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{{User sandbox}}

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'''Code integrity''' is a measurement used in the software shippingdelivery lifecycle. It measures how high the [[source code]]'s quality is when it is passed on to the QA, and is affected by how extensively (or thoroughly GZ) the code was processed by correctness-checking processes (whether manual or automatic). Examples for such correctness-checking processes can be [[unit tests|unit testing]] and [[integration test]]ing, code review, test automation, AI-based code analysis etc.<ref>{{cite web |title=A Survey on Machine Learning Techniques for Source Code Analysis |url=https://arxiv.org/abs/2110.09610 |access-date=15 March 2023}}</ref> Code integrity is the combination of applying code correctness processes (software quality) along with metrics that measure the completeness of these correctness-checking processes, such as, for example, code coverage. While code integrity is usually achieved by unit testing the source code to reach high code coverage, it is definitely not the only way, or the best way, to achieve code integrity. In fact, code coverage, a popular metric to measure the thoroughness of unit tests, is known to have a limited correlation with the measure of real code integrity.<ref>{{cite web |title=How Effective Are Code Coverage Criteria? |url=https://ieeexplore.ieee.org/abstract/document/7272926 |access-date=15 March 2023}}</ref>

==Developer's confidence==

With code integrity, the developer can be sure that his/her code is written correctly when passed on to QA. Code integrity is not just about the correctness of the code, but also about developers’ confidence regarding correctness of their code. With code integrity, the developer can be sure that his/her code is written correctly when passed on to QA. This is, in fact, the expected quality level of the code. Code integrity helps developers and companies release better products, with fewer bugs, in a shorter time.<ref name="wim" />

==Shift-left testing and shift-left code integrity==

Companies who practice code integrity avoid the classic scenario where the development stage is delayed, delaying the QA stage, delaying the release stage. TheProducts product isof companies that do not adopt code integrity are released with more bugs (due to time pressure), users report tons of bugs back to the development team, and they start working on version 1.1 shortly after releasing version 1.0, just to fix bugs that could have been avoided.

Shift-left testing is a method to perform related testing during the initial processes of software development, since the QA department cannot measure the code's integrity even after all their tests are run. Shift-left testing and code integrity are tightly connected but integrity consists not only of the testing part of the job which is a sub -task of the larger process of shift-left code integrity. This process not only applies more unit tests along with higher code coverage, but also involves various other correctness-checking processes against relevant data.<ref>{{cite web |title=High Level Test Driven Development – Shift Left |url=https://link.springer.com/chapter/10.1007/978-3-319-18612-2_23 |access-date=15 March 2023}}</ref> Here are some examples:

* Unit testing of the code

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* Assigning a code integrity manager

;Examples forof correctness-checking completeness metrics:

* Pure code integrity metric formulation is: 1 − (Non-covered bugs) / (Total bugs), In words: the perfect code integrity minus the number of bugs that weren’t covered by unit testing, divided by the total bugs found during the entire product cycle including development, is the code not in integrity.

* Different types of code coverage (line-coverage, branch- coverage etc)

* Mutation testing

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* Confidence in your code's quality – Releasing products with high code integrity means more positive feedback from your customers.

* Makes the QA's work much more efficient – The QA concentrates on testing the system, without worrying about bugs that could have been easily found through proper unit testing.

==Shift-left code integrity enablement==

This concept is based on the fact that developers would be able to make full use of the technological advantage if they have the relevant testing tools available to them from the start. As newer software become more and more complex and includes more dependencies, including the right side of the [[V-model]] in developers' roles will help them to assume control of the unit testing & integration processes.<ref name="wim">{{cite web |author1=Gadi Zimerman |title=Tests are not enough – Why code integrity matters? |url=https://www.codium.ai/blog/tests-are-not-enough-why-code-integrity-matters |access-date=16 March 2023 |date=11 November 2022}}</ref><ref>{{cite journal |author1=Rook, Paul, E. Rook |title=Controlling software projects |journal=IEEE Software Engineering Journal |date=1986 |volume=1 |issue=1 |page=7-16 |url=https://digital-library.theiet.org/content/journals/10.1049/sej.1986.0003 |access-date=15 March 2023}}</ref> The result will allow developers to bring up complete environments in many software companies. This trend is expected to continue because in many cases it is impossible to perform unit/integration testing without the full system’s context.<ref>{{cite web |title=Effect of Using Continuous Integration (CI) and Continuous Delivery (CD) Deployment in DevOps to reduce the Gap between Developer and Operation |url=https://ieeexplore.ieee.org/abstract/document/9994139 |access-date=15 March 2023}}</ref>

==References==