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Large language models (LLMs) have undergone rapid evolution and achieved remarkable results in recent times.
P. Black, “Sard: A software assurance reference dataset,” 1970
1970
Earlier work this paper cites.
R. S. Boyer, B. Elspas, and K. N. Levitt, “Select—a formal system for testing and debugging programs by symbolic execution,” ACM SigPlan Notices , vol. 10, no. 6, pp. 234–245, 1975
1975
Earlier work this paper cites.
J. C. King, “A new approach to program testing,” ACM Sigplan Notices , vol. 10, no. 6, pp. 228–233, 1975
1975
Earlier work this paper cites.
W. E. Howden, “Symbolic testing and the dissect symbolic evaluation system,” IEEE Transactions on Software Engineering , no. 4, pp. 266–278, 1977
1977
Earlier work this paper cites.
——, “Learning internal representations by error propagation,” California Univ San Diego La Jolla Inst for Cognitive Science, Tech. Rep., 1985
1985
Earlier work this paper cites.
D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” nature , vol. 323, no. 6088, pp. 533–536, 1986
1986
Earlier work this paper cites.
C. Ko, G. Fink, and K. Levitt, “Automated detection of vulnerabilities in privileged programs by execution monitoring,” in Tenth Annual Computer Security Applications Conference . IEEE, 1994, pp. 134–144
1994
Earlier work this paper cites.
M. I. Jordan, “Serial order: A parallel distributed processing approach,” in Advances in psychology . Elsevier, 1997, vol. 121, pp. 471–495
1997
Earlier work this paper cites.
S. Hochreiter and J. Schmidhuber, “Long short-term memory,” Neural computation , vol. 9, no. 8, pp. 1735–1780, 1997
1997
Earlier work this paper cites.
R. Kaksonen, M. Laakso, and A. Takanen, “Software security assessment through specification mutations and fault injection,” in Communications and Multimedia Security Issues of the New Century: IFIP TC6/TC11 Fifth Joint Working Conference on Communications and Multimedia Security (CMS’01) May 21–22, 2001, Darmstadt, Germany . Springer, 2001, pp. 173–183
2001
Earlier work this paper cites.
R. Collobert, S. Bengio, and J. Mariéthoz, “Torch: a modular machine learning software library,” Idiap, Tech. Rep., 2002
2002
Earlier work this paper cites.
The OpenSSL Project, “OpenSSL: The open source toolkit for SSL/TLS,” April 2003, www.openssl.org
2003
Earlier work this paper cites.
S. Sidiroglou and A. D. Keromytis, “Countering network worms through automatic patch generation,” IEEE Security & Privacy , vol. 3, no. 6, pp. 41–49, 2005
2005
Earlier work this paper cites.
M. Vuagnoux, “Autodafe: An act of software torture,” in Proceedings of the 22th Chaos Communication Congress , no. CONF. Chaos Computer Club, 2005, pp. 47–58
2005
Earlier work this paper cites.
C. Yagemann, M. Pruett, S. P. Chung, K. Bittick, B. Saltaformaggio, and W. Lee, “Arcus: Symbolic root cause analysis of exploits in production systems.” in USENIX Security Symposium , 2021, pp. 1989–2006
2006
Earlier work this paper cites.
H. J. Abdelnur, R. State, and O. Festor, “Kif: a stateful sip fuzzer,” in Proceedings of the 1st international Conference on Principles, Systems and Applications of IP Telecommunications , 2007, pp. 47–56
2007
Earlier work this paper cites.
D. L. Olson and D. Delen, Advanced data mining techniques . Springer Science & Business Media, 2008
2008
Earlier work this paper cites.
M. Musuvathi, S. Qadeer, T. Ball, G. Basler, P. A. Nainar, and I. Neamtiu, “Finding and reproducing heisenbugs in concurrent programs.” in OSDI , vol. 8, no. 2008, 2008
2008
Earlier work this paper cites.
C. Cadar, D. Dunbar, D. R. Engler et al. , “Klee: unassisted and automatic generation of high-coverage tests for complex systems programs.” in OSDI , vol. 8, 2008, pp. 209–224
2008
Earlier work this paper cites.
S. Anand, P. Godefroid, and N. Tillmann, “Demand-driven compositional symbolic execution,” in Tools and Algorithms for the Construction and Analysis of Systems: 14th International Conference, TACAS 2008, Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2008, Budapest, Hungary, March 29-April 6, 2008. Proceedings 14 . Springer, 2008, pp. 367–381
2008
Earlier work this paper cites.
J. Arnold and M. F. Kaashoek, “Ksplice: Automatic rebootless kernel updates,” in Proceedings of the 4th ACM European conference on Computer systems , 2009, pp. 187–198
2009
Earlier work this paper cites.
Y. Shi, Y. Zhang, T. Luo, X. Mao, Y. Cao, Z. Wang, Y. Zhao, Z. Huang, and M. Yang, “Backporting security patches of web applications: A prototype design and implementation on injection vulnerability patches,” in 31st USENIX Security Symposium (USENIX Security 22) , 2022, pp. 1993–2010
2010
Earlier work this paper cites.
V. Chipounov, V. Kuznetsov, and G. Candea, “S2e: A platform for in-vivo multi-path analysis of software systems,” Acm Sigplan Notices , vol. 46, no. 3, pp. 265–278, 2011
2011
Earlier work this paper cites.
K.-K. Ma, K. Yit Phang, J. S. Foster, and M. Hicks, “Directed symbolic execution,” in Static Analysis: 18th International Symposium, SAS 2011, Venice, Italy, September 14-16, 2011. Proceedings 18 . Springer, 2011, pp. 95–111
2011
Earlier work this paper cites.
M. Attariyan, M. Chow, and J. Flinn, “X-ray: Automating root-cause diagnosis of performance anomalies in production software,” in Presented as part of the 10th { \{ USENIX } \} Symposium on Operating Systems Design and Implementation ( { \{ OSDI } \} 12) , 2012, pp. 307–320
2012
Earlier work this paper cites.
R. R. Branco, G. N. Barbosa, and P. D. Neto, “Scientific but not academical overview of malware anti-debugging, anti-disassembly and anti-vm technologies,” Black Hat , vol. 1, no. 2012, pp. 1–27, 2012
2012
Earlier work this paper cites.
V. Kuznetsov, J. Kinder, S. Bucur, and G. Candea, “Efficient state merging in symbolic execution,” Acm Sigplan Notices , vol. 47, no. 6, pp. 193–204, 2012
2012
Earlier work this paper cites.
C. Mulliner, J. Oberheide, W. Robertson, and E. Kirda, “Patchdroid: Scalable third-party security patches for android devices,” in Proceedings of the 29th Annual Computer Security Applications Conference , 2013, pp. 259–268
2013
Earlier work this paper cites.
D. Kim, J. Nam, J. Song, and S. Kim, “Automatic patch generation learned from human-written patches,” in 2013 35th International Conference on Software Engineering (ICSE) . IEEE, 2013, pp. 802–811
2013
Earlier work this paper cites.
E. J. Schwartz, J. Lee, M. Woo, and D. Brumley, “Native x86 decompilation using semantics-preserving structural analysis and iterative control-flow structuring,” in Proceedings of the USENIX Security Symposium , vol. 16, 2013
2013
Earlier work this paper cites.
F. DeMarco, J. Xuan, D. Le Berre, and M. Monperrus, “Automatic repair of buggy if conditions and missing preconditions with smt,” in Proceedings of the 6th international workshop on constraints in software testing, verification, and analysis , 2014, pp. 30–39
2014
Earlier work this paper cites.
I. Ahmed, N. Mohan, and C. Jensen, “The impact of automatic crash reports on bug triaging and development in mozilla,” in Proceedings of The International Symposium on Open Collaboration , 2014, pp. 1–8
2014
Earlier work this paper cites.
F. Long and M. Rinard, “Staged program repair with condition synthesis,” in Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering , 2015, pp. 166–178
2015
Earlier work this paper cites.
M. Martinez and M. Monperrus, “Mining software repair models for reasoning on the search space of automated program fixing,” Empirical Software Engineering , vol. 20, pp. 176–205, 2015
2015
Earlier work this paper cites.
D. Schwartz-Narbonne, M. Schäf, D. Jovanović, P. Rümmer, and T. Wies, “Conflict-directed graph coverage,” in NASA Formal Methods: 7th International Symposium, NFM 2015, Pasadena, CA, USA, April 27-29, 2015, Proceedings 7 . Springer, 2015, pp. 327–342
2015
Earlier work this paper cites.
M. Martinez and M. Monperrus, “Astor: A program repair library for java,” in Proceedings of the 25th International Symposium on Software Testing and Analysis , 2016, pp. 441–444
2016
Earlier work this paper cites.
W. Cui, M. Peinado, S. K. Cha, Y. Fratantonio, and V. P. Kemerlis, “Retracer: Triaging crashes by reverse execution from partial memory dumps,” in Proceedings of the 38th International Conference on Software Engineering , 2016, pp. 820–831
2016
Earlier work this paper cites.
Y. Jiang, D. Wu, and P. Liu, “Jred: Program customization and bloatware mitigation based on static analysis,” in 2016 IEEE 40th annual computer software and applications conference (COMPSAC) , vol. 1. IEEE, 2016, pp. 12–21
2016
Earlier work this paper cites.
N. Stephens, J. Grosen, C. Salls, A. Dutcher, R. Wang, J. Corbetta, Y. Shoshitaishvili, C. Kruegel, and G. Vigna, “Driller: Augmenting fuzzing through selective symbolic execution.” in NDSS , vol. 16, no. 2016, 2016, pp. 1–16
2016
Earlier work this paper cites.
M. Abadi, “Tensorflow: learning functions at scale,” in Proceedings of the 21st ACM SIGPLAN International Conference on Functional Programming , 2016, pp. 1–1
2016
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” Advances in neural information processing systems , vol. 30, 2017
2017
Earlier work this paper cites.
P. F. Christiano, J. Leike, T. Brown, M. Martic, S. Legg, and D. Amodei, “Deep reinforcement learning from human preferences,” Advances in neural information processing systems , vol. 30, 2017
2017
Earlier work this paper cites.
D. Lin, J. Koppel, A. Chen, and A. Solar-Lezama, “Quixbugs: A multi-lingual program repair benchmark set based on the quixey challenge,” in Proceedings Companion of the 2017 ACM SIGPLAN international conference on systems, programming, languages, and applications: software for humanity , 2017, pp. 55–56
2017
Earlier work this paper cites.
S. Ma, F. Thung, D. Lo, C. Sun, and R. H. Deng, “Vurle: Automatic vulnerability detection and repair by learning from examples,” in Computer Security–ESORICS 2017: 22nd European Symposium on Research in Computer Security, Oslo, Norway, September 11-15, 2017, Proceedings, Part II 22 . Springer, 2017, pp. 229–246
2017
Earlier work this paper cites.
J. Xu, D. Mu, X. Xing, P. Liu, P. Chen, and B. Mao, “Postmortem program analysis with hardware-enhanced post-crash artifacts.” in USENIX Security Symposium , 2017, pp. 17–32
2017
Earlier work this paper cites.
V. Rastogi, D. Davidson, L. De Carli, S. Jha, and P. McDaniel, “Cimplifier: automatically debloating containers,” in Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering , 2017, pp. 476–486
2017
Earlier work this paper cites.
S. Rawat, V. Jain, A. Kumar, L. Cojocar, C. Giuffrida, and H. Bos, “Vuzzer: Application-aware evolutionary fuzzing.” in NDSS , vol. 17, 2017, pp. 1–14
2017
Earlier work this paper cites.
K. Serebryany, “Oss-fuzz-google’s continuous fuzzing service for open source software,” in USENIX Security symposium . USENIX Association, 2017
2017
Earlier work this paper cites.
A. Radford, K. Narasimhan, T. Salimans, I. Sutskever et al. , “Improving language understanding by generative pre-training,” 2018
2018
Earlier work this paper cites.
R. Russell, L. Kim, L. Hamilton, T. Lazovich, J. Harer, O. Ozdemir, P. Ellingwood, and M. McConley, “Automated vulnerability detection in source code using deep representation learning,” in 2018 17th IEEE international conference on machine learning and applications (ICMLA) . IEEE, 2018, pp. 757–762
2018
Earlier work this paper cites.
P. E. Black and P. E. Black, Juliet 1.3 test suite: Changes from 1.2 . US Department of Commerce, National Institute of Standards and Technology, 2018
2018
Earlier work this paper cites.
J. Hua, M. Zhang, K. Wang, and S. Khurshid, “Sketchfix: a tool for automated program repair approach using lazy candidate generation,” in Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering , 2018, pp. 888–891
2018
Cited alongside, same era.
M. Monperrus, “Automatic software repair: a bibliography,” ACM Computing Surveys (CSUR) , vol. 51, no. 1, pp. 1–24, 2018
2018
Cited alongside, same era.
E. Schulte, J. Ruchti, M. Noonan, D. Ciarletta, and A. Loginov, “Evolving exact decompilation,” in Workshop on Binary Analysis Research (BAR) , 2018
2018
Cited alongside, same era.
A. Quach, A. Prakash, and L. Yan, “Debloating software through piece-wise compilation and loading,” in 27th { \{ USENIX } \} Security Symposium ( { \{ USENIX } \} Security 18) , 2018, pp. 869–886
2018
Cited alongside, same era.
“Introducing chatgpt - open ai,” 2023. [Online]. Available: https://openai.com/blog/chatgpt
2023
Closest in time.
M. Aljanabi, M. Ghazi, A. H. Ali, S. A. Abed et al. , “Chatgpt: Open possibilities,” Iraqi Journal For Computer Science and Mathematics , vol. 4, no. 1, pp. 62–64, 2023
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
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K. Heo, W. Lee, P. Pashakhanloo, and M. Naik, “Effective program debloating via reinforcement learning,” in Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security , 2018, pp. 380–394
2018
Cited alongside, same era.
P. Chen and H. Chen, “Angora: Efficient fuzzing by principled search,” in 2018 IEEE Symposium on Security and Privacy (SP) . IEEE, 2018, pp. 711–725
2018
Cited alongside, same era.
H. Peng, Y. Shoshitaishvili, and M. Payer, “T-fuzz: fuzzing by program transformation,” in 2018 IEEE Symposium on Security and Privacy (SP) . IEEE, 2018, pp. 697–710
2018
Cited alongside, same era.
A. Radford, J. Wu, R. Child, D. Luan, D. Amodei, I. Sutskever et al. , “Language models are unsupervised multitask learners,” OpenAI blog , vol. 1, no. 8, p. 9, 2019
2019
Cited alongside, same era.
D. R. Jeong, K. Kim, B. Shivakumar, B. Lee, and I. Shin, “Razzer: Finding kernel race bugs through fuzzing,” in 2019 IEEE Symposium on Security and Privacy (SP) . IEEE, 2019, pp. 754–768
2019
Cited alongside, same era.
R. Duan, A. Bijlani, Y. Ji, O. Alrawi, Y. Xiong, M. Ike, B. Saltaformaggio, and W. Lee, “Automating patching of vulnerable open-source software versions in application binaries.” in NDSS , 2019
2019
Cited alongside, same era.
A. Ghanbari, S. Benton, and L. Zhang, “Practical program repair via bytecode mutation,” in Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis , 2019, pp. 19–30
2019
Cited alongside, same era.
K. Liu, A. Koyuncu, D. Kim, and T. F. Bissyandé, “Tbar: Revisiting template-based automated program repair,” in Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis , 2019, pp. 31–42
2019
Cited alongside, same era.
2023
Closest in time.
P. Maddigan and T. Susnjak, “Chat2vis: Generating data visualisations via natural language using chatgpt, codex and gpt-3 large language models,” IEEE Access , 2023
2023
Closest in time.
2023
Closest in time.
S. Biswas, “Role of chatgpt in gaming: According to chatgpt,” Available at SSRN 4375510 , 2023
2023
Closest in time.
2023
Closest in time.
M. Sallam, “Chatgpt utility in healthcare education, research, and practice: systematic review on the promising perspectives and valid concerns,” in Healthcare , vol. 11, no. 6. MDPI, 2023, p. 887
2023
Closest in time.
2023
Closest in time.
J. H. Choi, K. E. Hickman, A. Monahan, and D. Schwarcz, “Chatgpt goes to law school,” Available at SSRN , 2023
2023
Closest in time.
M. Ryznar, “Exams in the time of chatgpt,” Washington and Lee Law Review Online , vol. 80, no. 5, p. 305, 2023
2023
Closest in time.
P. M. Newton, “Chatgpt performance on mcq-based exams,” 2023
2023
Closest in time.
2023
Closest in time.
A. Borji, “A categorical archive of chatgpt failures,” arXiv preprint arXiv:2302.03494 , 2023
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
A. Cheshkov, P. Zadorozhny, and R. Levichev, “Evaluation of chatgpt model for vulnerability detection,” 2023
2023
Closest in time.
“Github copilot · your ai pair programmer,” https://copilot.github.com/ , 2023
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
Y. Feng, S. Vanam, M. Cherukupally, W. Zheng, M. Qiu, and H. Chen, “Investigating code generation performance of chat-gpt with crowdsourcing social data,” in Proceedings of the 47th IEEE Computer Software and Applications Conference , 2023, pp. 1–10
2023
Closest in time.
2023
Closest in time.
D. Baidoo-Anu and L. Owusu Ansah, “Education in the era of generative artificial intelligence (ai): Understanding the potential benefits of chatgpt in promoting teaching and learning,” Available at SSRN 4337484 , 2023
2023
Closest in time.
S. S. Biswas, “Potential use of chat gpt in global warming,” Annals of biomedical engineering , vol. 51, no. 6, pp. 1126–1127, 2023
2023
Closest in time.
C. S. Xia, Y. Wei, and L. Zhang, “Automated program repair in the era of large pre-trained language models,” in Proceedings of the 45th International Conference on Software Engineering (ICSE 2023). Association for Computing Machinery , 2023
2023
Closest in time.
2023
Closest in time.
M. Jin, S. Shahriar, M. Tufano, X. Shi, S. Lu, N. Sundaresan, and A. Svyatkovskiy, “Inferfix: End-to-end program repair with llms,” 2023
2023
Closest in time.
Y. Deng, C. S. Xia, C. Yang, S. D. Zhang, S. Yang, and L. Zhang, “Large language models are edge-case fuzzers: Testing deep learning libraries via fuzzgpt,” 2023
2023
Closest in time.
J. Hu, Q. Zhang, and H. Yin, “Augmenting greybox fuzzing with generative ai,” 2023
2023
Closest in time.
“CodeQL Documentation,” https://codeql.github.com/docs/ , 2023
2023
Closest in time.
“Infer static analyzer,” https://fbinfer.com/docs , 2023
2023
Closest in time.
“Clang static analyzer,” https://clang-analyzer.llvm.org/ , 2023
2023
Closest in time.
“CWE - Common Vulnerability Enumeration,” https://cwe.mitre.org/ , 2023
2023
Closest in time.
“Leetcode,” 2023. [Online]. Available: https://leetcode.com/
2023
Closest in time.
“Llvm commandline guide.” 2023. [Online]. Available: https://llvm.org/docs/CommandGuide/llvm-cov.html
2023
Closest in time.
“Sqlite,” 2023. [Online]. Available: https://www.sqlite.org/
2023
Closest in time.
“Eglibc,” 2023. [Online]. Available: http://www.eglibc.org/home
2023
Closest in time.
“Toybox,” 2023. [Online]. Available: https://landley.net/toybox
2023
Closest in time.
“Busybox,” 2023. [Online]. Available: https://busybox.net
2023
Closest in time.
“bzip2 - home,” 2023. [Online]. Available: https://sourceware.org/bzip2/
2023
Closest in time.
“american fuzzy lop,” 2023. [Online]. Available: https://lcamtuf.coredump.cx/afl/
2023
Closest in time.
“libfuzzer – a library for coverage-guided fuzz testing,” 2023. [Online]. Available: https://llvm.org/docs/LibFuzzer.html
2023
Closest in time.