Fitting Static Code Analysis into Continuous Integration

Continuous Integration

Continuous Integration or CI is one of the hottest topics in DevOps. Continuous integration is a software development practice in which members of a team incorporate their new code often, probably numerous times per day. Every integration kicks off automated build and test process for exposing any report status and defects as fast as possible.

CONTINOUS INTEGRATION A PERFECT COMPLEMENT TO DYNAMIC TESTING

Continuous integration is a perfect complement to dynamic testing since it:

  • Is more cost-effective when it comes to detecting bugs earlier in the lifecycle
  • Has the tendency to be more thorough in coverage
  • Needs less time to run

DEVELOPMENT ACCELERATION WITH CONTINUOUS STATIC CODE ANALYSIS

Development could be accelerated with continuous static code analysis. The adoption of agile methodologies, continuous integration and DevOps has taken the software development velocity to unprecedented levels. Continuous static code analysis is where extensive safety, security, reliability and performance checkers meet CI tools to offer fast feedback regarding the health of incremental check-ins across the software development team. This is made possible through the one-of-a-kind architecture static code analysis engine. It is designed to maximize performance and scalability for numerous concurrent analysis at a time.

STATIC CODE ANALYSIS, BRINGING A SUITE OF AUTOMATED CHECKS

Testing manually is out of the question to meet development velocity in which it counts, the same as automated testing forms wherein a person must spend time on research, creation and validation new tests before deployment. This is where static code analysis or SCA comes in. It brings in a suite of automated violations to compliance to industry standards gaps. The answer lies in the static code analysis engine itself. A lot of static code analysis tools, by their very nature, operate on holistic, huge code bases to make sure that their analysis takes into consideration as much components and execution paths as possible. This is the same as the old waterfall development method wherein testing only occurs after big code pieces have been integrated. Not a very good fit for fast release cycles and continuous integration. Changing engine itself to analyze just the modified code, instead of processing all code all the time, and running at check n brings agility to static code analysis and the process of testing. With SCA, developers get results of all automated checks in the shortest time possible, since the checks run only on their incremental code changes. It is truly the only way of testing through analysis to keep up.

HOW DOES SCA ENGINE WORK ACROSS NUMEROUS DEVELOPERS?

The answer again is to break up the problem. Through deployment of analysis to CI agents across machines, the workload is completely distributed and could work within the individual developer’s context. Also, it helps to scale up as more developers are added. The simplest method of doing this is integrating with current continuous integration systems, taking advantage of their architectures as well as making the set up easy for the development teams using them already.

THE RELEVANCE OF STATIC CODE ANALYSIS

For years, software code security and quality went from being ‘nice to have’ to a necessity. More and more organizations, including banks are making it mandatory to pass SCA test, security and penetration testing before deploying code in production. Static analysis tools are getting popular each and every day. Furthermore, more companies are making SCA mandatory for all new software development. SCA finds patterns, which are defined to them as rules, which could cause vulnerability of security or other issues with code quality, necessary for producing quality code. However, like any other technology SCA has its advantages and disadvantages, which also is the best way of judging any technology.

Code review, unit testing and static code analysis makes a nice combination, together with continuous integration.

THE BENEFITS OF STATIC CODE ANALYSIS

There are a lot of reasons to use SCA in a project. One is complete analysis of the code, without executing them. Static code analysis scans all code. If there are vulnerabilities in the corners of an app, which aren’t used even, then static analysis has a big probability of finding the vulnerabilities.

Another great thing about static code analysis is one could define project centric rules and they would be ensured to follow without manual intervention. If any member of the team forgets to follow the rules, they would be highlighted by SCA.

The third major benefit of SCA is that it could find bugs early on in the cycle of development. This means less cost of fixing them. All the benefits of a static code analyzer could be used only if they are part of the build process.

Nowadays, it is of the essence to use a static code analyzer. It is a very good tool for finding potential vulnerabilities in code.

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