This is a lunchtime talk I gave to the Southampton astronomy department. The aim was to make them aware of version control systems and when they might need to use them.
This document provides an introduction to version control. It discusses what version control is, the history and evolution of version control systems, different types of version control systems classified by their repository model and concurrency model, and practical considerations for starting to use version control. Key topics covered include centralized and distributed version control, lock-modify-unlock and merge models, and domain vocabulary for common version control tasks and workflows.
This document provides an introduction to Git and GitHub. It begins with an overview of source control and the history of version control systems like SVN and CVS. It then discusses key concepts of Git like its three-tree architecture, branches and merging, and undoing changes. The document concludes with an introduction to GitHub, how to clone and collaborate on repositories, and some tips on reducing merge conflicts.
This document provides an introduction to using GitHub, including:
- How to set up a GitHub account and add the Student Developer Pack for unlimited private repositories.
- Basic terminology like repositories, commits, pushes, pulls, branches, and pull requests.
- Tutorials for managing GitHub repositories through the web interface and command line, covering tasks like cloning repositories, adding/committing/pushing files, and adding collaborators.
This document provides an overview of Git and its basic commands for beginners. It covers installing Git, creating repositories on Bitbucket and GitHub, tracking changes with commands like add, commit, push, pull, and resolving merge conflicts. It also discusses branching, tagging, reverting changes, and ignoring files. Key concepts explained include distributed version control, staging changes, commit histories, and setting up aliases and submodules.
This document provides an introduction to the version control system Git. It defines key Git concepts like the working tree, repository, commit, and HEAD. It explains that Git is a distributed version control system where the full history of a project is available once cloned. The document outlines Git's history, with it being created by Linus Torvalds to replace the commercial BitKeeper tool. It then lists and briefly describes important Git commands for local and collaboration repositories, including config, add, commit, log, diff, status, branch, checkout, merge, remote, clone, push, and pull. Lastly, it covers installing Git and generating SSH keys on Windows for accessing Git repositories.
Git is a distributed version control system that allows developers to work collaboratively on projects. It works by creating snapshots of files in a project over time. Developers can commit changes locally and then push them to a remote repository to share with others. Key Git concepts include repositories, commits, branches, cloning repositories from remote locations, and commands like push, pull, commit, log and diff to manage changes.
This document provides an overview of Git and how to use it. It discusses version control systems and how distributed version control systems like Git work. It explains how Git was created by Linus Torvalds for Linux kernel development and why it gained popularity due to its speed and efficiency. The document then covers Git basics like setup, commits, branches and workflows. It also introduces tools for using Git in Eclipse and GitLab for code hosting and collaboration.
Version control is a method for centrally storing files and keeping a record of changes made by developers. It allows tracking who made what changes and when. This allows developers to back up their work, track different versions of files, merge changes from multiple developers, and recover old versions if needed. Centralized version control systems like Subversion store all files in a central repository that developers check files out from and check changes back into. Subversion allows viewing changes between versions, rolling back changes, and recovering old project versions with a single version number across all files.
One of the biggest advantages of Git is its branching capabilities. Unlike centralized version control systems, Git branches are cheap and easy to merge. This facilitates the feature branch workflow popular with many Git users.
Git provides a distributed version control system that is faster and more lightweight than the centralized SVN. Git allows for easy branching and merging of code. Developers can work independently on their local repositories and sync changes to remote repositories. This allows teams to work together seamlessly on codebases.
This document provides an overview of version control systems, including their benefits and basic functions. Version control systems allow recording changes to files over time, allowing users to recall specific file versions. They offer advantages like backup and restoration of files, synchronization across multiple computers, and facilitating collaboration on teams. The document defines common version control terms and best practices for users.
This document provides an introduction to Git and GitHub. It explains that Git is a widely used version control system that was created in 2005, while GitHub is an online platform that hosts Git repositories and allows for collaboration. Key Git concepts covered include repositories, commits, staging changes, branches, pushing and pulling changes. Basic Git commands like init, add, commit, clone, push and branch are also outlined.
Version control systems are a category of software tools that help a software team manage changes.
Git is a very well supported open source project.
Git is a mature, actively maintained open source project
originally developed in 2005 by Linus Torvalds.
GitHub is where over 73 million developers shape the future of software, together. Contribute to the open source community, manage your Git repositories
Git allows for a distributed model where every user has their own local copy of the code and changes are merged to a local master branch, while SVN uses a centralized model where changes are committed to a central repository. Git operations like diff and commit are much faster since they are performed locally without network latency. Git also uses much less storage space than SVN. A key advantage of Git is its powerful branching and merging capabilities.
The document discusses several common Git workflows:
- The Basic/Centralized Workflow is the most basic, similar to SVN, with a single master branch and all changes committed directly to it.
- The Feature Branch Workflow involves branching by feature, with each developer working on their own branch before merging into master via a pull request. This avoids broken code and allows code review.
- The Gitflow Workflow manages features, releases, and hotfixes across main branches like master and develop, plus feature, release, and hotfix branches. It is more complex but provides more structure than the Feature Branch.
- The Forking Workflow differs in that there is no central repository - each developer has their own public server
Hosting code online allows developers to securely store code, experiment safely without risk of damage, and gain feedback through collaboration. Services like BitBucket offer free hosting of Git and Mercurial projects, including wikis, issue tracking, and pull requests. BitBucket is written in Python using the Django framework and provides similar functionality to GitHub for hosting Git repositories.
This document provides an introduction to Git and GitHub. It outlines the basics of Git including initializing repositories, tracking changes, branching, merging, and resolving conflicts. It also covers GitHub concepts such as cloning repositories from GitHub to a local machine and pushing/pulling changes between local and remote repositories. The document explains how to collaborate on projects hosted on GitHub using Git.
Github - Git Training Slides: FoundationsLee Hanxue
Slide deck with detailed step breakdown that explains how git works, together with simple examples that you can try out yourself. Slides originated from http://teach.github.com/articles/course-slides/
Author: https://twitter.com/matthewmccull
The document provides an overview of version control systems and introduces Git and GitHub. It discusses the differences between centralized and distributed version control. It then covers the basics of using Git locally including initialization, staging files, committing changes, branching and merging. Finally, it demonstrates some common remote operations with GitHub such as pushing, pulling and tagging releases.
This document provides an overview of Git commands and workflows:
- It introduces basic Git commands for setting up a local repository, adding and committing files, viewing the status and differences between commits, ignoring files, and more.
- Common workflows are demonstrated including cloning a repository, making changes and committing them locally, and pushing changes to a remote repository.
- More advanced topics are covered like branching, merging, rebasing, resolving conflicts, and using tools to help with these processes.
- Configuration options and tips are provided to customize Git behavior and inspect repositories.
This document summarizes a presentation given at DrupalCamp in Athens on December 12, 2010 about Git and GitHub. The presentation introduced Git as a distributed version control system designed for speed and efficiency. It explained some of Git's core concepts like snapshots, branches, merging, and its distributed nature. It also promoted GitHub as a social coding platform that improves collaboration and code hosting for both open source and private projects. The presentation aimed to help attendees learn Git for their own benefit and prepare for Drupal moving to GitHub.
This document provides an overview of Git and GitHub. It describes key Git concepts and commands like commit, push, pull, clone, fetch, merge, diff, branching, and .gitignore. It also provides step-by-step instructions for initializing a Git repository, making configurations, adding and committing files, checking out different versions, comparing changes, removing files, pushing changes to remote repositories, cloning repositories, fetching updates, creating and merging branches, and deleting branches. The goal is to explain both the theory and practical usage of version control with Git and GitHub.
Jenkins is the leading open source continuous integration tool. It builds and tests our software continuously and monitors the execution and status of remote jobs, making it easier for team members and users to regularly obtain the latest stable code.
Recently one of our customers faced the challenge of fixing a production error in his desktop client application. The application is deployed in different versions and may of course be deployed to different customers with a different set of features. Although this scenario seems quite common nowadays, a lot of software companies are not ready to tackle this problem.
Continuous integration involves developers committing code changes daily which are then automatically built and tested. Continuous delivery takes this further by automatically deploying code changes that pass testing to production environments. The document outlines how Jenkins can be used to implement continuous integration and continuous delivery through automating builds, testing, and deployments to keep the process fast, repeatable and ensure quality.
What is version control software and why do you need it?Leonid Mamchenkov
Version control software (VCS) manages changes to files such as documents, images, and code. It allows users to undo changes, try ideas, collaborate, and troubleshoot. VCS originated from engineering blueprints and software development in the early UNIX days. It works by storing revisions in a repository with branches and tags. Git is the most commonly used VCS as it is free, distributed, fast, and the standard for open source projects. Users can get started by installing Git, configuring user information, initializing repositories for projects, and committing file changes with descriptive messages.
Distributed version control with git provides a brief introduction to git. It discusses why git was created, what git is, the git object model of blobs, trees and commits, collaborating through local and remote repositories, branching and merging, and an overview of the basic git workflow. The document provides resources for learning more about git.
Version control is a method for centrally storing files and keeping a record of changes made by developers. It allows tracking who made what changes and when. This allows developers to back up their work, track different versions of files, merge changes from multiple developers, and recover old versions if needed. Centralized version control systems like Subversion store all files in a central repository that developers check files out from and check changes back into. Subversion allows viewing changes between versions, rolling back changes, and recovering old project versions with a single version number across all files.
One of the biggest advantages of Git is its branching capabilities. Unlike centralized version control systems, Git branches are cheap and easy to merge. This facilitates the feature branch workflow popular with many Git users.
Git provides a distributed version control system that is faster and more lightweight than the centralized SVN. Git allows for easy branching and merging of code. Developers can work independently on their local repositories and sync changes to remote repositories. This allows teams to work together seamlessly on codebases.
This document provides an overview of version control systems, including their benefits and basic functions. Version control systems allow recording changes to files over time, allowing users to recall specific file versions. They offer advantages like backup and restoration of files, synchronization across multiple computers, and facilitating collaboration on teams. The document defines common version control terms and best practices for users.
This document provides an introduction to Git and GitHub. It explains that Git is a widely used version control system that was created in 2005, while GitHub is an online platform that hosts Git repositories and allows for collaboration. Key Git concepts covered include repositories, commits, staging changes, branches, pushing and pulling changes. Basic Git commands like init, add, commit, clone, push and branch are also outlined.
Version control systems are a category of software tools that help a software team manage changes.
Git is a very well supported open source project.
Git is a mature, actively maintained open source project
originally developed in 2005 by Linus Torvalds.
GitHub is where over 73 million developers shape the future of software, together. Contribute to the open source community, manage your Git repositories
Git allows for a distributed model where every user has their own local copy of the code and changes are merged to a local master branch, while SVN uses a centralized model where changes are committed to a central repository. Git operations like diff and commit are much faster since they are performed locally without network latency. Git also uses much less storage space than SVN. A key advantage of Git is its powerful branching and merging capabilities.
The document discusses several common Git workflows:
- The Basic/Centralized Workflow is the most basic, similar to SVN, with a single master branch and all changes committed directly to it.
- The Feature Branch Workflow involves branching by feature, with each developer working on their own branch before merging into master via a pull request. This avoids broken code and allows code review.
- The Gitflow Workflow manages features, releases, and hotfixes across main branches like master and develop, plus feature, release, and hotfix branches. It is more complex but provides more structure than the Feature Branch.
- The Forking Workflow differs in that there is no central repository - each developer has their own public server
Hosting code online allows developers to securely store code, experiment safely without risk of damage, and gain feedback through collaboration. Services like BitBucket offer free hosting of Git and Mercurial projects, including wikis, issue tracking, and pull requests. BitBucket is written in Python using the Django framework and provides similar functionality to GitHub for hosting Git repositories.
This document provides an introduction to Git and GitHub. It outlines the basics of Git including initializing repositories, tracking changes, branching, merging, and resolving conflicts. It also covers GitHub concepts such as cloning repositories from GitHub to a local machine and pushing/pulling changes between local and remote repositories. The document explains how to collaborate on projects hosted on GitHub using Git.
Github - Git Training Slides: FoundationsLee Hanxue
Slide deck with detailed step breakdown that explains how git works, together with simple examples that you can try out yourself. Slides originated from http://teach.github.com/articles/course-slides/
Author: https://twitter.com/matthewmccull
The document provides an overview of version control systems and introduces Git and GitHub. It discusses the differences between centralized and distributed version control. It then covers the basics of using Git locally including initialization, staging files, committing changes, branching and merging. Finally, it demonstrates some common remote operations with GitHub such as pushing, pulling and tagging releases.
This document provides an overview of Git commands and workflows:
- It introduces basic Git commands for setting up a local repository, adding and committing files, viewing the status and differences between commits, ignoring files, and more.
- Common workflows are demonstrated including cloning a repository, making changes and committing them locally, and pushing changes to a remote repository.
- More advanced topics are covered like branching, merging, rebasing, resolving conflicts, and using tools to help with these processes.
- Configuration options and tips are provided to customize Git behavior and inspect repositories.
This document summarizes a presentation given at DrupalCamp in Athens on December 12, 2010 about Git and GitHub. The presentation introduced Git as a distributed version control system designed for speed and efficiency. It explained some of Git's core concepts like snapshots, branches, merging, and its distributed nature. It also promoted GitHub as a social coding platform that improves collaboration and code hosting for both open source and private projects. The presentation aimed to help attendees learn Git for their own benefit and prepare for Drupal moving to GitHub.
This document provides an overview of Git and GitHub. It describes key Git concepts and commands like commit, push, pull, clone, fetch, merge, diff, branching, and .gitignore. It also provides step-by-step instructions for initializing a Git repository, making configurations, adding and committing files, checking out different versions, comparing changes, removing files, pushing changes to remote repositories, cloning repositories, fetching updates, creating and merging branches, and deleting branches. The goal is to explain both the theory and practical usage of version control with Git and GitHub.
Jenkins is the leading open source continuous integration tool. It builds and tests our software continuously and monitors the execution and status of remote jobs, making it easier for team members and users to regularly obtain the latest stable code.
Recently one of our customers faced the challenge of fixing a production error in his desktop client application. The application is deployed in different versions and may of course be deployed to different customers with a different set of features. Although this scenario seems quite common nowadays, a lot of software companies are not ready to tackle this problem.
Continuous integration involves developers committing code changes daily which are then automatically built and tested. Continuous delivery takes this further by automatically deploying code changes that pass testing to production environments. The document outlines how Jenkins can be used to implement continuous integration and continuous delivery through automating builds, testing, and deployments to keep the process fast, repeatable and ensure quality.
What is version control software and why do you need it?Leonid Mamchenkov
Version control software (VCS) manages changes to files such as documents, images, and code. It allows users to undo changes, try ideas, collaborate, and troubleshoot. VCS originated from engineering blueprints and software development in the early UNIX days. It works by storing revisions in a repository with branches and tags. Git is the most commonly used VCS as it is free, distributed, fast, and the standard for open source projects. Users can get started by installing Git, configuring user information, initializing repositories for projects, and committing file changes with descriptive messages.
Distributed version control with git provides a brief introduction to git. It discusses why git was created, what git is, the git object model of blobs, trees and commits, collaborating through local and remote repositories, branching and merging, and an overview of the basic git workflow. The document provides resources for learning more about git.
This document provides an overview of version control and the basics of using Git. It discusses why backups are important, how version control works, and how to install and set up Git. It then covers basic Git commands and workflows for creating repositories, cloning repositories, staging and committing changes, branching and merging, tagging releases, ignoring files, resolving conflicts, and working in a distributed environment.
This document provides an overview of version control and the distributed version control system Git. It discusses the history and benefits of version control, including backup and recovery, synchronization, undo capabilities, and tracking changes. Key aspects of Git are explained, such as branching and merging, the fast and efficient nature of Git, and how it allows for cheap local experimentation through branches. The document demonstrates Git workflows and commands and provides resources for further information.
Introduction to Version Control and Configuration ManagementPhilip Johnson
Version control systems like SVN aim to address three classic configuration management problems: the double maintenance problem of multiple copies needing separate updates, the shared data problem of developers accessing the same files, and the simultaneous update problem of file clobbering during concurrent edits. SVN improves on CVS by using a database backend instead of file versions, supporting repository-wide instead of file-based versions, and using directory-based tags and branches. Distributed version control systems like Git store a full code repository locally and support decentralized workflows without a central server.
This document provides a brief introduction to Git, a distributed version control system. It describes what Git is and some of its key features, such as tracking changes to files over time, supporting distributed development, efficient object storage, easy branching and merging, and universal public identifiers. The document also discusses some of Git's internal mechanisms, such as SHA-1 hashes to uniquely identify objects, the index cache, and how commits and branches work.
This document provides an overview of version control using Subversion (SVN). It discusses key SVN concepts like the trunk, branches, and tags. It explains how SVN allows for collaboration between developers and management of code revisions. The document also summarizes SVN features like authentication, revision management, tagging for releases, and advanced topics like hooks and externals.
A Basic Git intro presentation for SVN long timers doing their first steps in Git.
This presentation is meant to clear up most of the basic concepts which cause confusion with developers using Git as if it was an SVN.
Introduction to Git/Github - A beginner's guideRohit Arora
Introduction to Git/Github - A beginner's guide
Agenda:
Installing Git
Introduction to Version Control
Git Basics
Creating a new local Git repository
Cloning a Git repository
Making use of Git commit history
Reverting files to previous states
Creating a Github Repository
Adding, Committing & Pushing changes
Branching
Merging Branches
Sending Pull Requests
Conflict Resolution
and 3 Exercises
Git 101 - Crash Course in Version Control using GitGeoff Hoffman
Find out why more and more developers are switching to Git - distributed version control. This intro to Git covers the basics, from cloning to pushing for beginners.
Version Control Systems - ArabNet Beirut 2014 - Dani ArnaoutDani Arnaout
This is the presentation that was given at ArabNet Beirut 2014. It cover some basic & intermediate info about Version Control Systems in a simple & special way.
It includes lots of images & just few text, so you won't be able to fully understand what's going on unless you watched the talk.
Will add a link to the talk once it becomes available.
An introduction to Version Control SystemsJon Warbrick
Version control systems allow users to track changes to documents and code over time, maintain revision histories, and collaborate on projects. They provide features like check-outs that allow editing working copies, commits to save changes to repositories, diffs to view differences between versions, and merging of changes from multiple branches. Version control is well-suited for software source code management and collaborative work, but not as effective for tasks like bug tracking or large media files.
Provides an absolute beginner\'s guide to how version control works, why you should switch and how to get started. Note that this presentation was for Design 4 Drupal, so it is angled towards Drupal themers.
Distributed Version Control Systems in the Enterprise - Atlassian Summit 2010Atlassian
This document discusses distributed version control (DVCS) and the benefits of migrating to a DVCS like Mercurial from a centralized version control system (CVS). It provides an overview of DVCS and popular options like Git and Mercurial. It then details a case study of a team that migrated their codebase from Subversion to Mercurial, including the reasons for choosing Mercurial, the conversion process using different Mercurial extensions, and exporting the code to their new hosting provider.
Using a revision control system that tracks changes in source code with ways to manage your code in separate branches and tag revisions as releases is a bare minimum for developers.
This presentation highlights the importance of using a version control system Subversion.
CVS is a version control system that allows users to record the history of source files. It stores different versions of files in a single file to save disk space. CVS helps groups of developers work on the same project by preventing accidental overwriting of each other's changes. The document provides a sample session demonstrating how a developer would check out source files from the CVS repository, make changes locally, and commit the updated files back to the repository.
This document provides an overview of implementing affordable disaster recovery with Hyper-V and multi-site clustering. It discusses what constitutes a disaster, the key components needed which are a storage mechanism, replication mechanism, and target servers/cluster. It also covers clustering history, what a cluster is, and the important concept of quorum which determines a cluster's existence through voting of its members.
Analyze a SVC, STORWIZE metro/ global mirror performance problem-v58-20150818...Michael Pirker
Latency problem was reported for VDisk CA-CL1-Disk04-N at 02/05/15 8:09,
The environment are two clusters connected with Metro Mirror. The first aim of this document is to show how we found the root cause of this problem in the link between the two clusters.
The second aim of this document is to describe how the root cause for this problem was found by using the BVQ structured performance problem analysis method. It demonstrates that successful analysis work needs a structured method and also a tool which supports this method and delivers the needed technical insight. We have the concept that everybody should be able to conduct a performance analysis. This is important because the level of service is lowered day by day and especially small customers are more and more reliant on their own skills or on the skills of their partners. This is a common problem occurring at all vendors!
The document discusses strategies for constructing and administering VMware vSphere environments. It notes that 44% of virtualization deployments fail due to issues like lack of ROI quantification and training. 55% of organizations experience more problems than benefits with virtualization due to issues like lack of visibility, tools, and education. The document advocates becoming an "ESXpert" to elevate your experience with virtualization and avoid common pitfalls. It outlines six typical steps in a virtualization implementation including environment assessment, constructing virtualization, backups expansion, virtualization to private cloud, virtualization at the desktop, and DR implementation.
Version control systems (VCS) allow developers to manage code through capabilities like reversibility, concurrency, and annotation. Subversion is a popular centralized VCS that was released in 2000. It uses a trunk-branch-tag structure where the trunk contains stable code, branches are for development work, and tags create snapshots. Developers check code out from the repository, check changes in after making modifications, and view file histories.
JavaEdge 2008: Your next version control systemGilad Garon
The next generation of VCS has a clear target ahead of them: making branching and merging easier. Until recently, Subversion was dominating the world of Version Control Systems, but now, Distributed Version Control Systems are growing in popularity and everywhere you go you hear about Git or Mercurial, and how they make branching and merging a breeze. But the Subversion team isn't going down quietly, they have a new weapon: the 1.5 version. Learn about the next generation of Version Control Systems is planning to solve your problems.
The document provides an overview of using Subversion (SVN) for source code control, including how to set up SVN clients and servers, basic and advanced SVN commands, best practices for usage, and how to install the VisualSVN server software. SVN allows developers to concurrently edit and manage different versions of code through features like revision tracking, merging, branching and locking files during edits. The document recommends using SVN for both individual developers and development teams to avoid issues with shared network drives and provides instructions for getting started with clients like TortoiseSVN and servers like VisualSVN.
This document is a slide deck about Hyper-V high availability and live migration presented by Greg Shields of Concentrated Technology. The deck covers understanding live migration and its role in Hyper-V HA, fundamentals of Windows failover clustering, building a two-node Hyper-V cluster with iSCSI storage, managing a Hyper-V cluster, and adding disaster recovery with multi-site clustering. The deck is intended to help IT professionals implement and manage highly available Hyper-V environments.
This document discusses the benefits of distributed version control systems (DVCS) like Git over centralized version control systems (CVCS) like SVN. It argues that DVCS tools make collaboration and branching much easier and more flexible. Various workflow models for DVCS are presented, including integrating feature branches and using different roles like integration managers. The document provides references for learning more about Git and distributed version control.
Managing VMware with PowerShell - VMworld 2008Carter Shanklin
This is the slide deck I used during my talk "Managing VMware with PowerShell" at VMworld 2008. Some video snippets of the presentation are also available at http://communities.vmware.com/thread/169066
Maven is a project management tool that provides conventions for building Java projects, including a standard project structure, dependency management, and lifecycle phases. It simplifies development by standardizing common tasks like compiling, testing, packaging, and deploying. Compared to Ant, Maven takes a more convention-based approach and handles dependencies and lifecycles automatically. The document provides an overview of Maven's key features and how it can help manage Java projects.
This document provides an overview of new features and changes in Maven 3.0, including improved compatibility, speed, efficiency and extensibility compared to previous versions. It discusses updates to the POM format like additional validations and the consolidation of profiles. New capabilities in Maven 3.0 include parallel builds, artifact resolution caching, and changes to plugin behavior. The document also introduces mvnshell and polyglot Maven, which expand the Maven command-line and allow projects to use alternative DSLs.
This document provides an overview of Apache Subversion (SVN), a version control system. It discusses basic SVN concepts like repositories, trunks, tags, and branches. It also covers setting up the SVN environment, including installing SVN, configuring Apache, setting up users and repositories. The document then outlines the typical SVN lifecycle of creating a repository, checking out a working copy, making changes, reviewing changes, resolving conflicts, and committing updates. It provides details on key SVN processes like checking out, making changes, updating, fixing mistakes, and resolving conflicts. Finally, it briefly discusses tags and branching in SVN. The document serves as a tutorial for understanding and using SVN for software version control.
This document provides an overview of the key operations in the Subversion (SVN) version control system life cycle. It describes creating a repository, checking out a working copy, updating changes from the repository, performing edits and other changes locally, reviewing pending changes, fixing mistakes by reverting changes, and resolving conflicts when merging changes. The main operations covered are checkout, update, commit, status, diff, revert, and merge.
This document discusses version control and introduces Git. It defines version control as a system to record changes to files. Centralized version control stores changes on a central server, while distributed version control gives each user a complete copy of the code repository. The document then covers basic Git commands like init, add, commit, log, revert, branch, merge, and handling merge conflicts. More resources for learning Git are provided.
This document provides an overview and tutorial on using the Apache Subversion (SVN) version control system. It begins with introducing basic SVN concepts like repositories, trunks, tags, branches and working copies. It then describes how to set up the SVN environment, including installing SVN on Linux, configuring Apache as the HTTP server, and creating repositories and user accounts. The rest of the tutorial covers the SVN lifecycle including checkout, commit, update, and resolving conflicts. It also discusses features like tags and branching.
Which transient when? - A utility function for transient follow-up schedulingTim Staley
Next-generation astronomical facilities such as the LSST and the SKA will be game-changers, allowing us to observe the entire southern sky and track changing sources in near real-time. Keeping up with their alert-streams represents a significant challenge - how do we make the most of our limited telescope resources to follow up 100000 sources per night?
The biggest problem here is classification - we want to find the really interesting transients and spend our time watching those. However, classification based on the initial survey data can only get you so far - we'll need to use robotic follow-up telescopes for rapid-response observations, to give us more information on the most promising targets. To get the most science done, we need to be smart about scheduling that follow-up.
We're exploring use of active learning algorithms (AKA Bayesian Decision Theory) to solve this problem, building a framework that allows for iterative refinement of a probabilistic classification state. Because there are no algorithms that fit this problem 'out-of-the-box', we've built our own analysis framework using the emcee and PyMultiNest packages to power the underlying Bayesian inference. I'll give an overview of how our proposed system fits into the wider context of an automated astronomy ecosystem, then give a gentle introduction to Bayesian Decision Theory and how it can be applied to this problem.
How to build a TraP: An image-plane transient-discovery toolTim Staley
There are three main points summarized:
1. There are many interesting slow radio transients that could be detected through imaging surveys like accretion flares, orphan gamma-ray bursts, and flare stars.
2. Radio surveys are increasing in sensitivity and field of view by orders of magnitude with instruments like LOFAR, enabling the detection of more rare transient events.
3. TraP is a transient detection pipeline that works by extracting sources from radio images, matching to known sources, identifying new bright sources, analyzing light curves, and making the results accessible through a user-friendly web interface.
From gamma-ray to radio: Multi-wavelength follow-up in the first five minutesTim Staley
This document summarizes recent work on fast radio follow-up of transient sources and multi-wavelength classification. It discusses three key areas: 1) examples of fast radio follow-up of gamma-ray bursts and stellar flares, 2) using radio and optical measurements to classify transients, and 3) the need to automate "transient triage" to efficiently prioritize follow-up observations across different facilities. The presenter argues that distributing information about new transients via VOEvents can help the community automate real-time classification and prioritization of targets.
Tunable algorithms for transient follow-upTim Staley
This document discusses an approach for optimizing follow-up observations of astronomical transients using Bayesian decision theory. The approach uses transient lightcurve models, telescope noise models, and prior information to calculate the information content of potential future observations. Observations are prioritized based on their expected information content to efficiently classify transients. The presenter outlines the necessary components for a software system to implement this approach, including lightcurve generation, data fitting, calculating confusion matrices, and an observation scheduler. Future work involves integrating these components and testing the system in realistic simulations.
Training your astronomy robots to work as a teamTim Staley
I present a case that the astronomy community is missing a part of the puzzle for the next era of automated big-survey astronomy: we currently have very little published work on target prioritization and optimized observation scheduling. I discuss the sociological issues surrounding the sort of open collaboration needed to make optimal use of globally distributed observatories, and show some preliminary work on generally-applicable classification methods.
An invited talk given to an audience interested in using lucky imaging for microlensing studies. I tried to give an overview of where the challenges lie in getting good science data using lucky imaging techniques.
Lucky imaging - Life in the visible after HSTTim Staley
This document discusses using lucky imaging techniques to improve spatial resolution in astronomy. Standard lucky imaging can select the best frames from thousands taken at high speed to achieve near-diffraction limited resolution on ground-based telescopes. When combined with adaptive optics, lucky imaging can further improve resolution and help expand the sky coverage of AO. Potential applications include exoplanet imaging, resolving close binary stars, and probing binarity in globular cluster cores.
How Valletta helped healthcare SaaS to transform QA and compliance to grow wi...Egor Kaleynik
This case study explores how we partnered with a mid-sized U.S. healthcare SaaS provider to help them scale from a successful pilot phase to supporting over 10,000 users—while meeting strict HIPAA compliance requirements.
Faced with slow, manual testing cycles, frequent regression bugs, and looming audit risks, their growth was at risk. Their existing QA processes couldn’t keep up with the complexity of real-time biometric data handling, and earlier automation attempts had failed due to unreliable tools and fragmented workflows.
We stepped in to deliver a full QA and DevOps transformation. Our team replaced their fragile legacy tests with Testim’s self-healing automation, integrated Postman and OWASP ZAP into Jenkins pipelines for continuous API and security validation, and leveraged AWS Device Farm for real-device, region-specific compliance testing. Custom deployment scripts gave them control over rollouts without relying on heavy CI/CD infrastructure.
The result? Test cycle times were reduced from 3 days to just 8 hours, regression bugs dropped by 40%, and they passed their first HIPAA audit without issue—unlocking faster contract signings and enabling them to expand confidently. More than just a technical upgrade, this project embedded compliance into every phase of development, proving that SaaS providers in regulated industries can scale fast and stay secure.
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Adobe Illustrator is a powerful, professional-grade vector graphics software used for creating a wide range of designs, including logos, icons, illustrations, and more. Unlike raster graphics (like photos), which are made of pixels, vector graphics in Illustrator are defined by mathematical equations, allowing them to be scaled up or down infinitely without losing quality.
Here's a more detailed explanation:
Key Features and Capabilities:
Vector-Based Design:
Illustrator's foundation is its use of vector graphics, meaning designs are created using paths, lines, shapes, and curves defined mathematically.
Scalability:
This vector-based approach allows for designs to be resized without any loss of resolution or quality, making it suitable for various print and digital applications.
Design Creation:
Illustrator is used for a wide variety of design purposes, including:
Logos and Brand Identity: Creating logos, icons, and other brand assets.
Illustrations: Designing detailed illustrations for books, magazines, web pages, and more.
Marketing Materials: Creating posters, flyers, banners, and other marketing visuals.
Web Design: Designing web graphics, including icons, buttons, and layouts.
Text Handling:
Illustrator offers sophisticated typography tools for manipulating and designing text within your graphics.
Brushes and Effects:
It provides a range of brushes and effects for adding artistic touches and visual styles to your designs.
Integration with Other Adobe Software:
Illustrator integrates seamlessly with other Adobe Creative Cloud apps like Photoshop, InDesign, and Dreamweaver, facilitating a smooth workflow.
Why Use Illustrator?
Professional-Grade Features:
Illustrator offers a comprehensive set of tools and features for professional design work.
Versatility:
It can be used for a wide range of design tasks and applications, making it a versatile tool for designers.
Industry Standard:
Illustrator is a widely used and recognized software in the graphic design industry.
Creative Freedom:
It empowers designers to create detailed, high-quality graphics with a high degree of control and precision.
Mastering OOP: Understanding the Four Core PillarsMarcel David
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Dive into the essential concepts of Object-Oriented Programming (OOP) with a detailed explanation of its four key pillars: Encapsulation, Inheritance, Polymorphism, and Abstraction. Understand how these principles contribute to robust, maintainable, and scalable software development.
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Proactive Vulnerability Detection in Source Code Using Graph Neural Networks:...Ranjan Baisak
As software complexity grows, traditional static analysis tools struggle to detect vulnerabilities with both precision and context—often triggering high false positive rates and developer fatigue. This article explores how Graph Neural Networks (GNNs), when applied to source code representations like Abstract Syntax Trees (ASTs), Control Flow Graphs (CFGs), and Data Flow Graphs (DFGs), can revolutionize vulnerability detection. We break down how GNNs model code semantics more effectively than flat token sequences, and how techniques like attention mechanisms, hybrid graph construction, and feedback loops significantly reduce false positives. With insights from real-world datasets and recent research, this guide shows how to build more reliable, proactive, and interpretable vulnerability detection systems using GNNs.
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Wondershare Filmora is a video editing software and app designed for both beginners and experienced users. It's known for its user-friendly interface, drag-and-drop functionality, and a wide range of tools and features for creating and editing videos. Filmora is available on Windows, macOS, iOS (iPhone/iPad), and Android platforms.
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Adobe Lightroom Classic is a desktop-based software application for editing and managing digital photos. It focuses on providing users with a powerful and comprehensive set of tools for organizing, editing, and processing their images on their computer. Unlike the newer Lightroom, which is cloud-based, Lightroom Classic stores photos locally on your computer and offers a more traditional workflow for professional photographers.
Here's a more detailed breakdown:
Key Features and Functions:
Organization:
Lightroom Classic provides robust tools for organizing your photos, including creating collections, using keywords, flags, and color labels.
Editing:
It offers a wide range of editing tools for making adjustments to color, tone, and more.
Processing:
Lightroom Classic can process RAW files, allowing for significant adjustments and fine-tuning of images.
Desktop-Focused:
The application is designed to be used on a computer, with the original photos stored locally on the hard drive.
Non-Destructive Editing:
Edits are applied to the original photos in a non-destructive way, meaning the original files remain untouched.
Key Differences from Lightroom (Cloud-Based):
Storage Location:
Lightroom Classic stores photos locally on your computer, while Lightroom stores them in the cloud.
Workflow:
Lightroom Classic is designed for a desktop workflow, while Lightroom is designed for a cloud-based workflow.
Connectivity:
Lightroom Classic can be used offline, while Lightroom requires an internet connection to sync and access photos.
Organization:
Lightroom Classic offers more advanced organization features like Collections and Keywords.
Who is it for?
Professional Photographers:
PCMag notes that Lightroom Classic is a popular choice among professional photographers who need the flexibility and control of a desktop-based application.
Users with Large Collections:
Those with extensive photo collections may prefer Lightroom Classic's local storage and robust organization features.
Users who prefer a traditional workflow:
Users who prefer a more traditional desktop workflow, with their original photos stored on their computer, will find Lightroom Classic a good fit.
Agentic AI Use Cases using GenAI LLM modelsManish Chopra
This document presents specific use cases for Agentic AI (Artificial Intelligence), featuring Large Language Models (LLMs), Generative AI, and snippets of Python code alongside each use case.
Who Watches the Watchmen (SciFiDevCon 2025)Allon Mureinik
Tests, especially unit tests, are the developers’ superheroes. They allow us to mess around with our code and keep us safe.
We often trust them with the safety of our codebase, but how do we know that we should? How do we know that this trust is well-deserved?
Enter mutation testing – by intentionally injecting harmful mutations into our code and seeing if they are caught by the tests, we can evaluate the quality of the safety net they provide. By watching the watchmen, we can make sure our tests really protect us, and we aren’t just green-washing our IDEs to a false sense of security.
Talk from SciFiDevCon 2025
https://www.scifidevcon.com/courses/2025-scifidevcon/contents/680efa43ae4f5
How to Batch Export Lotus Notes NSF Emails to Outlook PST Easily?steaveroggers
Migrating from Lotus Notes to Outlook can be a complex and time-consuming task, especially when dealing with large volumes of NSF emails. This presentation provides a complete guide on how to batch export Lotus Notes NSF emails to Outlook PST format quickly and securely. It highlights the challenges of manual methods, the benefits of using an automated tool, and introduces eSoftTools NSF to PST Converter Software — a reliable solution designed to handle bulk email migrations efficiently. Learn about the software’s key features, step-by-step export process, system requirements, and how it ensures 100% data accuracy and folder structure preservation during migration. Make your email transition smoother, safer, and faster with the right approach.
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Landscape of Requirements Engineering for/by AI through Literature ReviewHironori Washizaki
Hironori Washizaki, "Landscape of Requirements Engineering for/by AI through Literature Review," RAISE 2025: Workshop on Requirements engineering for AI-powered SoftwarE, 2025.
Scaling GraphRAG: Efficient Knowledge Retrieval for Enterprise AIdanshalev
If we were building a GenAI stack today, we'd start with one question: Can your retrieval system handle multi-hop logic?
Trick question, b/c most can’t. They treat retrieval as nearest-neighbor search.
Today, we discussed scaling #GraphRAG at AWS DevOps Day, and the takeaway is clear: VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval.
GraphRAG builds a knowledge graph from source documents, allowing for a deeper understanding of the data + higher accuracy.
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Adobe After Effects is a software application used for creating motion graphics, special effects, and video compositing. It's widely used in TV and film post-production, as well as for creating visuals for online content, presentations, and more. While it can be used to create basic animations and designs, its primary strength lies in adding visual effects and motion to videos and graphics after they have been edited.
Here's a more detailed breakdown:
Motion Graphics:
.
After Effects is powerful for creating animated titles, transitions, and other visual elements to enhance the look of videos and presentations.
Visual Effects:
.
It's used extensively in film and television for creating special effects like green screen compositing, object manipulation, and other visual enhancements.
Video Compositing:
.
After Effects allows users to combine multiple video clips, images, and graphics to create a final, cohesive visual.
Animation:
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It uses keyframes to create smooth, animated sequences, allowing for precise control over the movement and appearance of objects.
Integration with Adobe Creative Cloud:
.
After Effects is part of the Adobe Creative Cloud, a suite of software that includes other popular applications like Photoshop and Premiere Pro.
Post-Production Tool:
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After Effects is primarily used in the post-production phase, meaning it's used to enhance the visuals after the initial editing of footage has been completed.
TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...Andre Hora
Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be timeconsuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy.
Explaining GitHub Actions Failures with Large Language Models Challenges, In...ssuserb14185
GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupts development, causing delays and driving up costs. Diagnosing failures becomes especially challenging because error logs are often long, complex and unstructured. Given these difficulties, this study explores the potential of large language models (LLMs) to generate correct, clear, concise, and actionable contextual descriptions (or summaries) for GA failures, focusing on developers’ perceptions of their feasibility and usefulness. Our results show that over 80% of developers rated LLM explanations positively in terms of correctness for simpler/small logs. Overall, our findings suggest that LLMs can feasibly assist developers in understanding common GA errors, thus, potentially reducing manual analysis. However, we also found that improved reasoning abilities are needed to support more complex CI/CD scenarios. For instance, less experienced developers tend to be more positive on the described context, while seasoned developers prefer concise summaries. Overall, our work offers key insights for researchers enhancing LLM reasoning, particularly in adapting explanations to user expertise.
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When you say Xforce with GTA 5, it sounds like you might be talking about Xforce Keygen — a tool that's often mentioned in connection with cracking software like Autodesk programs.
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1. A brief introduction to
version control systems
Tim Staley
Astronomy Group Monday Seminar
Southampton, November 2013
WWW: timstaley.co.uk
2. The problem No backup Manual copies Centralised VCS Distributed VCS
Aims
Help identify problem that can be
solved.
Introduce basic concepts of version
control.
Explain why various technologies
exist, and which you should choose.
3. The problem No backup Manual copies Centralised VCS Distributed VCS
4. The problem No backup Manual copies Centralised VCS Distributed VCS
When you need version
control
Complex documents, built up over
time.
Multiple collaborators (or even just
multiple machines).
Multiple versions which ‘co-evolve.’
Reproducibility (‘snapshots’).
5. The problem No backup Manual copies Centralised VCS Distributed VCS
Four Evolutionary Stages
6. The problem No backup Manual copies Centralised VCS Distributed VCS
Stage 0: Not backing up
7. The problem No backup Manual copies Centralised VCS Distributed VCS
Stage 0: Not backing up
DON’T DO THIS
8. The problem No backup Manual copies Centralised VCS Distributed VCS
Stage 1: Manual copies
9. The problem No backup Manual copies Centralised VCS Distributed VCS
Stage 1: Manual copies
Flaws:
Manual = fallible.
Backup: Copies of copies.
Labelling.
10. The problem No backup Manual copies Centralised VCS Distributed VCS
Stage 1: Manual copies
Flaws:
Manual = fallible.
Backup: Copies of copies.
Labelling.
We need metadata - datestamps,
annotations, attribution.
And tools - make this stuff quick and
easy!
11. The problem No backup Manual copies Centralised VCS Distributed VCS
Aside: ‘Cloudy’ technologies
Trade off — convenience vs control.
Good for:
Small docs, frequently updated across
multiple locations (e.g. to-do list).
Basic backups of items unlikely to
evolve (photos, etc).
12. The problem No backup Manual copies Centralised VCS Distributed VCS
Aside: ‘Cloudy’ technologies
Problems:
Versioning is all automated - can’t
choose sensible ‘checkpoints’ to mark
out.
Collaboration is still broken, unless
you’re working on very simple docs.
13. The problem No backup Manual copies Centralised VCS Distributed VCS
Aside: ‘Cloudy’ technologies
Problems:
Versioning is all automated - can’t
choose sensible ‘checkpoints’ to mark
out.
Collaboration is still broken, unless
you’re working on very simple docs.
NEED MORE METADATA
14. The problem No backup Manual copies Centralised VCS Distributed VCS
Stage Two
15. The problem No backup Manual copies Centralised VCS Distributed VCS
Centralised version control
e.g.
‘Concurrent Versions System’ (CVS,
now defunct).
‘Subversion’ (SVN).
16. The problem No backup Manual copies Centralised VCS Distributed VCS
Basic concepts, 1
Record an annotated history of change
sets.
Trunk, branch
Parents, ancestors
17. The problem No backup Manual copies Centralised VCS Distributed VCS
Basic concepts, 2
Centralized ⇔ Master copy
Repository
Checkout
Commit / Revision
18. The problem No backup Manual copies Centralised VCS Distributed VCS
Basic concepts, 3
Merging
In simple cases, merges are automatic!
Tree-records allows us to build the new
combined version.
19. The problem No backup Manual copies Centralised VCS Distributed VCS
Basic concepts, 3
Manual merging: When conflicts exist,
we have the info and tools to manually
resolve them.
20. The problem No backup Manual copies Centralised VCS Distributed VCS
Distributed VCS
1986 – early 2000’s: Why would you
make this any more complex? This works.
21. The problem No backup Manual copies Centralised VCS Distributed VCS
Distributed VCS
1986 – early 2000’s: Why would you
make this any more complex? This works.
INTERWEBS
22. The problem No backup Manual copies Centralised VCS Distributed VCS
Distributed VCS
1986 – early 2000’s: Why would you
make this any more complex? This works.
INTERWEBS
(See e.g. visualised history of Python,
https://www.youtube.com/watch?v=
cNBtDstOTmA)
23. The problem No backup Manual copies Centralised VCS Distributed VCS
Centralised doesn’t scale
Many collaborators.
Cannot check-in half-finished work to
master.
Cannot keep track of a branch for
every collaborator.
24. The problem No backup Manual copies Centralised VCS Distributed VCS
Centralised doesn’t scale
Many collaborators.
Cannot check-in half-finished work to
master.
Cannot keep track of a branch for
every collaborator.
Resort back to hybrid of central copy
under version control, with many
local, manual backups for
intermediate work.
25. The problem No backup Manual copies Centralised VCS Distributed VCS
The distributed model
Stage 3: Distribute!
Everyone has their own mirror, or
clone of the repository.
Changes are distributed via pushes
and pulls.
26. The problem No backup Manual copies Centralised VCS Distributed VCS
Distribute!
Benefits for you:
More flexible. Allows different
workflows and collaborative behaviour
etc.
Can commit offline, sync later.
Talk to me later if you want the details.
27. The problem No backup Manual copies Centralised VCS Distributed VCS
So which should I use?
28. The problem No backup Manual copies Centralised VCS Distributed VCS
So which should I use?
At this stage, git and mercurial are
functionally equivalent — but git has won
the majority mindshare, therefore: better
support, better chance of collaborators
using same system, etc.
29. The problem No backup Manual copies Centralised VCS Distributed VCS
Summary
Version control helps with:
Backups
Reproducibility
Comparing arbitrary historical versions.
Maintaining multiple live versions.
Lots of free services and material
online to help you out.
Bit of a learning curve at first - but
payoff is large in long-run. (And now
you have a headstart!)
30. The problem No backup Manual copies Centralised VCS Distributed VCS
Advanced Reading
To start, google ‘git intro’, etc. Then. . .
Git for Computer Scientists
http://eagain.net/articles/
git-for-computer-scientists/
Understanding Git Conceptually
http://www.sbf5.com/~cduan/
technical/git/
Understanding the Git Workflow
https://sandofsky.com/blog/
git-workflow.html