Enterprise AI Analysis
Automatically Engineering Trusted Software: A Research Roadmap
By YURIY BRUN, SAIKAT CHAKRABORTY, CLAIRE LE GOUES, CORINA PĂSĂREANU, ADISH SINGLA
Published: 02 March 2026
Executive Impact & Core Metrics
Recent advances in automated programming have the potential to reduce human involvement in the software engineering process, but this can lead to less trustworthy software. We envision a three-pronged approach to automating the engineering of trustworthy software that involves (1) eliciting requirements from users and automatically generating formal specifications encoding users' intent, (2) automatically synthesizing source code conforming to those specifications, and (3) automatically synthesizing formal proofs to verify the correctness of the produced software. We describe this vision and the state of the art in each of these three areas, and the research challenges that must be overcome in each area and in their integration.
0
PDF Downloads
0
Total Citations
0
Total Downloads
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
This section explores how AI advances are revolutionizing software engineering, specifically in making formal methods more accessible and effective for building trustworthy systems. From automated specification generation to proof synthesis, AI tools are bridging the gap between human intent and rigorous verification.
8x
Proof Length vs. Code Length in CompCert: A testament to the manual effort in traditional formal verification. AI aims to reduce this gap dramatically.
Enterprise Process Flow
Intent Prompting
→
Interactive Specification Synthesis
→
Automated Code Synthesis
→
Automated Verification Proof Synthesis
→
Feedback Loop for Refinement
| Aspect | Traditional Methods | AI-Assisted Methods |
|---|---|---|
| Cost & Effort |
|
|
| Scalability |
|
|
| Proof Generation |
|
|
| Specification Capture |
|
|
CompCert Verified C Compiler
The CompCert verified C compiler is deployed in Airbus aircraft control systems, providing mathematically-established security guarantees. It required roughly 100,000 lines of Rocq proofs to verify 42,000 lines of compiler code.
Key Takeaway: Formal verification, though costly, delivers critical reliability for mission-critical systems.
Advanced ROI Calculator
Estimate the potential savings and reclaimed hours for your enterprise by implementing AI-driven trusted software engineering.
Your Trusted AI Implementation Roadmap
A phased approach to integrate AI-driven trusted software into your enterprise, ensuring a smooth and secure transition.
Phase 1: Discovery & Strategy
Comprehensive assessment of current software development processes, identification of key pain points, and strategic planning for AI integration. Define clear, measurable goals and identify pilot projects for maximum impact.
Phase 2: Pilot Program & Integration
Implement AI-assisted tools for specification, code, and proof synthesis on selected pilot projects. Establish feedback loops, refine AI models, and train internal teams on new methodologies. Focus on measurable improvements and early wins.
Phase 3: Scaling & Optimization
Expand AI integration across the enterprise, continuously monitoring performance, refining processes, and optimizing for long-term trustworthiness and efficiency. Integrate AI-driven maintenance and evolution strategies.
Ready to Transform Your Software Development?
Our experts are ready to guide you through the journey of building trusted, AI-engineered software solutions, ensuring correctness and efficiency from day one.
Ready to Get Started?
Book Your Free Consultation.
Let's Discuss Your AI Strategy!
Lets Discuss Your Needs
Select a Date
Sun
Mon
Tue
Wed
Thu
Fri
Sat