A Study of the Reliability of Agentic AI-Generated Programs
Agentic-AI based software development offers the promise of faster completion of the software, greater programmer efficiency, and more reliable code. The question is how can we verify these claims in an objective way? In this project, we attempted to answer this question based on three practices. First, we applied a typical best-practices agentic AI workflow for software development. Second, our target programs were ten well-known, release-quality human-written Linux utility programs so that we could compare the AI-generated code against a concrete ground truth. Third, we based our measure of reliability on a widely used testing technique, fuzz random testing. For this testing, we used bo...
| Authors | Ayesha Shafique, Barton P. MIller, Elisa R. Heymann |
|---|---|
| Primary category | cs.SE |
| Published | 16 September 2026 |
| Last updated at source | 23 September 2026 |
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