Parasoft Logo

See Parasoft C/C++test in action!

Schedule a personalized demo.

Request a Demo

WEBINAR

Watch How to Enhance Software Quality With AI-Powered Static Analysis

Watch this video to discover how AI is transforming static analysis. Developers and managers can achieve unparalleled efficiency, precision, and compliance. See how Parasoft integrates machine learning and generative AI into its static analysis tools, revolutionizing how to identify, prioritize, and resolve C and C++ code quality issues

 

This webinar dives into how Parasoft is integrating Artificial Intelligence into the static analysis workflow. We’ll explore how AI can prioritize code violations, identify critical issues, and even suggest code fixes, making software development more efficient and accurate.

Whether you’re a developer seeking faster feedback loops or a manager aiming to optimize resources and meet deadlines without compromising quality, we’ll show you how to deliver secure, compliant, and reliable software faster than ever.

Key Takeaways

  • How AI/ML prioritizes and resolves critical code violations.
  • Accelerating compliance with industry standards.
  • Transforming manual code fixes into automated precision.
  • Achieving faster development cycles with reduced costs and greater confidence.

The Power of Static Analysis

Static analysis is all about checking your source code without actually running it. Think of it as an early warning system for your software. It helps catch problems like memory leaks, threading issues, and division by zero errors. These might sound small, but in safety-critical systems, they can have serious consequences. Static analysis also spots security vulnerabilities, like buffer overflows or weak cryptography. Plus, it can measure things like how easy your code is to maintain or how complex it is.

Years ago, teams would do manual code reviews, which took ages. Now, static analysis tools do this automatically. Parasoft’s engine uses pattern-based analysis to find known coding patterns that can cause unexpected behavior. It also uses data and control flow analysis, which is like simulating the code’s execution to find paths that might lead to bugs. If you’re not doing static analysis, you really should be. It helps find bugs earlier, when they’re cheapest to fix, leading to fewer defects in the field, higher quality code, and significant labor savings.

Adhering to Industry Coding Standards

There are many well-established coding standards out there, like MISRA, AUTOSAR, CWE, and OWASP. Standards like MISRA, which Parasoft contributes to, are developed by experienced professionals to define the best coding rules for safety and security. CWE, or Common Weakness Enumeration, isn’t a standard itself but a list of known software weaknesses that can lead to vulnerabilities. Many of these can be found using static analysis. Parasoft supports a wide range of these standards, including the full MISRA C 2025 and MISRA C++ 2023, and even lets you create your own custom rules.

AI for Prioritizing Code Violations

This is where things get really interesting. Parasoft is using machine learning to prioritize the coding violations found by static analysis. Here’s how it works:

  • Run Static Analysis: You integrate Parasoft’s static analysis into your CI/CD pipeline or IDE.
  • Export Violations: Identified violations are sent to a central reporting tool called DTP.
  • Train the Model: As you mark violations as fixed, suppressed, or reassigned in DTP, the machine learning model learns. You can train it manually over sprints, or if you’re an existing customer, use your historical data.
  • Prioritize Fixes: Once the model is trained enough, it can predict which violations are most critical and should be addressed first, assigning them a remediation value (e.g., 100%, 80%, 60%, 40%).

This helps teams focus their efforts on the most impactful issues, making the fixing process much more efficient.

Generative AI for Code Fixes

Parasoft is taking it a step further by integrating generative AI, specifically through a VS Code extension that uses GitHub Copilot. What makes Parasoft’s approach unique is how we ensure the AI-generated fixes are high quality and compliant:

  1. Rule Documentation: The AI is given detailed guidance from the compliance standard, so it understands the context and requirements for each rule.
  2. Chain-of-Thought Reasoning: The AI breaks down problems step-by-step, leading to more complete and robust fixes that align with best practices.

These elements mean the AI suggestions are more accurate, compliant with standards like MISRA and CWE, and can handle complex issues. This approach reduces labor, accelerates timelines, and allows developers to focus more on innovation.

A Real-World Example

Imagine you’re working in VS Code and find a “division by zero” violation. Instead of manually figuring out the fix, you can use the “Explain Violation” action. The VS Code C/C++test extension builds a prompt for Copilot, including the source code and rule documentation. Copilot then provides an explanation and even suggests a code fix. You can review it and apply it directly.

Another example is an SQL injection vulnerability. The AI can explain the risk and suggest using parameterized SQL queries, which is a much more secure and proper way to handle external data in queries than a simple validation check. This kind of intelligent suggestion, similar to what a senior developer might offer, significantly boosts productivity, especially for less experienced team members.

By using Parasoft’s AI-powered tools, teams can resolve complex coding issues faster, ensure compliance, and ultimately deliver higher quality, more secure software with greater confidence.