Introduction to Software Engineering/Tools/Continuous Integration

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In software engineering, continuous integration (CI) implements continuous processes of applying quality control — small pieces of effort, applied frequently. Continuous integration aims to improve the quality of software, and to reduce the time taken to deliver it, by replacing the traditional practice of applying quality control after completing all development.

Theory[edit | edit source]

When embarking on a change, a developer takes a copy of the current code base on which to work. As other developers submit changed code to the code repository, this copy gradually ceases to reflect the repository code. When developers submit code to the repository they must first update their code to reflect the changes in the repository since they took their copy. The more changes the repository contains, the more work developers must do before submitting their own changes.

Eventually, the repository may become so different from the developers' baselines that they enter what is sometimes called "integration hell",[1] where the time it takes to integrate exceeds the time it took to make their original changes. In a worst-case scenario, developers may have to discard their changes and completely redo the work.

Continuous integration involves integrating early and often, so as to avoid the pitfalls of "integration hell". The practice aims to reduce rework and thus reduce cost and time.

The rest of this article discusses best practice in how to achieve continuous integration, and how to automate this practice. Automation is a best practice itself.[2][3]

Recommended practices[edit | edit source]

Continuous integration - as the practice of frequently integrating one's new or changed code with the existing code repository - should occur frequently enough that no intervening window remains between commit and build, and such that no errors can arise without developers noticing them and correcting them immediately.[4] Normal practice is to trigger these builds by every commit to a repository, rather than a periodically scheduled build. The practicalities of doing this in a multi-developer environment of rapid commits are such that it's usual to trigger a short timer after each commit, then to start a build when either this timer expires, or after a rather longer interval since the last build. Automated tools such as CruiseControl or Hudson offer this scheduling automatically.

Another factor is the need for a version control system that supports atomic commits, i.e. all of a developer's changes may be seen as a single commit operation. There is no point in trying to build from only half of the changed files.

Maintain a code repository[edit | edit source]

This practice advocates the use of a revision control system for the project's source code. All artifacts required to build the project should be placed in the repository. In this practice and in the revision control community, the convention is that the system should be buildable from a fresh checkout and not require additional dependencies. Extreme Programming advocate Martin Fowler also mentions that where branching is supported by tools, its use should be minimised [citation needed]. Instead, it is preferred that changes are integrated rather than creating multiple versions of the software that are maintained simultaneously. The mainline (or trunk) should be the place for the working version of the software.

Automate the build[edit | edit source]

A single command should have the capability of building the system. Many build-tools, such as make, have existed for many years. Other more recent tools like Ant, Maven, MSBuild or IBM Rational Build Forge are frequently used in continuous integration environments. Automation of the build should include automating the integration, which often includes deployment into a production-like environment. In many cases, the build script not only compiles binaries, but also generates documentation, website pages, statistics and distribution media (such as Windows MSI files, RPM or DEB files).

Make the build self-testing[edit | edit source]

Once the code is built, all tests should run to confirm that it behaves as the developers expect it to behave.

Everyone commits to the baseline every day[edit | edit source]

By committing regularly, every committer can reduce the number of conflicting changes. Checking in a week's worth of work runs the risk of conflicting with other features and can be very difficult to resolve. Early, small conflicts in an area of the system cause team members to communicate about the change they are making.

Many programmers recommend committing all changes at least once a day (once per feature built), and in addition performing a nightly build.

Every commit (to baseline) should be built[edit | edit source]

The system should build commits to the current working version in order to verify that they integrate correctly. A common practice is to use Automated Continuous Integration, although this may be done manually. For many, continuous integration is synonymous with using Automated Continuous Integration where a continuous integration server or daemon monitors the version control system for changes, then automatically runs the build process.

Keep the build fast[edit | edit source]

The build needs to complete rapidly, so that if there is a problem with integration, it is quickly identified.

Test in a clone of the production environment[edit | edit source]

Having a test environment can lead to failures in tested systems when they deploy in the production environment, because the production environment may differ from the test environment in a significant way. However, building a replica of a production environment is cost prohibitive. Instead, the pre-production environment should be built to be a scalable version of the actual production environment to both alleviate costs while maintaining technology stack composition and nuances.

Make it easy to get the latest deliverables[edit | edit source]

Making builds readily available to stakeholders and testers can reduce the amount of rework necessary when rebuilding a feature that doesn't meet requirements. Additionally, early testing reduces the chances that defects survive until deployment. Finding errors earlier also, in some cases, reduces the amount of work necessary to resolve them.

Everyone can see the results of the latest build[edit | edit source]

It should be easy to find out where/whether the build breaks and who made the relevant change.

Automate deployment[edit | edit source]

Most CI systems allow the running of scripts after a build finishes. In most situations, it is possible to write a script to deploy the application to a live test server that everyone can look at. A further advance in this way of thinking is Continuous Deployment, which calls for the software to be deployed directly into production, often with additional automation to prevent defects or regressions[5].

History[edit | edit source]

Continuous Integration emerged in the Extreme Programming (XP) community, and XP advocates Martin Fowler and Kent Beck first wrote about continuous integration circa 1999. Fowler's paper[6] is a popular source of information on the subject. Beck's book Extreme Programming Explained[7], the original reference for Extreme Programming, also describes the term.

Advantages and disadvantages[edit | edit source]

Advantages[edit | edit source]

Continuous integration has many advantages:

  • when unit tests fail or a bug emerges, developers might revert the codebase back to a bug-free state, without wasting time debugging
  • developers detect and fix integration problems continuously - avoiding last-minute chaos at release dates, (when everyone tries to check in their slightly incompatible versions).
  • early warning of broken/incompatible code
  • early warning of conflicting changes
  • immediate unit testing of all changes
  • constant availability of a "current" build for testing, demo, or release purposes
  • immediate feedback to developers on the quality, functionality, or system-wide impact of code they are writing
  • frequent code check-in pushes developers to create modular, less complex code[citation needed]
  • metrics generated from automated testing and CI (such as metrics for code coverage, code complexity, and features complete) focus developers on developing functional, quality code, and help develop momentum in a team[citation needed]

Disadvantages[edit | edit source]

  • initial setup time required
  • well-developed test-suite required to achieve automated testing advantages
  • large-scale refactoring can be troublesome due to continuously changing code base
  • hardware costs for build machines can be significant

Many teams using CI report that the advantages of CI well outweigh the disadvantages.[8] The effect of finding and fixing integration bugs early in the development process saves both time and money over the lifespan of a project.

Software[edit | edit source]

To support continuous integration, software tools such as automated build software can be employed.

Software tools for continuous integration include:

  • AnthillPro — continuous integration server by Urbancode
  • Apache Continuum — continuous integration server supporting Apache Maven and Apache Ant. Supports CVS, Subversion, Ant, Maven, and shell scripts
  • Apache Gump — continuous integration tool by Apache
  • Automated Build Studio — proprietary automated build, continuous integration and release management system by AutomatedQA
  • Bamboo — proprietary continuous integration server by Atlassian Software Systems
  • BuildBot — Python/Twisted-based continuous build system
  • BuildForge - proprietary automated build engine by IBM / Rational
  • BuildMaster — proprietary application lifecycle management and continuous integration tool by Inedo
  • CABIE - Continuous Automated Build and Integration Environment — open source, written in Perl; works with CVS, Subversion, AccuRev, Bazaar and Perforce
  • Cascade — proprietary continuous integration tool; provides a checkpointing facility to build and test changes before they are committed
  • codeBeamer — proprietary collaboration software with built-in continuous integration features
  • CruiseControl — Java-based framework for a continuous build process
  • CruiseControl.NET — .NET-based automated continuous integration server
  • CruiseControl.rb - Lightweight, Ruby-based continuous integration server that can build any codebase, not only Ruby, released under Apache Licence 2.0
  • ElectricCommander — proprietary continuous integration and release management solution from Electric Cloud
  • FinalBuilder Server — proprietary automated build and continuous integration server by VSoft Technologies
  • Go — proprietary agile build and release management software by Thoughtworks
  • Jenkins (formerly known as Hudson) — MIT-licensed, written in Java, runs in servlet container, supports CVS, Subversion, Mercurial, Git, StarTeam, Clearcase, Ant, NAnt, Maven, and shell scripts
  • Software Configuration and Library Manager — software configuration management system for z/OS by IBM Rational Software
  • QuickBuild - proprietary continuous integration server with free community edition featuring build life cycle management and pre-commit verification.
  • TeamCity — proprietary continuous-integration server by JetBrains with free professional edition
  • Team Foundation Server — proprietary continuous integration server and source code repository by Microsoft
  • Tinderbox — Mozilla-based product written in Perl
  • Rational Team Concert — proprietary software development collaboration platform with built-in build engine by IBM including Rational Build Forge

See comparison of continuous integration software for a more in depth feature matrix.

Further reading[edit | edit source]

  • Duvall, Paul M. (2007). Continuous Integration. Improving Software Quality and Reducing Risk. Addison-Wesley. ISBN 0-321-33638-0.

References[edit | edit source]

  1. Cunningham, Ward (05 Aug 2009). "Integration Hell". WikiWikiWeb. Retrieved 19 Sept 2009. {{cite web}}: Check date values in: |accessdate= and |date= (help)
  2. Brauneis, David (01 January 2010). "[OSLC Possible new Working Group - Automation"]. open-services.net Community mailing list. http://open-services.net/pipermail/community_open-services.net/2010-January/000214.html. Retrieved 16 February 2010. 
  3. Taylor, Bradley. "Rails Deployment and Automation with ShadowPuppet and Capistrano".
  4. Fowler, Martin. "Continuous Integration". Retrieved 2009-11-11.
  5. See Continuous deployment in 5 easy steps - O'Reilly Radar and Continuous Deployment at IMVU: Doing the impossible fifty times a day. - Timothy Fitz
  6. Fowler, Martin. "Continuous Integration".
  7. Beck, Kent (1999). Extreme Programming Explained. ISBN 0-201-61641-6.
  8. Richardson, Jared (September 2008). "Agile Testing Strategies at No Fluff Just Stuff Conference". Boston, Massachusetts. http://www.nofluffjuststuff.com. 

External links[edit | edit source]