Contributors. 52 What Is a Contribution? . 58 Essentials of Building a Community . 59 Onboarding . 66 Creating a Culture of Mentorship . 71 Project and Community Governance . 78 Community Roles . 97 Community Manager Self-Care . 103 Measuring Success . 122 Defining Healthy Communities . 123 Understanding Community Metrics . 136 Announcing Software Releases . 144 Contributors . 148 Chapters writers. 148 Project teams. 149 This guidebook is available in HTML single page and PDF. Bugs (mistakes, comments, etc.) with this release may be filed as an issue in our repo on GitHub. You are also welcome to bring it as a discussion to our forum/mailing list. 1 Presenting the Open Source Way An English idiom says, "There is a method to my madness."[1] Most of the time, the things we do make absolutely no sense to outside observers. Out of context, they look like sheer madness. But for those inside that messiness—inside that whirlwind of activity—there’s a certain regularity, a certain predictability, and a certain motive. -
A First Look at Developers' Live Chat on Gitter
A First Look at Developers’ Live Chat on Gitter Lin Shi Xiao Chen Ye Yang [email protected] [email protected] [email protected] Institute of Software Chinese Institute of Software Chinese School of Systems and Enterprises, Academy of Sciences, University of Academy of Sciences, University of Stevens Institute of Technology Chinese Academy of Sciences, China Chinese Academy of Sciences, China Hoboken, NJ, USA Hanzhi Jiang Nan Niu Qing Wang∗ Ziyou Jiang [email protected] [email protected] {hanzhi2021,ziyou2019}@iscas.ac.cn Department of EECS, University of State Key Laboratory of Computer Institute of Software Chinese Cincinnati, Cincinnati, OH Science, Institute of Software Chinese Academy of Sciences, University of USA Academy of Sciences, University of Chinese Academy of Sciences, China Chinese Academy of Sciences, China ABSTRACT KEYWORDS Modern communication platforms such as Gitter and Slack play an Live chat, Team communication, Open source, Empirical Study increasingly critical role in supporting software teamwork, espe- ACM Reference Format: cially in open source development. Conversations on such platforms Lin Shi, Xiao Chen, Ye Yang, Hanzhi Jiang, Ziyou Jiang, Nan Niu, and Qing often contain intensive, valuable information that may be used for Wang. 2021. A First Look at Developers’ Live Chat on Gitter. In Proceed- better understanding OSS developer communication and collabora- ings of the 29th ACM Joint European Software Engineering Conference and tion. However, little work has been done in this regard. To bridge Symposium on the Foundations of Software Engineering (ESEC/FSE ’21), Au- the gap, this paper reports a first comprehensive empirical study gust 23–28, 2021, Athens, Greece. -
How Are Issue Reports Discussed in Gitter Chat Rooms?
How are issue reports discussed in Gitter chat rooms? Hareem Sahar1, Abram Hindle1, Cor-Paul Bezemer2 University of Alberta Edmonton, Canada Abstract Informal communication channels like mailing lists, IRC and instant messaging play a vital role in open source software development by facilitating communica- tion within geographically diverse project teams e.g., to discuss issue reports to facilitate the bug-fixing process. More recently, chat systems like Slack and Git- ter have gained a lot of popularity and developers are rapidly adopting them. Gitter is a chat system that is specifically designed to address the needs of GitHub users. Gitter hosts project-based asynchronous chats which foster fre- quent project discussions among participants. Developer discussions contain a wealth of information such as the rationale behind decisions made during the evolution of a project. In this study, we explore 24 open source project chat rooms that are hosted on Gitter, containing a total of 3,133,106 messages and 14,096 issue references. We manually analyze the contents of chat room discus- sions around 457 issue reports. The results of our study show the prevalence of issue discussions on Gitter, and that the discussed issue reports have a longer resolution time than the issue reports that are never brought on Gitter. Keywords: developer discussions, Gitter, issue reports Email address: [email protected] (Hareem Sahar ) 1Department of Computing Science, University of Alberta, Canada 2Analytics of Software, Games and Repository Data (ASGAARD) lab, University of Al- berta, Canada Preprint submitted to Journal of Systems and Software October 29, 2020 1. Introduction Open source software (OSS) development uses the expertise of developers from all over the world, who communicate with each other via email, mailing lists [1], IRC channels [2], and modern communication platforms like Gitter 5 and Slack [3]. -
Introduction to Label-Free Quantification
SeqAn and OpenMS Integration Workshop Temesgen Dadi, Julianus Pfeuffer, Alexander Fillbrunn The Center for Integrative Bioinformatics (CIBI) Mass-spectrometry data analysis in KNIME Julianus Pfeuffer, Alexander Fillbrunn OpenMS • OpenMS – an open-source C++ framework for computational mass spectrometry • Jointly developed at ETH Zürich, FU Berlin, University of Tübingen • Open source: BSD 3-clause license • Portable: available on Windows, OSX, Linux • Vendor-independent: supports all standard formats and vendor-formats through proteowizard • OpenMS TOPP tools – The OpenMS Proteomics Pipeline tools – Building blocks: One application for each analysis step – All applications share identical user interfaces – Uses PSI standard formats • Can be integrated in various workflow systems – Galaxy – WS-PGRADE/gUSE – KNIME Kohlbacher et al., Bioinformatics (2007), 23:e191 OpenMS Tools in KNIME • Wrapping of OpenMS tools in KNIME via GenericKNIMENodes (GKN) • Every tool writes its CommonToolDescription (CTD) via its command line parser • GKN generates Java source code for nodes to show up in KNIME • Wraps C++ executables and provides file handling nodes Installation of the OpenMS plugin • Community-contributions update site (stable & trunk) – Bioinformatics & NGS • provides > 180 OpenMS TOPP tools as Community nodes – SILAC, iTRAQ, TMT, label-free, SWATH, SIP, … – Search engines: OMSSA, MASCOT, X!TANDEM, MSGFplus, … – Protein inference: FIDO Data Flow in Shotgun Proteomics Sample HPLC/MS Raw Data 100 GB Sig. Proc. Peak 50 MB Maps Data Reduction 1 -
Openms – a Framework for Computational Mass Spectrometry
OpenMS { A framework for computational mass spectrometry Dissertation der Fakult¨atf¨urInformations- und Kognitionswissenschaften der Eberhard-Karls-Universit¨atT¨ubingen zur Erlangung des Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.) vorgelegt von Dipl.-Inform. Marc Sturm aus Saarbr¨ucken T¨ubingen 2010 Tag der m¨undlichen Qualifikation: 07.07.2010 Dekan: Prof. Dr. Oliver Kohlbacher 1. Berichterstatter: Prof. Dr. Oliver Kohlbacher 2. Berichterstatter: Prof. Dr. Knut Reinert Acknowledgments I am tremendously thankful to Oliver Kohlbacher, who aroused my interest in the field of computational proteomics and gave me the opportunity to write this thesis. Our discussions where always fruitful|no matter if scientific or technical. Furthermore, he provided an enjoyable working environment for me and all the other staff of the working group. OpenMS would not have been possible without the joint effort of many people. My thanks go to all core developers and students who contributed to OpenMS and suffered from the pedantic testing rules. I especially thank Eva Lange, Andreas Bertsch, Chris Bielow and Clemens Gr¨oplfor the tight cooperation and nice evenings together. Of course, I'm especially grateful to my parents and family for their support through- out my whole life. Finally, I thank Bettina for her patience and understanding while I wrote this thesis. iii Abstract Mass spectrometry coupled to liquid chromatography (LC-MS) is an analytical technique becoming increasingly popular in biomedical research. Especially in high-throughput proteomics and metabolomics mass spectrometry is widely used because it provides both qualitative and quantitative information about analytes. The standard protocol is that complex analyte mixtures are first separated in liquid chromatography and then analyzed using mass spectrometry. -
Einstein Toolkit Web Infrastructure Overview Steve Brandt (LSU), Roland Haas (NCSA) Other Sources of Information
Einstein Toolkit Web infrastructure overview Steve Brandt (LSU), Roland Haas (NCSA) Other sources of information ● the ET wiki at https://docs.einsteintoolkit.org/et-docs/Services is the authoritative source of information on ET web infrastructure ● current ET repos eg https://bitbucket.org/einsteintoolkit/einsteinbase/admin ● README files in bitbucket / github / etc repos ● minutes of the calls https://docs.einsteintoolkit.org/et-docs/Phone_Call_Minutes ● the mailing list [email protected] searchable on ET website: https://www.einsteintoolkit.org/support.html ● the mailing list [email protected] to which the maintainers are subscribed (its archive is private). This lists accepts posts from anyone. Components of ET web infrastructure The Einstein Toolkit, being a community project involving members that are at geographically distant institutions in different time zones, relies on a collection of web services to distribute information and code. ● the main website: https://www.einsteintoolkit.org hosted at LSU ● the mailing list(s) [email protected] hosted at LSU ● the wiki https://docs.einsteintoolkit.org hosted at LSU ● the issue tracker https://trac.einsteintoolkit.org hosted at LSU ● the tutorial server https://etkhub.ndslabs.org hosted at NCSA ● git code repositories hosted on bitbucket https://bitbucket.org/einsteintoolkit ● svn code repositories https://svn.einsteintoolkit.org hosted at LSU ● the Jenkins instance https://build.barrywardell.net/ hosted at NCSA ● the gitter chat https://gitter.im/EinsteinToolkit ● the github orignization https://github.com/einsteintoolkit used with gitter Jenkins continuous integration system ● Jenkins builds the Einstein Toolkit and runs Four VMs working in concert the testsuites whenever a commit to the "master" branches is detected. -
Software-Related Slack Chats with Disentangled Conversations
Software-related Slack Chats with Disentangled Conversations Preetha Chatterjee∗, Kostadin Damevskiy, Nicholas A. Kraftz, Lori Pollock∗ ∗ University of Delaware, Newark, DE, USA; {preethac, pollock}@udel.edu y Virginia Commonwealth University, Richmond, VA, USA; [email protected] z Uservoice, Raleigh, NC, USA; [email protected] ABSTRACT to ask and answer a variety of questions. Our preliminary stud- More than ever, developers are participating in public chat com- ies show that such chat communications on Slack contain valu- munities to ask and answer software development questions. With able information, such as descriptions of code snippets and spe- over ten million daily active users, Slack is one of the most popular cific APIs, good programming practices, and causes of common chat platforms, hosting many active channels focused on software errors/exceptions [9, 11]. Availability of these types of information development technologies, e.g., python, react. Prior studies have in software-related chats suggests that mining chats could provide shown that public Slack chat transcripts contain valuable informa- similar support for improving software maintenance tools as what tion, which could provide support for improving automatic soft- researchers have already leveraged from emails and bug reports [7], ware maintenance tools or help researchers understand developer tutorials [25], and Q&A forums [4, 10, 26, 28]. struggles or concerns. Different from many other sources of software development- In this paper, we present a dataset of software-related Q&A related communication, the information on chat forums is shared chat conversations, curated for two years from three open Slack in an unstructured, informal, and asynchronous manner. There is communities (python, clojure, elm). -
June 5, 2017 Bioinformatics MS Interest Group Your Hosts
Open Source Software Packages: Using and Making your conbributions June 5, 2017 Bioinformatics MS Interest Group Your hosts Meena Choi Samuel Payne Post doc. Scientist Northeastern University Pacific Northwest National Lab Statistical methods for Integrative Omics quantitative proteomics Outline • General Intro – Meena Choi • mzRefinery/proteowizard - Sam Payne • openMS - Oliver Kohlbacher • Skyline - Brendan MacLean • General discussion on open source • Ask questions for the General Discussion http://bit.ly/2qNZVBU • Shout-out for Open Source tool http://bit.ly/2qVHVo7 Oliver Kohlbacher • The chair of Applied Bioinformatics at University of Tübingen & fellow at the Max Plank Institute • OpenMS ( openms.de ) Brendan MacLean • Principal developer for Skyline ( skyline.ms ) • University of Washington Ask questions or comments : http://bit.ly/2qNZVBU • Why have open source? • What are the advantages and disadvantages between open source and private closed-source software? • How should a developer consider the question of making a project open source or not? • What is appropriate level of guide/documentation to help new developers? • How to incentivize people to contribute to open source software? Bioconductor.org biocViews search R package development • Provide the framework for developing package : basic structure, requirements… • Requirements : 1. pass check or BiocCheck on all supported platforms (their own checking system) 2. Documents • DESCRIPTION, NAMESPACE, vignette, help file, NEWS 3. Review process (2-5 weeks) • submit a GitHub repository • a reviewer will be assigned and a detailed package review is returned. • the process is repeated until the package is accepted to Bioconductor. • Maintaining the packages across release cycles (twice a year) + deprecate packages • Import or depend on other packages in Bioconductor or CRAN R package as software • Easy to make open source software for new method development.