2019 · Conference paper
DIRE: A Neural Approach to Decompiled Identifier Naming
Combines lexical and structural information from decompiler output to predict meaningful variable names, with a training and evaluation corpus derived from compiled C projects.
Scope and limitations
This is learned identifier naming, not complete source reconstruction or an autonomous agent. Its reported results concern an x86-64 C corpus and depend on decompiler output. The original author repository is deprecated and points to a successor.
Why it fits this collection
A foundational reference for the renaming step frequently delegated to reverse-engineering assistants.
Publication and review details
- Venue
- ASE 2019
- Status
- Conference paper
- Publication / posting date
- November 2019
- Date source
- Publisher-deposited Crossref print-publication month; the 11–15 November 2019 conference dates are not used to assert a publication day.
- First arXiv submission
- September 19, 2019
- arXiv
- 1909.09029
- Reviewed arXiv version
- v2
- DOI
- 10.1109/ASE.2019.00064
IEEE/ACM ASE 2019 proceedings, pages 628–639; the DOI resolves to IEEE Xplore document 8952404. The publisher-deposited and arXiv titles use 'Naming'; the ASE program and original code repository use the variant 'Renaming'. Both refer to this paper. Crossref lists 'Edward Schwartz'; the paper's own 'Edward J. Schwartz' is retained. Code URL is the verified original author artifact, explicitly deprecated.
Sources reviewed
Reviewed against the paper and its primary sources. Cite the original authors using the linked paper or BibTeX.
Discussed in the survey
Primary sources
- https://doi.org/10.1109/ASE.2019.00064
- https://api.crossref.org/works/10.1109/ASE.2019.00064
- https://arxiv.org/abs/1909.09029
- https://2019.ase-conferences.org/details/ase-2019-papers/49/DIRE-A-Neural-Approach-to-Decompiled-Identifier-Renaming
- https://github.com/pcyin/dire
- README.md GitHub · pcyin/dire · Revision e58c2ee
- https://github.com/CMUSTRUDEL/DIRTY