Escaping the Quicksand: A Call to Arms
Computing has been an astonishing success - but the accumulated technical debt exposes us all to huge costs in business and societal risk. For 75 years, we've built systems to prose specifications with test-and-debug development. That works well enough for industry to thrive, but it's an expensive and ineffective feedback loop, and leaves everyone relying on shaky foundations. Now, AI-enabled engineering is amplifying the success by reducing coding costs, but also amplifies the risks, by rapidly increasing technical debt, and by automating detection of the vulnerabilities therein. How can we do better? Research has long pursued mathematical proof of correctness, which, unlike testing, can...
| Authors | Peter Sewell, Jean Pichon-Pharabod |
|---|---|
| Primary category | cs.PL |
| Published | 20 August 2026 |
| Last updated at source | 20 August 2026 |
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.