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Static Code Analysis and Its Development Trend



Static Code Analysis and Its Development Trend

There are a lot of methodologies and tools that allow improving code quality. In this article, we will tell about one of those, namely static code analysis, and discuss the importance of regular analyzer runs while developing software, and also focus on modern trends in static code analysis.

What is Static Code Analysis?

Static code analysis is the process of finding errors and weaknesses in code without program launching. The analyzer can find problems of different kinds: buffer overflow, addressing uninitialized variables, copy-paste errors, etc.

Static Code Analysis Relevance

The time has passed, when just one programmer understood the entire working principle of a program and knew the whole project. Even if the project was quite big for those days, one person could remember the main details. Now it seems impossible to figure out the working process of a program considering current amount of code. For example, Linux version 1.0.0 (1994) had 176 250 lines of code.  The situation had changed over the years – Linux 5.0 has more than 26 million lines of code. You can hardly find a programmer who is able to keep track of all the modern project details and fully understand the connections between different code pieces. That is when the static code analyzers come to the rescue.

The analyzers can’t get tired and don’t have breaks: they are attentive and have wide knowledge about error patterns. They will help maintain the old project code and avoid many errors occurring because of a programmer being inattentive while coding. Finally, to find errors they use such technologies as data flow analysis, automatic method annotation, symbolic execution and so on regardless of persisting stereotype of widespread regular expressions use. That is what helps to find various and tricky errors. Many people think that static code analysis is based on regular expressions but it’s not true. At least for the modern analyzers. By the way, regular expressions fail to meet the challenge. The PVS-Studio analyzer, one of the class representatives, can illustrate how these technologies work and what they are necessary for.

By the way, everyone can contribute to the open source projects development using static code analyzers. You can check a project, find an error, make a patch and do that all over again as many times as you want. You can read more about it in the 'One good way to start contributing to open source - Static Analysersarticle. For the record, the above-mentioned PVS-Studio analyzer has free license for developers taking part in open projects development posted on GitHub or Bitbucket. The license is valid during a year, after expiration of which the license key can be renewed.

Modern Trends

Code analysis doesn’t stand still. Together with the AI development, the static code analyzers using deep learning begin to appear. DeepCode, the Swiss startup, developing system of automatic code review based on deep study is a good example of it. DeepCode can analyze Java, JavaScript and Python code. 'DeepCode can find errors, security issues, possible performance improvements, and also problems with code style', - said one of the analyzer’s creator in his interview.
However, you should understand that these claims are more like PR stunt and the urge to give another 'silver bullet' to the world. AI is definitely useful for finding errors but machine learning won’t solve all the problems. It will rather become one of those technologies used in static code analyzers to find defects.

Static code analyzers are becoming more popular as the projects scope grows. The static analysis software market is expected to reach $26 billion by 2024 comparing to $13 billion in 2019.

Available Static Code Analysis Tools

There are many static code analysis tools and even those that support such exotic languages as Opa. This Wikipedia article has a large list of existing analyzers. The softwaretestinghelp.com website made its own Top 40 static code analysis tools list briefly describing each of them so the reader could form their own opinion and choose the suitable one.

Conclusion

Static code analysis is one of the ways to make the software product better. The main thing is to learn how to use the analyzer properly, and do it regularly. It is also important to remember to combine it with other tools and methodologies. That’s when you can improve the code quality of a program. I recommend that you read a good article on the proper static code analysis use – 'Introduce Static Analysis in the Process, Don't Just Search for Bugs with It'.

Author: Ekaterina Nikiforova

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