Deep learning-based software engineering: progress, challenges, and opportunities
Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …
which in turn has substantially advanced other research disciplines, such as natural …
How effective are neural networks for fixing security vulnerabilities
Security vulnerability repair is a difficult task that is in dire need of automation. Two groups of
techniques have shown promise:(1) large code language models (LLMs) that have been pre …
techniques have shown promise:(1) large code language models (LLMs) that have been pre …
Vulnerabilities and Security Patches Detection in OSS: A Survey
R Lin, Y Fu, W Yi, J Yang, J Cao, Z Dong, F ** from the vulnerable code to the fixed …
APR4Vul: an empirical study of automatic program repair techniques on real-world Java vulnerabilities
Security vulnerability fixes could be a promising research avenue for Automated Program
Repair (APR) techniques. In recent years, APR tools have been thoroughly developed for …
Repair (APR) techniques. In recent years, APR tools have been thoroughly developed for …
Limits of machine learning for automatic vulnerability detection
Recent results of machine learning for automatic vulnerability detection have been very
promising indeed: Given only the source code of a function $ f $, models trained by machine …
promising indeed: Given only the source code of a function $ f $, models trained by machine …
TDD-Bench Verified: Can LLMs Generate Tests for Issues Before They Get Resolved?
Test-driven development (TDD) is the practice of writing tests first and coding later, and the
proponents of TDD expound its numerous benefits. For instance, given an issue on a source …
proponents of TDD expound its numerous benefits. For instance, given an issue on a source …