In a recent survey report, Incredibuild asked 300 senior IT managers about their most used technologies and methodologies for accelerating and improving the development cycle.
More than three-quarters (76%) said they use static code analysis, and another 11% said they planned to implement it in the coming year. But not everyone has embraced automation just yet.
Software development teams are always looking for ways to increase both the speed of development processes and the reliability of their software. According to our 2024 State of Software Quality report, 58% of developers say not having enough time is the single most common challenge faced during code reviews. The best way to achieve both speed and reliability is to identify and fix code issues as early in the development process as possible.
Static code analysis can help you do just that.
What Is Static Code Analysis?
Static code analysis is a popular software development practice performed in the early “creation” stages of development. In this analysis process, developers examine the source code they’ve created before executing it.
Static code analysis is used to identify potential vulnerabilities, errors, and deviations from coding standards early in the development process. It also helps teams comply with coding guidelines like MISRA and industry standards like ISO 26262.
When implemented effectively, static code analysis and the early error detection it offers can help your development team achieve the following:
- Code consistency through enforcing coding standards and best practices that keep your codebase maintainable and readable.
- Stronger code security through catching potential vulnerabilities like SQL injection, buffer overflows, and XSS attacks.
- Cost savings by detecting and fixing issues early in development instead of addressing them in later stages or post-release, when fixes become more complex and issues may have already affected customers.
So, what’s the difference between code analysis and code review? In a typical code review process, developers manually read their code line-by-line to review it for potential issues. Code analysis uses automated tools to analyze your code against pre-written checks that identify issues for you.
Development teams also perform static code analysis to create an automated feedback loop within their team that helps catch code issues early. The earlier you identify coding errors, the easier and faster it will be to resolve them.
Automated tools that teams use to perform this type of code analysis are called static code analyzers or simply static code analysis tools. An example of a popular static code analyzer is a linter. This automated tool focuses on code style and formatting by checking your code against predefined rules, conventions, and best practices.
Code quality tools can integrate into text editors and integrated development environments (IDEs) to give developers real-time feedback and error detection as they write their code.
Static Analysis vs. Dynamic Analysis
Static and dynamic code analysis are both processes that help you detect defects in your code. The difference lies in what stage of the development cycle the analysis is performed.
Static analysis identifies issues before you run the program. The process occurs in a non-run-time environment, between the time you create the code and perform unit testing.
Dynamic analysis identifies issues after you run the program (during unit testing).
In this process, you test code while executing on a real or virtual processor. Dynamic analysis is especially effective for finding subtle defects and vulnerabilities because it looks at the code’s interaction with other databases, servers, and services.
However, dynamic analysis comes with some important caveats. For example, it will only find faults in the specific excerpt of the code being executed, not the entire codebase.
Both are essential processes. Static analysis ensures fewer defects during unit testing, and dynamic analysis catches issues your static analysis tools might have missed. To achieve the highest possible level of test coverage, combine the two methods.
How Static Code Analysis Works
The first step in the static code analysis process is source code input. Developers make their source code files or a specific codebase available to the static analysis tool they’re using.
A compiler then scans the source code. A compiler is a program that translates your source code from human-readable to machine code that’s computer-executable. The compiler breaks your code down into smaller pieces, known as tokens. If your source code is a book or short story, tokens are the words used to create it.
The next stage of the process is parsing. Parsers take the tokens, confirm that the tokens are sequenced in a way that makes sense according to the programming language you are using, and organize them into a structure called an abstract syntax tree (AST), which is an abstract representation of the code’s structure.
Now, your static analysis tool can start checking your code. Depending on which one you’re using, the tool performs analysis techniques, including:
- Syntax analysis that checks for syntax errors and coding style violations to ensure code consistency and readability.
- Data flow analysis that traces the flow of data within the code to find issues related to variable usage, uninitialized variables, and data dependencies to detect potential runtime errors.
- Control flow analysis that examines the program’s control flow paths to identify issues like dead code, unreachable code, and infinite loops to enhance code reliability and performance.
- Security vulnerability analysis that identifies vulnerabilities such as SQL injection, Cross-Site Scripting (XSS), and buffer overflows.
Suppose the tool identifies potential issues, like violations of coding standards or security vulnerabilities. In that case, the static code analyzer generates a report listing all the issues found and often provides other details, such as the suspected severity of the issue. Some static code analysis tools even offer suggested fixes for the found issues.
Benefits of Static Code Analysis
Static code analysis is one of the pillars of the “shift left testing movement,” which prioritizes pushing software testing into the earliest possible stages of development. When you’re performing source code analysis early and frequently, you can find and fix problems before they reach the product and they become more complicated and expensive to fix.
Early source code testing via static analysis helps your team achieve the following:
- Consistency by enforcing coding standards, patterns, and best practices.
- Enhanced security by finding security flaws early to decrease the risk of data breaches occurring.
- Improved efficiency by automating testing instead of having to perform manual code reviews.
- Better maintainability by fixing issues quickly and making your codebase less error-prone over time as it grows.
When you can create and ship code faster while maintaining consistency, quality, security, and maintainability, you can cut your development costs—and even increase revenue—which is the main benefit of having an efficient and effective static code analysis process.
According to a recent Consortium for Information and Software Quality report, software quality issues cost companies more than $2.08 trillion annually. The study also found that in a 25-year application lifecycle, companies spend nearly half of their money on identifying and fixing errors, making bug detection and correction a software company’s single greatest expense.
Static code analysis also helps companies avoid another huge expense—dealing with security breaches and their impact. The global average cost of a data breach in 2023 was $4.45 million, according to IBM’s most recent Cost of a Data Breach Report, an increase of 15% since 2020.
Static code analysis can also increase your team’s productivity, reducing the time and cost of development. Undo’s recent research report found that 26% of developer time is spent reproducing and fixing failing tests, adding that the total estimated value of salary spent on this work costs businesses $61 billion annually.
McKinsey’s 2020 report on developer velocity found that companies with faster and more efficient development cycles grow revenue four to five times faster than companies that don’t invest in increasing team productivity and speed.
Incredibuild’s 2022 survey report found that 21% of software leaders want access to better debugging tools to improve their day-to-day work and save development time.
Potential Limitations of Static Code Analysis
When you can catch and fix code issues early, you’re already on a great path toward improving code quality and the velocity of your development cycle. However, static code analysis is not a fool-proof solution that guarantees perfect code.
Static analysis cannot catch every issue all the time. Static analyzers typically don’t detect issues related to runtime behavior and external dependencies. They also may not understand domain-specific logic. Static code analyzers are also prone to producing false positives.
The quality of your analysis will depend on the thoroughness of the rules you set for each tool you’re using.
Best Practices for Effective Static Code Analysis
For best results, static code analysis should be used in conjunction with other testing techniques, such as:
- Dynamic testing after the code has been integrated to test code behavior during execution. Unit, functional, integration, performance, and penetration testing are all dynamic tests that can identify potential static code analysis missed.
- Manual code review in which software developers read through their source code and try to spot defects manually.
- Human testing techniques like usability and user acceptance testing that allow users to identify and report performance issues that your team might not have considered or experienced while creating certain features and functionalities.
To get the most out of using static analysis processes and tools, establish code quality standards internally and document coding standards for your project. Customize analysis coding rules to match project-specific requirements.
Integrate static analysis into your development workflow. Pick tools that work with your preferred IDE and continuous integration and deployment (CI/CD) pipeline.
Remember to regularly and routinely update and maintain static analysis tools and rule sets to improve the efficiency of your tools and the breadth of issue types they can identify.
Choosing the Right Static Code Analysis Tool
To get the most out of a static code analyzer, be sure to choose one that supports the programming language your team uses and the coding standards most relevant to your industry.
Codacy is a cutting-edge static analysis tool that supports most major coding languages and standards. It offers customizable code analysis, intelligent project quality evaluation, extensive feedback on your code, and easy integration into your existing workflow.
Give Codacy a spin today by signing up for a free trial.
