AI for Software Engineering
Code models, repository context, patch generation, test-driven agents and SWE benchmarks.
12concepts
101flashcards
87minutes of reading
- 01 Automated Program Repair and Fault Localisation How spectrum-based fault localisation ranks suspicious code from test coverage, why generate-and-validate repair overfits weak test suites, and how LLM pipelines such as Agentless rebuilt the same localise-repair-validate loop.
- 02 Measuring AI-Assisted Developer Productivity Why credible studies of the same tools report everything from a 19 percent slowdown to a 56 percent speedup, what each study design can and cannot establish, and how to read an effect size before repeating it.
- 03 The Verification Cost of Generated Code Generation got cheap and checking did not, so the net speedup of an AI-assisted change is governed by how much of the work was verification in the first place, which is why the same tool helps on a greenfield script and hurts in a mature repository.