What Is Continuous Integration?
The processes used by your team have a direct impact on the efficiency of your software development workflow. For that reason, it is important for your team to adopt processes that streamline your software development — like Continuous Integration (CI).
To help ensure that your CI process is efficient and effective, we explain what is Continuous Integration, how Continuous Integration works, and how to successfully implement Continuous Integration.
What Is Continuous Integration?
Continuous Integration (CI) is the practice of automating the build and testing of code every time a change is made — and committing that code back to a central repository.
One of the fundamental cornerstones of CI is that it encourages breaking up development tasks into small bite-sized pieces that can be performed frequently by every developer on the team.
Each new code commit triggers a consistent, automated build and test process — often called a “pipeline” — to report any defects found during compilation or testing as quickly as possible
CI is one of the key components of DevOps Automation.
What Are the Benefits of Continuous Integration?
By implementing CI, software development teams benefit by:
Making it Easier to Fix Bugs
Identifying issues sooner makes it easier for developers to fix errors, vulnerabilities, and defects in the code. What’s more, this helps to ensure that an issue will be fixed correctly, resulting in a build that’s issue free and working as quickly as possible.
Reducing Project Risk
Encouraging small, modular changes to the code enables new functionality to be backed out of a release more quickly, or even prevented from entering the main code stream altogether. This minimizes the impact on other developers.
Improving Software Quality
Maximizing the value of CI means detecting as many issues as possible in each integration build, through automation. This increases the breadth, depth, and repeatability of the tests while avoiding manual testing.
Automating these tasks frees up developers to focus on higher-value feature development.
What Is the Difference Between Continuous Integration (CI) and Continuous Delivery (CD)?
CI and CD are both software development practices.
CI is used during the build and test phase. CD is used once changes are committed. The ultimate aim of CD is to always have validated and verified code in the code repository — or version control system — ready for release.
How Continuous Integration Works
The nine steps of how Continuous Integration works:
1. Developers check code into the version control system’s staging repository.
2. The Version Control System (VCS)or code repository notifies the CI server that a commit has occurred. Or, the CI server polls the repository periodically looking for commits.
3. The CI server starts the build process on a build server.
4. The code containing the latest commit — ideally just the minimum file set — is checked out of the repository into a local workspace on the build server.
5. The changed code is built, analyzed, and tested.
6. Important results are reported back to the CI server, along with any important details and files that need to be retained.
7. The CI server sets the final — Pass / Fail — result of the build.
8. If the build met the success criteria, then the committed change may proceed through the development cycle - transferred to the real repository or merged to the main development stream. If the build failed, the committed changes are blocked from proceeding until those issues are resolved.
9. The CI server notifies any parties who have registered interest in the build. They can then log into the CI server to view the status plus any additional information.
Why Is Continuous Integration Important In Software Development?
CI accelerates software development to avoid these common pitfalls of development:
- Frequent code integration helps to eliminate code conflicts and code incompatibility
- Developers are encouraged to have the most up-to-date repository code when working
- Reduces the refactoring complexity
- Quality gates ensure only clean, working and tested code makes it to the repository
- Reduces repository commit bottlenecks
With a CI pipeline, every change is integrated, tested and verified which brings the commit closer to being a viable release candidate
How Does Static Analysis Extend Continuous Integration?
Static analysis is a natural addition to any CI development process and done correctly, adds the possibility for almost immediate feedback of new coding issues, specific to the branch or commit containing them. This provides the opportunity for quality gates to prevent those issues from ever entering the main codestream and needing to be resolved later — improving development efficiency.
Static analysis complements other verification and validation techniques, such as dynamic testing, because:
- Static analysis provides coverage of all possible execution paths, whereas for dynamic analysis error or fault conditions of the code that are typically very difficult, or even impossible, to induce at runtime.
- Static analysis is very cost-efficient in terms of detecting bugs earlier in the lifecycle — and it requires much less time to run.
- Issues detected with static analysis, prior to dynamic tests being written also saves downstream costs of reworking those dynamic tests, once the issues have been resolved — most dynamic tests are quite dependent on the code itself and so a change has an impact also on the tests.
The ideal static analysis engine for CI processes only modified code and affected execution paths, rather than processing the entire codebase all the time, and reports the impact of those changes.
Since static code analysis operates on source code and doesn’t have to actually execute the code, it can perform a complete analysis of the submitted code changes in a specific time frame. In addition, static code analysis doesn’t require specific test cases to be written.
To be effective in complementing CI, a static code analysis tool must be fast, scalable, and automated.
How Klocwork Complements CI
Klocwork for C, C++, C#, and Java integrates with build systems and CI environments along with its unique Differential Analysis technology provides the fastest analysis results for CI Pipelines. Learn more about how Klocwork can help.