Continuous integration (CI) is the practice of frequently building and testing a software system during its development. It is intended to ensure that code written by programmers is always buildable, runnable and passes automated testing. Developers merge to an integration branch and an automated system builds and tests.^[1] Often, the automated process runs on each commit or runs on a schedule such as once a day.

Grady Booch first proposed the term CI in 1991,^[2] although he did not advocate integrating multiple times a day, but later, CI came to include that aspect.^[3]

The earliest known work on continuous integration was the Infuse environment developed by G. E. Kaiser, D. E. Perry, and W. M. Schell.^[4]

In 1994, Grady Booch used the phrase continuous integration in Object-Oriented Analysis and Design with Applications (2nd edition)^[5] to explain how, when developing using micro processes, "internal releases represent a sort of continuous integration of the system, and exist to force closure of the micro process".

In 1997, Kent Beck and Ron Jeffries invented extreme programming (XP) while on the Chrysler Comprehensive Compensation System project, including continuous integration.^{[1][self-published source]} Beck published about continuous integration in 1998, emphasising the importance of face-to-face communication over technological support.^[6] In 1999, Beck elaborated more in his first full book on Extreme Programming.^[7] CruiseControl, one of the first open-source CI tools,^{[8][self-published source]} was released in 2001.

In 2010, Timothy Fitz published an article detailing how IMVU's engineering team had built and been using the first practical CI system. While his post was originally met with scepticism, it quickly caught on and found widespread adoption^[9] as part of the Lean software development methodology, also based on IMVU.

A stated goal of CI is to run the automated process 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.^[1] Generally, this means triggering builds on each commit to a repository. Due to processing limitations, sometimes multiple changes are committed between automation runs.

A server builds the integration branch frequently.

Once built, all tests should run.^[10]

The server may also run other quality control and software quality processes such as static analysis, measuring performance, extracting documentation from the source code, and facilitating manual QA processes.

This section lists best practices from practitioners for other practices that enhance CI.

Build automation is a best practice.^[11][12]

CI requires the version control system to support atomic commits; i.e., all of a developer's changes are handled as a single commit.

When making a code change, a developer creates a branch that is a copy of the current codebase. As other changes are committed to the repository, this copy diverges from the latest version.

The longer development continues on a branch without merging to the integration branch, the greater the risk of multiple integration conflicts^[13] and failures when the developer branch is eventually merged back. 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 referred to as "merge hell", or "integration hell",^[14] where the time it takes to integrate exceeds the time it took to make their original changes.^[15]

Proponents of CI suggest that developers should use test-driven development and to ensure that all unit tests pass locally before committing to the integration branch so that one developer's work does not break another developer's copy.

Incomplete features can be disabled before committing, using feature toggles.

Continuous delivery ensures the software checked in on an integration branch is always in a state that can be deployed to users, and continuous deployment automates the deployment process.

Continuous delivery and continuous deployment are often performed in conjunction with CI and together form a CI/CD pipeline.

Proponents of CI recommend storing all files and information needed for building in version control, (for git a repository); that the system should be buildable from a fresh checkout and not require additional dependencies.

Martin Fowler recommends that all developers commit to the same integration branch.^[16]

Build automation tools automate building.

Proponents of CI recommend that a single command should have the capability of building the system.

Automation often includes 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 Debian DEB, Red Hat RPM or Windows MSI files).

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.^[17] Committing all changes at least once a day (once per feature built) is generally considered part of the definition of Continuous Integration. In addition, performing a nightly build is generally recommended.^{[citation needed]} These are lower bounds; the typical frequency is expected to be much higher.

The system should build commits to the current working version to verify that they integrate correctly. A common practice is to use Automated Continuous Integration, although this may be done manually. Automated Continuous Integration employs a continuous integration server or daemon to monitor the revision control system for changes, then automatically run the build process.

When fixing a bug, it is a good practice to push a test case that reproduces the bug. This avoids the fix to be reverted, and the bug to reappear, which is known as a regression.

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

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 test environment or a separate pre-production environment ("staging") should be built to be a scalable version of the production environment to alleviate costs while maintaining technology stack composition and nuances. Within these test environments, service virtualisation is commonly used to obtain on-demand access to dependencies (e.g., APIs, third-party applications, services, mainframes, etc.) that are beyond the team's control, still evolving, or too complex to configure in a virtual test lab.

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 can reduce the amount of work necessary to resolve them.

All programmers should start the day by updating the project from the repository. That way, they will all stay up to date.

It should be easy to find out whether the build breaks and, if so, who made the relevant change and what that change was.

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.^[18][19]

Continuous integration is intended to produce benefits such as:

• Integration bugs are detected early and are easy to track down due to small changesets. This saves both time and money over the lifespan of a project.
• Avoids last-minute chaos at release dates, when everyone tries to check in their slightly incompatible versions
• When unit tests fail or a bug emerges, if developers need to revert the codebase to a bug-free state without debugging, only a small number of changes are lost (because integration happens frequently)
• Constant availability of a "current" build for testing, demo, or release purposes
• Frequent code check-in pushes developers to create modular, less complex code^[20]

With continuous automated testing, benefits can include:

• Enforces discipline of frequent automated testing
• Immediate feedback on the system-wide impact of local changes
• Software metrics generated from automated testing and CI (such as metrics for code coverage, code complexity, and feature completeness) focus developers on developing functional, quality code, and help develop momentum in a team^{[citation needed]}

Some downsides of continuous integration can include:

• Constructing an automated test suite requires a considerable amount of work, including ongoing effort to cover new features and follow intentional code modifications.
  • Testing is considered a best practice for software development in its own right, regardless of whether or not continuous integration is employed, and automation is an integral part of project methodologies like test-driven development.
  • Continuous integration can be performed without any test suite, but the cost of quality assurance to produce a releasable product can be high if it must be done manually and frequently.
• There is some work involved to set up a build system, and it can become complex, making it difficult to modify flexibly.^[21]
  • However, there are a number of continuous integration software projects, both proprietary and open-source, which can be used.
• Continuous integration is not necessarily valuable if the scope of the project is small or contains untestable legacy code.
• Value added depends on the quality of tests and how testable the code really is.^[22]
• Larger teams mean that new code is constantly added to the integration queue, so tracking deliveries (while preserving quality) is difficult and builds queueing up can slow down everyone.^[22]
• With multiple commits and merges a day, partial code for a feature could easily be pushed and therefore integration tests will fail until the feature is complete.^[22]
• Safety and mission-critical development assurance (e.g., DO-178C, ISO 26262) require rigorous documentation and in-process review that are difficult to achieve using continuous integration. This type of life cycle often requires additional steps to be completed prior to product release when regulatory approval of the product is required.

• Application release automation
• Build light indicator
• Comparison of continuous integration software
• Continuous design
• Continuous testing
• Multi-stage continuous integration
• Rapid application development

• "Continuous Integration" (wiki) (a collegial discussion). C2. {{cite journal}}: Cite journal requires |journal= (help)
• Richardson, Jared. "Continuous Integration: The Cornerstone of a Great Shop" (introduction).
• Flowers, Jay. "A Recipe for Build Maintainability and Reusability". Archived from the original on 25 June 2020. Retrieved 28 May 2006.
• Duvall, Paul (4 December 2007). "Developer works". IBM.
• "Version lifecycle". MediaWiki. June 2024.