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"Carnegie Mellon University" } ], "person_or_org": { "family_name": "Yin", "given_name": "Pengcheng", "name": "Yin, Pengcheng", "type": "personal" } }, { "affiliations": [ { "name": "Carnegie Mellon University Software Engineering Institute" } ], "person_or_org": { "family_name": "Schwartz", "given_name": "Edward J.", "name": "Schwartz, Edward J.", "type": "personal" } }, { "affiliations": [ { "name": "Microsoft Research" } ], "person_or_org": { "family_name": "Allamanis", "given_name": "Miltiadis", "name": "Allamanis, Miltiadis", "type": "personal" } }, { "affiliations": [ { "name": "Carnegie Mellon University" } ], "person_or_org": { "family_name": "Le Goues", "given_name": "Claire", "name": "Le Goues, Claire", "type": "personal" } }, { "affiliations": [ { "name": "Carnegie Mellon University" } ], "person_or_org": { "family_name": "Neubig", "given_name": "Graham", "name": "Neubig, Graham", "type": "personal" } }, { "affiliations": [ { "name": "Carnegie Mellon University" } ], 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This dataset is released as a companion to the paper "DIRE: A Neural Approach to Decompiled Identifier Naming", appearing in the proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering (ASE 2019).
\n\nIt contains information generated by decompiling 3,195,962 functions found in 164,632 unique binaries generated from C code scraped from GitHub. For practicality, the dataset is partitioned into 16 archives by the first hexadecimal digit of the SHA-256 hash of the binary used to generate it. Each of the 16 archives contains approximately 10,000 JSONL files, named according to a binary's hash. Each JSONL file consists of a single JSON object per-line corresponding to a single function in the decompiled binary.
\n\nArchives are provided in both GZIP and BZIP2 format.
\n\nSee the README file for more information.
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