Deep learning based vulnerability detection: Are we there yet?
Automated detection of software vulnerabilities is a fundamental problem in software
security. Existing program analysis techniques either suffer from high false positives or false …
security. Existing program analysis techniques either suffer from high false positives or false …
Automated program repair
Automated program repair Page 1 56 COMMUNICATIONS OF THE ACM | DECEMBER 2019
| VOL. 62 | NO. 12 review articles ALEX IS A software developer, a recent hire at the company …
| VOL. 62 | NO. 12 review articles ALEX IS A software developer, a recent hire at the company …
An empirical study on the effectiveness of static C code analyzers for vulnerability detection
Static code analysis is often used to scan source code for security vulnerabilities. Given the
wide range of existing solutions implementing different analysis techniques, it is very …
wide range of existing solutions implementing different analysis techniques, it is very …
D2a: A dataset built for ai-based vulnerability detection methods using differential analysis
Static analysis tools are widely used for vulnerability detection as they understand programs
with complex behavior and millions of lines of code. Despite their popularity, static analysis …
with complex behavior and millions of lines of code. Despite their popularity, static analysis …
Lessons from building static analysis tools at google
Lessons from building static analysis tools at Google Page 1 58 COMMUNICATIONS OF THE
ACM | APRIL 2018 | VOL. 61 | NO. 4 Lessons from Building Static Analysis Tools at Google …
ACM | APRIL 2018 | VOL. 61 | NO. 4 Lessons from Building Static Analysis Tools at Google …
What developers want and need from program analysis: an empirical study
Program Analysis has been a rich and fruitful field of research for many decades, and
countless high quality program analysis tools have been produced by academia. Though …
countless high quality program analysis tools have been produced by academia. Though …
Deeplinedp: Towards a deep learning approach for line-level defect prediction
C Pornprasit… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Defect prediction is proposed to assist practitioners effectively prioritize limited Software
Quality Assurance (SQA) resources on the most risky files that are likely to have post-release …
Quality Assurance (SQA) resources on the most risky files that are likely to have post-release …
On the" naturalness" of buggy code
Real software, the kind working programmers produce by the kLOC to solve real-world
problems, tends to be" natural", like speech or natural language; it tends to be highly …
problems, tends to be" natural", like speech or natural language; it tends to be highly …
Security in the software development lifecycle
We interviewed developers currently employed in industry to explore real-life software
security practices during each stage of the development lifecycle. This paper explores steps …
security practices during each stage of the development lifecycle. This paper explores steps …
'Think secure from the beginning' A Survey with Software Developers
Vulnerabilities persist despite existing software security initiatives and best practices. This
paper focuses on the human factors of software security, including human behaviour and …
paper focuses on the human factors of software security, including human behaviour and …