Understanding Static Code Analysis

Static code analysis is a method of debugging that involves reviewing source code prior to running a program. It is accomplished by comparing a set of code against one set or several sets of coding rules. Static code analysis is frequently done as part of software testing (also known as white-box testing) during the security development lifecycle's implementation phase (SDL).

What Is Static Code Analysis?

In many different development environments, static code analysis software is used to perform an automated standardization test. Code legibility is a common concern among developers. If a developer writes a chunk of code that is sent to a software tester, the code should be understandable and digestible. 

Static code analysis software can help software engineers maintain their code consistency while improving team cooperation by constantly testing new code against benchmark. In theory, static code analysis saves developer time while improving the quality of their debugging operations. Manual code analysis can often be inefficient and difficult to follow. Developers frequently don't discover bugs until after they've been deployed. Bugs can be found and alerted to developers decades before they emerge in a deployed application using static code analysis technologies. 

Benefits of Static Code Analysis

Bugs that don't show up for a long time after application deployment are all too common to software developers or engineers. Manual code analysis frequently relies on running the code and hoping that an error surfaces during quality assurance testing. Static code analysis software, on the other hand, allows developers to find and fix bugs that otherwise would be tucked away in the code, resulting in cleaner deployments and fewer issues down the road.

• To determine best practices, static code analysis software compares code to industry benchmarks. This standardized guideline guarantees that everyone's code is clear and optimized, ensuring that teams stay on track. Furthermore, some software allows users to adopt and tailor best practices to the specific demands of their company or department.
• Developers can spend more time working on new code and less time sifting through existing code since static code analysis software does automated scans. It finds and alerts users to problematic code automatically. This eliminates the need for software engineers to spend time and resources manually searching through lines of code.
• Static code analysis technologies can frequently detect and notify developers of security flaws in their code. It allows developers to prioritize security.

Limitations of Static Code Analysis 

False Positives

Some static code analysis tools might produce false positive results, indicating a potential vulnerability that is not present. This occurs because the tool cannot guarantee the integrity and security of data as it passes from input to output.

When analyzing an application that interacts with closed-source components or external systems, false positive findings may be produced because it is impossible to track the flow of data in the external system and thereby assure the integrity and confidentiality of the system without the source code.

False Negatives

Static code analysis techniques can potentially produce false negative results, in which vulnerabilities are discovered but not reported by the tool. This could happen if a new vulnerability in an external component is uncovered, or if the analysis tool has no knowledge of the runtime environment and how secure it is set.

Using Static Code Analysis as a Tool

Static code analysis, or source code analysis, employs tools to examine program code in search of application coding errors, back doors, or other malicious code that could allow hackers access to sensitive company data or customer data. In some circumstances, the analysis is carried out on a certain version of the source code, while in other cases, it is executed on a specific form of the object code. The tool scans source or sequence of instructions, evaluates the security and functionality of software while the program is not operating, which is typically early in the development lifecycle. 

The Case of Using Automated Tools for Static Analysis

For static analysis, automated technologies are used. Because static analysis tools are faster than manual reviews, they can evaluate programs much more frequently, in such a way that the tool operator does not need to have the same level of expertise as a human auditor. The automation takes care of everything. 

Just like a programmer can rely on a compiler to enforce finer language syntax points for code quality, an automated tool can similarly perform static analysis without hassling on the finer points or bugs. 

Furthermore, testing for faults such as security vulnerabilities is made more difficult by the fact that they usually occur in hard-to-reach regions or under unusual circumstances. Static analysis, which requires the program to be performed, can look into more of a program's dark areas with less effort. Before a program reaches the point where significant testing can be done, static analysis can be employed.

In a nutshell, static code analysis tools have an advantage in:

• The ability to find bugs faster is perhaps the most significant advantage of static analysis. The quicker you discover a bug, the simpler and less expensive, it is to fix. Developers can perform static analysis and get answers to a number of questions as soon as they finish even a small piece of the project's functionality. 
• Static analysis tools can provide thorough code analysis as developers work on their builds, providing insight into potential problems.
• With the exception of manual code reviews prone to human error, automated tools scan each line of code to recognize potential issues, allowing secure code to be in place before testing.

The cost range or pricing of static analysis tools can range from $15 to $250. For teams that require a range of solutions for better efficiency, there are some engineering analytics platforms to boost engineering teams’ performance and offer better visibility into dev workflow.