Version Control Systems
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Version Control 101 Exported from Please Visit the Link for the Latest Version and the Best Typesetting
Version Control 101 Exported from http://cepsltb4.curent.utk.edu/wiki/efficiency/vcs, please visit the link for the latest version and the best typesetting. Version Control 101 is created in the hope to minimize the regret from lost files or untracked changes. There are two things I regret. I should have learned Python instead of MATLAB, and I should have learned version control earlier. Version control is like a time machine. It allows you to go back in time and find out history files. You might have heard of GitHub and Git and probably how steep the learning curve is. Version control is not just Git. Dropbox can do version control as well, for a limited time. This tutorial will get you started with some version control concepts from Dropbox to Git for your needs. More importantly, some general rules are suggested to minimize the chance of file losses. Contents Version Control 101 .............................................................................................................................. 1 General Rules ................................................................................................................................... 2 Version Control for Files ................................................................................................................... 2 DropBox or Google Drive ............................................................................................................. 2 Version Control on Confluence ................................................................................................... -
Jenkins Declarative Pipeline Checkout Scm Example
Jenkins Declarative Pipeline Checkout Scm Example Thor confab improbably. Permissible Augie usually damnify some corolla or name-drops unalike. Nicholas remains scenic: she depressurize her chessels doctors too straight? How they evaluate Git branch name itself a Jenkins pipeline using. 'checkout scm' is a great single line to add maybe your script that checks out the commute the Jenkinsfile is crisp from. Confirmed that were very similar to us to other useful by jenkins declarative pipeline checkout scm example, and seeing that. Jenkins Pipeline Checkout Scm Example abound on Jenkins comjavahometechmywebblobmasterJenkins-Declarative-GitFor OnlineClassroom trainings and. BRANCHNAME JENKINS-4565 Declarative Pipeline Example. Jenkins Stash Example. I've key a jenkins pipeline and bow is pulling the pipeline script from scm. If necessary files in the example pipeline code. Feature Request Parallel Stage name for Declarative. Pipeline Pipeline stage Pipeline Declarative Checkout SCM Pipeline checkout. Jenkins Beginner Tutorial 14 How to setup DELIVERY PIPELINE in Jenkins Step by. In turkey first step 1 we checkout project from GitHub and then build it with Maven 2. How to Use the Jenkins Scripted Pipeline BlazeMeter. In simple words Jenkins Pipeline is a combination of plugins that block the integration and implementation of continuous delivery pipelines using Jenkins A pipeline has an extensible automation server for creating simple less complex delivery pipelines as code via pipeline DSL Domain-specific Language. The Declarative Pipeline example above contains the minimum necessary. That is why science would awake to steam a border more with Jenkins Pipelines to present. How do I of environment variables in Jenkins pipeline? Nodelabel def myRepo checkout scm def gitCommit myRepo. -
Generating Commit Messages from Git Diffs
Generating Commit Messages from Git Diffs Sven van Hal Mathieu Post Kasper Wendel Delft University of Technology Delft University of Technology Delft University of Technology [email protected] [email protected] [email protected] ABSTRACT be exploited by machine learning. The hypothesis is that methods Commit messages aid developers in their understanding of a con- based on machine learning, given enough training data, are able tinuously evolving codebase. However, developers not always doc- to extract more contextual information and latent factors about ument code changes properly. Automatically generating commit the why of a change. Furthermore, Allamanis et al. [1] state that messages would relieve this burden on developers. source code is “a form of human communication [and] has similar Recently, a number of different works have demonstrated the statistical properties to natural language corpora”. Following the feasibility of using methods from neural machine translation to success of (deep) machine learning in the field of natural language generate commit messages. This work aims to reproduce a promi- processing, neural networks seem promising for automated commit nent research paper in this field, as well as attempt to improve upon message generation as well. their results by proposing a novel preprocessing technique. Jiang et al. [12] have demonstrated that generating commit mes- A reproduction of the reference neural machine translation sages with neural networks is feasible. This work aims to reproduce model was able to achieve slightly better results on the same dataset. the results from [12] on the same and a different dataset. Addition- When applying more rigorous preprocessing, however, the per- ally, efforts are made to improve upon these results by applying a formance dropped significantly. -
Ethereal Developer's Guide Draft 0.0.2 (15684) for Ethereal 0.10.11
Ethereal Developer's Guide Draft 0.0.2 (15684) for Ethereal 0.10.11 Ulf Lamping, Ethereal Developer's Guide: Draft 0.0.2 (15684) for Ethere- al 0.10.11 by Ulf Lamping Copyright © 2004-2005 Ulf Lamping Permission is granted to copy, distribute and/or modify this document under the terms of the GNU General Public License, Version 2 or any later version published by the Free Software Foundation. All logos and trademarks in this document are property of their respective owner. Table of Contents Preface .............................................................................................................................. vii 1. Foreword ............................................................................................................... vii 2. Who should read this document? ............................................................................... viii 3. Acknowledgements ................................................................................................... ix 4. About this document .................................................................................................. x 5. Where to get the latest copy of this document? ............................................................... xi 6. Providing feedback about this document ...................................................................... xii I. Ethereal Build Environment ................................................................................................14 1. Introduction .............................................................................................................15 -
Efficient Algorithms for Comparing, Storing, and Sharing
EFFICIENT ALGORITHMS FOR COMPARING, STORING, AND SHARING LARGE COLLECTIONS OF EVOLUTIONARY TREES A Dissertation by SUZANNE JUDE MATTHEWS Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY May 2012 Major Subject: Computer Science EFFICIENT ALGORITHMS FOR COMPARING, STORING, AND SHARING LARGE COLLECTIONS OF EVOLUTIONARY TREES A Dissertation by SUZANNE JUDE MATTHEWS Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Approved by: Chair of Committee, Tiffani L. Williams Committee Members, Nancy M. Amato Jennifer L. Welch James B. Woolley Head of Department, Hank W. Walker May 2012 Major Subject: Computer Science iii ABSTRACT Efficient Algorithms for Comparing, Storing, and Sharing Large Collections of Evolutionary Trees. (May 2012) Suzanne Jude Matthews, B.S.; M.S., Rensselaer Polytechnic Institute Chair of Advisory Committee: Dr. Tiffani L. Williams Evolutionary relationships between a group of organisms are commonly summarized in a phylogenetic (or evolutionary) tree. The goal of phylogenetic inference is to infer the best tree structure that represents the relationships between a group of organisms, given a set of observations (e.g. molecular sequences). However, popular heuristics for inferring phylogenies output tens to hundreds of thousands of equally weighted candidate trees. Biologists summarize these trees into a single structure called the consensus tree. The central assumption is that the information discarded has less value than the information retained. But, what if this assumption is not true? In this dissertation, we demonstrate the value of retaining and studying tree collections. -
Distributed Configuration Management: Mercurial CSCI 5828 Spring 2012 Mark Grebe Configuration Management
Distributed Configuration Management: Mercurial CSCI 5828 Spring 2012 Mark Grebe Configuration Management Configuration Management (CM) systems are used to store code and other artifacts in Software Engineering projects. Since the early 70’s, there has been a progression of CM systems used for Software CM, starting with SCCS, and continuing through RCS, CVS, and Subversion. All of these systems used a single, centralized repository structure. Distributed Configuration Management As opposed to traditional CM systems, Distributed Configuration Management Systems are ones where there does not have to be a central repository. Each developer has a copy of the entire repository and history. A central repository may be optionally used, but it is equal to all of the other developer repositories. Advantages of Distributed Configuration Management Distributed tools are faster than centralized ones since metadata is stored locally. Can use tool to manage changes locally while not connected to the network where server resides. Scales more easily, since all of the load is not on a central server. Allows private work that is controlled, but not released to the larger community. Distributed systems are normally designed to make merges easy, since they are done more often. Mercurial Introduction Mercurial is a cross-platform, distributed configuration management application. In runs on most modern OS platforms, including Windows, Linux, Solaris, FreeBSD, and Mac OSX. Mercurial is written 95% in Python, with the remainder written in C for speed. Mercurial is available as a command line tool on all of the platforms, and with GUI support programs on many of the platforms. Mercurial is customizable with extensions, hooks, and output templates. -
Steve Burnett Education Employment
Steve Burnett Raleigh NC [email protected] More details and attached recommendations at http://www.linkedin.com/in/steveburnett Education 1992 M.S. Technical Communication, North Carolina State University 1992 Emergency Medical Technician, Wake Technical Community College 1989 B.A. History, B.A. Economics, NCSU Employment Information Developer III, Hewlett-Packard (formerly Opsware) (November 2007 – present) (HP acquired Opsware effective November 2007.) Creating install, user, and administrator guides for HP SAR (Service Automation Reporter, formerly Opsware OMDB) and HP Live Network (formerly TON) on Linux, Solaris, VMware, and Windows platforms. Sole documentation support for OMDB (1.0, had contributing author for the 1.0.2 release), SAR (7.0, 7.50), and HP Live Network (1.0 to 1.30). Provided Web QA for the HP Live Network Portal. Tools: FrameMaker 7, WebWorks, ClearCase, subversion, RapidSVN, Eclipse, Bugzilla, HP Quality Center, Collabnet, BIRT Report Designer, WebEx, MS SharePoint. Senior Technical Writer, Opsware (January – November 2007) Created install, user, and administrator guides for Opsware OMDB (Operational Management Database) and TON (The Opsware Network) on Linux, Solaris, and Windows platforms. Worked with Technical Support on CMS selection. Tools: FrameMaker 7, WebWorks, ClearCase, subversion, Bugzilla, Quality Center, Collabnet, BIRT Report Designer, WebEx. Technical Writer, SAS Institute (contract, Apex Systems) (November 2005 – January 2007) SAS Technical Support: Internal and external documentation. Tools: SAS, SIRIUS, SOS. SAS R&D: Internal and external documentation. Tools: SAS, WebLogic, Xythos, SQL. Systems Administrator, SAS Institute (contract, Apex Systems) (March – September 2005) SAS Solutions: Provided Linux, Windows, Solaris, and HP-UX server system administration, technical support, and internal training for an ASP (application service provider) team. -
Codice Plastic
Francisco Monteverde “The Cadillac of the SCMs” - eWeek CEO Codice Software www.plasticscm.com [email protected] @plasticscm @plasticscm www.plasticscm.com © 2014 Codice Software Computers, Mobile Phones, Tablets, Internet Services, Video Games, Consoles, Financial Services, Telecommunications, Automobiles, Transportation, Healthcare, Commerce, Distribution, Industrial Manufacturing… … TODAY SOFTWARE IS ALMOST EVERYWHERE….AND INCREASING © 2014 Codice Software VERSION CONTROL IS AN ESSENTIAL FUNCTION WITHIN SOFTWARE DEVELOPMENT © 2014 Codice Software The Problem with Software Development: Limited Productivity, Low Quality Code 1. Development in serial mode (not parallel) creates many dependencies and continuous broken builds 2. Developers need to be connected to central server to use the Version Control tool Distributed Version Control Systems (DVCS) © 2014 Codice Software Introducing Plastic SCM Branching and Merging is GOOD! The Only Commercial Enterprise Distributed Version Control Systems (DVCS) for Teams of Any Size, Enabling Parallel and Distributed Development that works Integrated with Polarion ALM: Closing the GAP between Requirements & Code © 2014 Codice Software Polarion ALM & Plastic SCM Working Together • Plastic SCM integrates with Polarion using “branch per task” and “task per cset” • Branches can be created listing the assigned and open tasks • Alternatively, individual changesets can be linked to Polarion tasks • Quick access from Plastic SCM GUI to Polarion info © 2014 Codice Software Codice Software Company Background Some Global Customers: Funded 2005 Products Plastic SCM & Semantic Merge Investors Bullnet Capital (VC): Valladolid (Spain) & Silicon Valley HQ’s Office Distribution US/Canda, EU, Israel, South Korea © 2014 Codice Software Codice Software in US Developer’s Press Jeff Cogswell Adrian Bridgwater Eric Caoili Heavy Refactoring In Parallel? Plastic SCM 4.0 solution for Plastic SCM is the Cadillac No Problem. -
Altova Umodel 2012 User & Reference Manual
User and Reference Manual Altova UModel 2012 User & Reference Manual All rights reserved. No parts of this work may be reproduced in any form or by any means - graphic, electronic, or mechanical, including photocopying, recording, taping, or information storage and retrieval systems - without the written permission of the publisher. Products that are referred to in this document may be either trademarks and/or registered trademarks of the respective owners. The publisher and the author make no claim to these trademarks. While every precaution has been taken in the preparation of this document, the publisher and the author assume no responsibility for errors or omissions, or for damages resulting from the use of information contained in this document or from the use of programs and source code that may accompany it. In no event shall the publisher and the author be liable for any loss of profit or any other commercial damage caused or alleged to have been caused directly or indirectly by this document. Published: 2012 © 2012 Altova GmbH UML®, OMG™, Object Management Group™, and Unified Modeling Language™ are either registered trademarks or trademarks of Object Management Group, Inc. in the United States and/or other countries. Table of Contents 1 UModel 3 2 Introducing UModel 6 3 What's new in UModel 8 4 UModel tutorial 14 4.1 Starting UModel................................................................................................................. 16 4.2 Use cases ................................................................................................................ -
Higher Inductive Types (Hits) Are a New Type Former!
Git as a HIT Dan Licata Wesleyan University 1 1 Darcs Git as a HIT Dan Licata Wesleyan University 1 1 HITs 2 Generator for 2 equality of equality HITs Homotopy Type Theory is an extension of Agda/Coq based on connections with homotopy theory [Hofmann&Streicher,Awodey&Warren,Voevodsky,Lumsdaine,Garner&van den Berg] 2 Generator for 2 equality of equality HITs Homotopy Type Theory is an extension of Agda/Coq based on connections with homotopy theory [Hofmann&Streicher,Awodey&Warren,Voevodsky,Lumsdaine,Garner&van den Berg] Higher inductive types (HITs) are a new type former! 2 Generator for 2 equality of equality HITs Homotopy Type Theory is an extension of Agda/Coq based on connections with homotopy theory [Hofmann&Streicher,Awodey&Warren,Voevodsky,Lumsdaine,Garner&van den Berg] Higher inductive types (HITs) are a new type former! They were originally invented[Lumsdaine,Shulman,…] to model basic spaces (circle, spheres, the torus, …) and constructions in homotopy theory 2 Generator for 2 equality of equality HITs Homotopy Type Theory is an extension of Agda/Coq based on connections with homotopy theory [Hofmann&Streicher,Awodey&Warren,Voevodsky,Lumsdaine,Garner&van den Berg] Higher inductive types (HITs) are a new type former! They were originally invented[Lumsdaine,Shulman,…] to model basic spaces (circle, spheres, the torus, …) and constructions in homotopy theory But they have many other applications, including some programming ones! 2 Generator for 2 equality of equality Patches Patch a a 2c2 diff b d = < b c c --- > d 3 3 id a a b b -
Analysis of Devops Tools to Predict an Optimized Pipeline by Adding Weightage for Parameters
International Journal of Computer Applications (0975 – 8887) Volume 181 – No. 33, December 2018 Analysis of DevOps Tools to Predict an Optimized Pipeline by Adding Weightage for Parameters R. Vaasanthi V. Prasanna Kumari, PhD S. Philip Kingston Research Scholar, HOD, MCA Project Manager SCSVMV University Rajalakshmi Engineering Infosys, Mahindra City, Kanchipuram College, Chennai Chennai ABSTRACT cloud. Now-a-days more than ever, DevOps [Development + Operations] has gained a tremendous amount of attention in 2. SCM software industry. Selecting the tools for building the DevOps Source code management (SCM) is a software tool used for pipeline is not a trivial exercise as there are plethora’s of tools development, versioning and enables team working in available in market. It requires thought, planning, and multiple locations to work together more effectively. This preferably enough time to investigate and consult other plays a vital role in increasing team’s productivity. Some of people. Unfortunately, there isn’t enough time in the day to the SCM tools, considered for this study are GIT, SVN, CVS, dig for top-rated DevOps tools and its compatibility with ClearCase, Mercurial, TFS, Monotone, Bitkeeper, Code co- other tools. Each tool has its own pros/cons and compatibility op, Darcs, Endevor, Fossil, Perforce, Rational Synergy, of integrating with other tools. The objective of this paper is Source Safe, and GNU Bazaar. Table1 consists of SCM tools to propose an approach by adding weightage to each with weightage. parameter for the curated list of the DevOps tools. 3. BUILD Keywords Build is a process that enables source code to be automatically DevOps, SCM, dependencies, compatibility and pipeline compiled into binaries including code level unit testing to ensure individual pieces of code behave as expected [4]. -
Version Control – Agile Workflow with Git/Github
Version Control – Agile Workflow with Git/GitHub 19/20 November 2019 | Guido Trensch (JSC, SimLab Neuroscience) Content Motivation Version Control Systems (VCS) Understanding Git GitHub (Agile Workflow) References Forschungszentrum Jülich, JSC:SimLab Neuroscience 2 Content Motivation Version Control Systems (VCS) Understanding Git GitHub (Agile Workflow) References Forschungszentrum Jülich, JSC:SimLab Neuroscience 3 Motivation • Version control is one aspect of configuration management (CM). The main CM processes are concerned with: • System building • Preparing software for releases and keeping track of system versions. • Change management • Keeping track of requests for changes, working out the costs and impact. • Release management • Preparing software for releases and keeping track of system versions. • Version control • Keep track of different versions of software components and allow independent development. [Ian Sommerville,“Software Engineering”] Forschungszentrum Jülich, JSC:SimLab Neuroscience 4 Motivation • Keep track of different versions of software components • Identify, store, organize and control revisions and access to it • Essential for the organization of multi-developer projects is independent development • Ensure that changes made by different developers do not interfere with each other • Provide strategies to solve conflicts CONFLICT Alice Bob Forschungszentrum Jülich, JSC:SimLab Neuroscience 5 Content Motivation Version Control Systems (VCS) Understanding Git GitHub (Agile Workflow) References Forschungszentrum Jülich,