As codebases grow and development cycles shrink, development and engineering teams are left buried under a mounting backlog of code errors and security alerts, slowing down release cycles. Perforce Klocwork and Perforce QAC bridge this gap by moving into automated resolution with AI-assisted code remediation, delivering context-aware fix recommendations based on deep static analysis.
Fill out the form to request a free trial of Klocwork and QAC with AI-assisted code remediation and see how quickly your team can turn findings into fixes.
Your Collaborative AI Coding Assistant
Enhance the power of Perforce Static Analysis with AI and shift left testing even earlier.
Remediation Has Become the New Development Bottleneck
Traditional workflows stall releases because they focus on identifying defects rather than fixing them, leaving teams to manually triage an overwhelming volume of alerts. This review process creates operational drag that delays deployment.
AI-Generated Code Creates More Issues to Resolve
AI coding assistants are powerful tools for increasing code output and speed, but they also expand the volume of code that needs to be reviewed. As a result, teams face more opportunities for security vulnerabilities, coding standard violations, and overall quality issues to slip through without proper oversight.
Developers Spend More Time Understanding Context
AI-generated code introduces patterns that static analysis flags but developers didn’t write themselves, making it harder and more time-consuming to assess the full context of the finding.
Release Pressure Leaves Little Room for Rework
Developer and engineering teams are expected to deliver faster while maintaining security posture — every code change requires confidence that remediation can solve the original issues without introducing new problems.
From Detection to Resolution in the Same Workflow
Perforce Static Analysis — Klocwork and QAC — doesn’t stop at surfacing vulnerabilities in your code. Our AI-assisted code remediation feature draws on deep, inter-procedural data to suggest fixes that reflect how your code actually behaves across the entire development and engineering chain.
The result is recommendations that are specific to your codebase, compliance standards, and the nature of each finding.
1. Write and Analyze
As you code, our tools run incremental analysis in the background — instantly surfacing coding errors, standards violations, and security vulnerabilities.
2. Receive Intelligent Fixes
Instead of spending hours researching a resolution, the integrated AI assistant analyzes each found defect using deep contextual data from QAC or Klocwork and suggests highly accurate, compliant code corrections that are grounded in a precise understanding of how your code actually behaves.
3. Review, Refine, Approve
Every fix requires explicit developer approval before it is applied. Use interactive chat features available in GitHub Copilot or other conversational assistants to fine-tune suggestions as needed. Human-in-the-loop oversight is built-in.
The Cost-Effective Solution to More Accurate Fixes with Less Manual Effort
By combining intelligent recommendations with deep analysis and automated remediation, engineering teams spend less time investigating findings and more time delivering software with Klocwork and QAC. This is most significant where cost of errors is highest — safety-critical systems, regulated industries, and high-velocity teams where quality gates aren’t optional.
When AI operates without code context, the average vulnerability resolution accuracy is only 20–30%, according to Carnegie Mellon University. Enriched with comprehensive static analysis data, the figure rises to between 72–90%.
- Generate fix suggestions using rich data flow and control flow analysis.
- Reduce time spent researching findings or revising inaccurate AI-generated fixes.
- Support fix applications with documentation and trace information.
Perforce Static Analysis delivers only the analysis data an AI model needs to generate an accurate fix. Targeted, relevant context allows teams to improve response quality while reducing token consumption.
- Focus AI-assisted remediation on specific findings and their behavioral contexts.
- Minimize unnecessary code exposure when working with private or self-hosted LLMs.
- Support faster, more cost-efficient AI-assisted remediation at enterprise scale.
In functional safety and security-critical development, every change carries regulatory weight. Perforce Static Analysis addresses that directly with human-in-the-loop workflows.
- Maintain human oversight to review, refine, or reject AI-generated recommendations — with full audit trail
- Automatically generate compliance-ready reports alongside each remediation.
- Alignment with compliance standards in regulated industries.
Klocwork and QAC integrate into the AI and development setup your organization already has. For teams operating in private or air-gapped environments, deployment stays entirely within your infrastructure.
- Integrates with any MCP-compatible host, including GitHub Copilot, delivered via the Perforce Static Analysis MCP server.
- Full support for private cloud, on-premises, or air-gapped environments.
Teams are managing larger codebases, increasing use of AI-generated code, and faster release cycles. Klocwork and QAC help teams keep remediation moving without increasing manual effort.
- AI-suggested fixes are generated immediately when a finding surfaces.
- Support shift-left development by resolving issues earlier in the software development lifecycle.
- Continuous quality coverage across both human-written and AI-generated code.
How AI-Assisted Code Remediation Works for You
Follow along with this interactive demo to see how the AI assistant fits into Perforce Static Analysis.
Don’t Take Our Word for It — Try for Yourself
You can prevent compliance backlogs and hidden security issues from stalling your pipeline by transitioning to an automated, context-aware remediation workflow. See how Klocwork and QAC turn complex static analysis data into actionable, safe code fixes that keep your engineering teams moving.