Refactoring programs to improve the performance of deep learning for vulnerability detection
Published in Iowa State University, ProQuest Dissertations & Theses Global, 2021
Recommended citation: Steenhoek, Benjamin. (2021). Refactoring programs to improve the performance of deep learning for vulnerability detection (Order No. 28648161). Available from Dissertations & Theses @ Iowa State University; ProQuest Dissertations & Theses Global. (2625295478). https://www.proquest.com/dissertations-theses/refactoring-programs-improve-performance-deep/docview/2625295478/se-2?accountid=10906
This paper is about refactoring programs as a method of data augmentation. Intuitively, when we refactor programs, we can produce a program that looks quite different syntactically because many tokens are changed, but is identical semantically because the behavior does not change. We applied this technique and found that it is a useful and general method for improving the performance of deep learning-based vulnerability detection.