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ORCIDCorina S. Pasareanu
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- affiliation: Carnegie Mellon University, Pittsburgh, USA
- affiliation: NASA Ames Research Center, Mountain View, CA, USA
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2020 – today
- 2024
[j50]Amirfarhad Nilizadeh
, Gary T. Leavens, Corina S. Pasareanu, Yannic Noller:
JMLKelinci+: Detecting Semantic Bugs and Covering Branches with Valid Inputs Using Coverage-guided Fuzzing and Runtime Assertion Checking. Formal Aspects Comput. 36(1): 2:1-2:24 (2024)- [j49]Yoshiki Takashima, Chanhee Cho, Ruben Martins, Limin Jia, Corina S. Pasareanu:
Crabtree: Rust API Test Synthesis Guided by Coverage and Type. Proc. ACM Program. Lang. 8(OOPSLA2): 618-647 (2024) - [j48]Ismet Burak Kadron, Yannic Noller, Rohan Padhye, Tevfik Bultan, Corina S. Pasareanu, Koushik Sen:
Fuzzing, Symbolic Execution, and Expert Guidance for Better Testing. IEEE Softw. 41(1): 98-104 (2024) - [j47]Radu Calinescu, Calum Imrie, Ravi Mangal, Genaína Nunes Rodrigues, Corina S. Pasareanu, Misael Alpizar Santana, Gricel Vázquez:
Controller Synthesis for Autonomous Systems With Deep-Learning Perception Components. IEEE Trans. Software Eng. 50(6): 1374-1395 (2024) - [c138]Zichao Zhang, Limin Jia, Corina S. Pasareanu:
ProInspector: Uncovering Logical Bugs in Protocol Implementations. EuroS&P 2024: 617-632 - [c137]Amirfarhad Nilizadeh, Gary T. Leavens, Corina S. Pasareanu, Xuan-Bach Dinh Le, David R. Cok:
Does Going Beyond Branch Coverage Make Program Repair Tools More Reliable? ICST 2024: 281-292 - [c136]Eduard Pinconschi, Divya Gopinath, Rui Abreu, Corina S. Pasareanu:
Evaluating Deep Neural Networks in Deployment: A Comparative Study (Replicability Study). ISSTA 2024: 1300-1311 - [c135]Ravi Mangal, Nina Narodytska, Divya Gopinath, Boyue Caroline Hu, Anirban Roy, Susmit Jha, Corina S. Pasareanu:
Concept-Based Analysis of Neural Networks via Vision-Language Models. SAIV 2024: 49-77 - [i37]Dat Nguyen, Hieu M. Vu, Cong-Thanh Le, Bach Le, David Lo, Corina S. Pasareanu:
Inferring Properties of Graph Neural Networks. CoRR abs/2401.03790 (2024) - [i36]Ravi Mangal, Nina Narodytska, Divya Gopinath, Boyue Caroline Hu, Anirban Roy, Susmit Jha, Corina S. Pasareanu:
Concept-based Analysis of Neural Networks via Vision-Language Models. CoRR abs/2403.19837 (2024) - [i35]Eduard Pinconschi, Divya Gopinath, Rui Abreu, Corina S. Pasareanu:
Evaluating Deep Neural Networks in Deployment (A Comparative and Replicability Study). CoRR abs/2407.08730 (2024) - [i34]Nils Palumbo, Ravi Mangal, Zifan Wang, Saranya Vijayakumar, Corina S. Pasareanu, Somesh Jha:
Mechanistically Interpreting a Transformer-based 2-SAT Solver: An Axiomatic Approach. CoRR abs/2407.13594 (2024) - 2023
- [j46]Marieke Huisman, Corina S. Pasareanu, Naijun Zhan:
Introduction to the Special Section on FM 2021. Formal Aspects Comput. 35(2): 6:1-6:2 (2023) - [j45]Elena Sherman, Yannic Noller, Cyrille Artho, Franck van Breugel, Anto Nanah Ji, John Kellerman, Parssa Khazra, Filip Kliber, Gaurang Kudale, Pavel Parízek, Corina S. Pasareanu, Ron Pressler, Matt Walker, Hongru Wang, Qiuchen Yan:
The Java Pathfinder Workshop 2022. ACM SIGSOFT Softw. Eng. Notes 48(1): 19-21 (2023) - [j44]Muhammad Usman, Youcheng Sun, Divya Gopinath, Rishi Dange, Luca Manolache, Corina S. Pasareanu:
An overview of structural coverage metrics for testing neural networks. Int. J. Softw. Tools Technol. Transf. 25(3): 393-405 (2023) - [c134]Eduard Pinconschi, Sofia Reis, Chi Zhang, Rui Abreu, Hakan Erdogmus, Corina S. Pasareanu, Limin Jia:
Tenet: A Flexible Framework for Machine-Learning-based Vulnerability Detection. CAIN 2023: 102-103 - [c133]Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Sinem Getir Yaman, Calum Imrie, Radu Calinescu, Huafeng Yu:
Closed-Loop Analysis of Vision-Based Autonomous Systems: A Case Study. CAV (1) 2023: 289-303 - [c132]Sofia Reis, Rui Abreu, Corina S. Pasareanu:
Are security commit messages informative? Not enough! EASE 2023: 196-199 - [c131]Divya Gopinath, Luca Lungeanu, Ravi Mangal, Corina S. Pasareanu, Siqi Xie, Huafeng Yu:
Feature-Guided Analysis of Neural Networks. FASE 2023: 133-142 - [c130]Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina S. Pasareanu, Matt Fredrikson:
On the Perils of Cascading Robust Classifiers. ICLR 2023 - [c129]Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Huafeng Yu:
Assumption Generation for Learning-Enabled Autonomous Systems. RV 2023: 3-22 - [c128]Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett:
Toward Certified Robustness Against Real-World Distribution Shifts. SaTML 2023: 537-553 - [c127]Muhammad Usman, Youcheng Sun, Divya Gopinath, Corina S. Pasareanu:
Rule-Based Testing of Neural Networks. SE4SafeML@SIGSOFT FSE 2023: 1-5 - [i33]Sofia Reis, Corina S. Pasareanu, Rui Abreu, Hakan Erdogmus:
SECOMlint: A linter for Security Commit Messages. CoRR abs/2301.06959 (2023) - [i32]Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Sinem Getir Yaman, Calum Imrie, Radu Calinescu, Huafeng Yu:
Closed-loop Analysis of Vision-based Autonomous Systems: A Case Study. CoRR abs/2302.04634 (2023) - [i31]Corina S. Pasareanu, Ravi Mangal, Divya Gopinath, Huafeng Yu:
Assumption Generation for the Verification of Learning-Enabled Autonomous Systems. CoRR abs/2305.18372 (2023) - [i30]Ravi Mangal, Klas Leino, Zifan Wang, Kai Hu, Weicheng Yu, Corina S. Pasareanu, Anupam Datta, Matt Fredrikson:
Is Certifying 𝓁p Robustness Still Worthwhile? CoRR abs/2310.09361 (2023) - [i29]Chi Zhang, Zifan Wang, Ravi Mangal, Matt Fredrikson, Limin Jia, Corina S. Pasareanu:
Transfer Attacks and Defenses for Large Language Models on Coding Tasks. CoRR abs/2311.13445 (2023) - 2022
- [j43]Marieke Huisman, Corina S. Pasareanu, Naijun Zhan:
Preface for the formal methods in system design special issue on 'Formal Methods 2021'. Formal Methods Syst. Des. 61(1): 1-2 (2022) - [j42]Hadar Frenkel, Orna Grumberg, Corina S. Pasareanu, Sarai Sheinvald:
Assume, guarantee or repair: a regular framework for non regular properties. Int. J. Softw. Tools Technol. Transf. 24(5): 667-689 (2022) - [j41]Corina S. Pasareanu, Andreas Zeller:
IEEE International Conference on Software Testing, Verification and Validation (ICST 2020). Softw. Test. Verification Reliab. 32(5) (2022) - [j40]Klas Leino, Chi Zhang, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu:
Degradation Attacks on Certifiably Robust Neural Networks. Trans. Mach. Learn. Res. 2022 (2022) - [c126]Youcheng Sun, Muhammad Usman, Divya Gopinath, Corina S. Pasareanu:
VPN: Verification of Poisoning in Neural Networks. NSV/FoMLAS@CAV 2022: 3-14 - [c125]Ravi Mangal, Corina S. Pasareanu:
A Cascade of Checkers for Run-time Certification of Local Robustness. NSV/FoMLAS@CAV 2022: 15-28 - [c124]Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu:
Self-correcting Neural Networks for Safe Classification. NSV/FoMLAS@CAV 2022: 96-130 - [c123]Hong Jin Kang, Truong Giang Nguyen, Xuan-Bach Dinh Le, Corina S. Pasareanu, David Lo:
Test mimicry to assess the exploitability of library vulnerabilities. ISSTA 2022: 276-288 - [c122]Sofia Reis, Rui Abreu, Hakan Erdogmus, Corina S. Pasareanu:
SECOM: Towards a convention for security commit messages. MSR 2022: 764-765 - [c121]Muhammad Usman, Divya Gopinath, Youcheng Sun, Corina S. Pasareanu:
Rule-Based Runtime Mitigation Against Poison Attacks on Neural Networks. RV 2022: 67-84 - [e14]Helmut Seidl, Zhiming Liu, Corina S. Pasareanu:
Theoretical Aspects of Computing - ICTAC 2022 - 19th International Colloquium, Tbilisi, Georgia, September 27-29, 2022, Proceedings. Lecture Notes in Computer Science 13572, Springer 2022, ISBN 978-3-031-17714-9 [contents] - [i28]Muhammad Usman, Youcheng Sun, Divya Gopinath, Corina S. Pasareanu:
AntidoteRT: Run-time Detection and Correction of Poison Attacks on Neural Networks. CoRR abs/2202.01179 (2022) - [i27]Radu Calinescu, Calum Imrie, Ravi Mangal, Corina S. Pasareanu, Misael Alpizar Santana, Gricel Vázquez:
Discrete-Event Controller Synthesis for Autonomous Systems with Deep-Learning Perception Components. CoRR abs/2202.03360 (2022) - [i26]Youcheng Sun, Muhammad Usman, Divya Gopinath, Corina S. Pasareanu:
VPN: Verification of Poisoning in Neural Networks. CoRR abs/2205.03894 (2022) - [i25]Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina S. Pasareanu, Matt Fredrikson:
On the Perils of Cascading Robust Classifiers. CoRR abs/2206.00278 (2022) - [i24]Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett:
Toward Certified Robustness Against Real-World Distribution Shifts. CoRR abs/2206.03669 (2022) - [i23]Hadar Frenkel, Orna Grumberg, Corina S. Pasareanu, Sarai Sheinvald:
Assume, Guarantee or Repair - A Regular Framework for Non Regular Properties (full version). CoRR abs/2207.10534 (2022) - [i22]Muhammad Usman, Youcheng Sun, Divya Gopinath, Rishi Dange, Luca Manolache, Corina S. Pasareanu:
An Overview of Structural Coverage Metrics for Testing Neural Networks. CoRR abs/2208.03407 (2022) - [i21]Hong Jin Kang, Pattarakrit Rattanukul, Stefanus Agus Haryono, Truong Giang Nguyen, Chaiyong Ragkhitwetsagul, Corina S. Pasareanu, David Lo:
SkipFuzz: Active Learning-based Input Selection for Fuzzing Deep Learning Libraries. CoRR abs/2212.04038 (2022) - 2021
- [c120]Muhammad Usman, Divya Gopinath, Youcheng Sun, Yannic Noller, Corina S. Pasareanu:
NNrepair: Constraint-Based Repair of Neural Network Classifiers. CAV (1) 2021: 3-25 - [c119]Zichao Zhang, Arthur Azevedo de Amorim, Limin Jia, Corina S. Pasareanu:
Learning Assumptions for Verifying Cryptographic Protocols Compositionally. FACS 2021: 3-23 - [c118]Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu:
Fast Geometric Projections for Local Robustness Certification. ICLR 2021 - [c117]Muhammad Usman, Yannic Noller, Corina S. Pasareanu, Youcheng Sun, Divya Gopinath:
NEUROSPF: A Tool for the Symbolic Analysis of Neural Networks. ICSE (Companion Volume) 2021: 25-28 - [c116]Amirfarhad Nilizadeh, Gary T. Leavens, Xuan-Bach Dinh Le, Corina S. Pasareanu, David R. Cok:
Exploring True Test Overfitting in Dynamic Automated Program Repair using Formal Methods. ICST 2021: 229-240 - [c115]Yoshiki Takashima, Ruben Martins, Limin Jia, Corina S. Pasareanu:
SyRust: automatic testing of Rust libraries with semantic-aware program synthesis. PLDI 2021: 899-913 - [c114]Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark W. Barrett:
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers. SAFECOMP 2021: 3-17 - [c113]Amirfarhad Nilizadeh, Gary T. Leavens, Corina S. Pasareanu:
Using a Guided Fuzzer and Preconditions to Achieve Branch Coverage with Valid Inputs. TAP@STAF 2021: 72-84 - [c112]Ismet Burak Kadron, Divya Gopinath, Corina S. Pasareanu, Huafeng Yu:
Case Study: Analysis of Autonomous Center Line Tracking Neural Networks. VSTTE 2021: 104-121 - [c111]Muhammad Usman, Divya Gopinath, Corina S. Pasareanu:
QuantifyML: How Good is my Machine Learning Model? FMAS 2021: 92-100 - [e13]Marieke Huisman, Corina S. Pasareanu, Naijun Zhan:
Formal Methods - 24th International Symposium, FM 2021, Virtual Event, November 20-26, 2021, Proceedings. Lecture Notes in Computer Science 13047, Springer 2021, ISBN 978-3-030-90869-0 [contents] - [e12]Radu Calinescu, Corina S. Pasareanu:
Software Engineering and Formal Methods - 19th International Conference, SEFM 2021, Virtual Event, December 6-10, 2021, Proceedings. Lecture Notes in Computer Science 13085, Springer 2021, ISBN 978-3-030-92123-1 [contents] - [i20]Muhammad Usman, Yannic Noller, Corina S. Pasareanu, Youcheng Sun, Divya Gopinath:
NEUROSPF: A tool for the Symbolic Analysis of Neural Networks. CoRR abs/2103.00124 (2021) - [i19]Colin Paterson, Haoze Wu, John Grese, Radu Calinescu, Corina S. Pasareanu, Clark W. Barrett:
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers. CoRR abs/2103.01629 (2021) - [i18]Muhammad Usman, Divya Gopinath, Youcheng Sun, Yannic Noller, Corina S. Pasareanu:
NNrepair: Constraint-based Repair of Neural Network Classifiers. CoRR abs/2103.12535 (2021) - [i17]David Coimbra, Sofia Reis, Rui Abreu, Corina S. Pasareanu, Hakan Erdogmus:
On using distributed representations of source code for the detection of C security vulnerabilities. CoRR abs/2106.01367 (2021) - [i16]Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu:
Self-Repairing Neural Networks: Provable Safety for Deep Networks via Dynamic Repair. CoRR abs/2107.11445 (2021) - 2020
- [b1]Corina S. Pasareanu:
Symbolic Execution and Quantitative Reasoning: Applications to Software Safety and Security. Synthesis Lectures on Software Engineering, Morgan & Claypool Publishers 2020, ISBN 978-3-031-01423-9 - [j39]Cyrille Artho, Quoc-Sang Phan, Peter Aldous, Alyas Almaawi, Lucas Bang, Lasse Berglund, Tevfik Bultan, Zhenbang Chen, Hayes Converse, Wei Dong, William Eiers, Milos Gligoric, Simon Goldsmith, Lars Grunske, Joshua Hooker, Ismet Burak Kadron, Timo Kehrer, Sarfraz Khurshid, Xuan-Bach Dinh Le, David Lo, Eric Mercer, Sasa Misailovic, Egor Namakonov, Hoang Lam Nguyen, Yannic Noller, Benjamin Ogles, Rohan Padhye, Pavel Parízek, Corina S. Pasareanu, Sheridan Jacob Powell, Seemanta Saha, Koushik Sen, Elena Sherman, Kyle Storey, Minxing Tang, Willem Visser, Ji Wang, Hengbiao Yu:
The Java Pathfinder Workshop 2019. ACM SIGSOFT Softw. Eng. Notes 45(2): 20-22 (2020) - [j38]Kasper Søe Luckow, Rody Kersten, Corina S. Pasareanu:
Complexity vulnerability analysis using symbolic execution. Softw. Test. Verification Reliab. 30(7-8) (2020) - [c110]Edward Kim, Divya Gopinath, Corina S. Pasareanu, Sanjit A. Seshia:
A Programmatic and Semantic Approach to Explaining and Debugging Neural Network Based Object Detectors. CVPR 2020: 11125-11134 - [c109]Zichao Zhang, Arthur Azevedo de Amorim, Limin Jia, Corina S. Pasareanu:
Automating Compositional Analysis of Authentication Protocols. FMCAD 2020: 113-118 - [c108]Haoze Wu, Alex Ozdemir, Aleksandar Zeljic, Kyle Julian, Ahmed Irfan, Divya Gopinath, Sadjad Fouladi, Guy Katz, Corina S. Pasareanu, Clark W. Barrett:
Parallelization Techniques for Verifying Neural Networks. FMCAD 2020: 128-137 - [c107]Corina S. Pasareanu, Hayes Converse, Antonio Filieri, Divya Gopinath:
On the probabilistic analysis of neural networks. SEAMS@ICSE 2020: 5-8 - [c106]Yannic Noller, Corina S. Pasareanu, Marcel Böhme, Youcheng Sun, Hoang Lam Nguyen, Lars Grunske:
HyDiff: hybrid differential software analysis. ICSE 2020: 1273-1285 - [c105]Hayes Converse, Antonio Filieri, Divya Gopinath, Corina S. Pasareanu:
Probabilistic Symbolic Analysis of Neural Networks. ISSRE 2020: 148-159 - [c104]Shirin Nilizadeh, Yannic Noller, Corina S. Pasareanu:
DifFuzz: Differential Fuzzing for Side-Channel Analysis. SE 2020: 125-126 - [c103]Corina S. Pasareanu:
SafeDNN: understanding and verifying neural networks (keynote). A-TEST@ESEC/SIGSOFT FSE 2020: 1 - [c102]Hadar Frenkel, Orna Grumberg, Corina S. Pasareanu, Sarai Sheinvald:
Assume, Guarantee or Repair. TACAS (1) 2020: 211-227 - [e11]Sarfraz Khurshid, Corina S. Pasareanu:
ISSTA '20: 29th ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, USA, July 18-22, 2020. ACM 2020, ISBN 978-1-4503-8008-9 [contents] - [i15]Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu:
Fast Geometric Projections for Local Robustness Certification. CoRR abs/2002.04742 (2020) - [i14]Haoze Wu, Alex Ozdemir, Aleksandar Zeljic, Ahmed Irfan, Kyle Julian, Divya Gopinath, Sadjad Fouladi, Guy Katz, Corina S. Pasareanu, Clark W. Barrett:
Parallelization Techniques for Verifying Neural Networks. CoRR abs/2004.08440 (2020)
2010 – 2019
- 2019
- [j37]Corina S. Pasareanu, Rody Kersten, Kasper Søe Luckow, Quoc-Sang Phan:
Chapter Six - Symbolic Execution and Recent Applications to Worst-Case Execution, Load Testing, and Security Analysis. Adv. Comput. 113: 289-314 (2019) - [j36]Guowei Yang, Rui Qiu, Sarfraz Khurshid, Corina S. Pasareanu, Junye Wen:
A synergistic approach to improving symbolic execution using test ranges. Innov. Syst. Softw. Eng. 15(3-4): 325-342 (2019) - [j35]Xuan-Bach Dinh Le, Corina S. Pasareanu, Rohan Padhye, David Lo, Willem Visser, Koushik Sen:
Saffron: Adaptive Grammar-based Fuzzing for Worst-Case Analysis. ACM SIGSOFT Softw. Eng. Notes 44(4): 14 (2019) - [c101]Shirin Nilizadeh, Yannic Noller, Corina S. Pasareanu:
DifFuzz: differential fuzzing for side-channel analysis. ICSE 2019: 176-187 - [c100]Divya Gopinath, Corina S. Pasareanu, Kaiyuan Wang, Mengshi Zhang, Sarfraz Khurshid:
Symbolic execution for attribution and attack synthesis in neural networks. ICSE (Companion Volume) 2019: 282-283 - [c99]Xuan-Bach Dinh Le, Lingfeng Bao, David Lo, Xin Xia, Shanping Li, Corina S. Pasareanu:
On reliability of patch correctness assessment. ICSE 2019: 524-535 - [c98]Divya Gopinath, Mengshi Zhang, Kaiyuan Wang, Ismet Burak Kadron, Corina S. Pasareanu, Sarfraz Khurshid:
Symbolic Execution for Importance Analysis and Adversarial Generation in Neural Networks. ISSRE 2019: 313-322 - [c97]Divya Gopinath, Hayes Converse, Corina S. Pasareanu, Ankur Taly:
Property Inference for Deep Neural Networks. ASE 2019: 797-809 - [c96]Yannic Noller, Rody Kersten, Corina S. Pasareanu:
Badger: Complexity Analysis with Fuzzing and Symbolic Execution. SE/SWM 2019: 65-66 - [c95]Yannic Noller, Corina S. Pasareanu, Aymeric Fromherz, Xuan-Bach Dinh Le, Willem Visser:
Symbolic Pathfinder for SV-COMP - (Competition Contribution). TACAS (3) 2019: 239-243 - [i13]Divya Gopinath, Ankur Taly, Hayes Converse, Corina S. Pasareanu:
Finding Invariants in Deep Neural Networks. CoRR abs/1904.13215 (2019) - [i12]Edward Kim, Divya Gopinath, Corina S. Pasareanu, Sanjit A. Seshia:
A Programmatic and Semantic Approach to Explaining and DebuggingNeural Network Based Object Detectors. CoRR abs/1912.00289 (2019) - 2018
- [j34]Karam Abd Elkader, Orna Grumberg, Corina S. Pasareanu, Sharon Shoham:
Automated circular assume-guarantee reasoning. Formal Aspects Comput. 30(5): 571-595 (2018) - [c94]Divya Gopinath, Guy Katz, Corina S. Pasareanu, Clark W. Barrett:
DeepSafe: A Data-Driven Approach for Assessing Robustness of Neural Networks. ATVA 2018: 3-19 - [c93]Pasquale Malacaria, M. H. R. Khouzani, Corina S. Pasareanu, Quoc-Sang Phan, Kasper Søe Luckow:
Symbolic Side-Channel Analysis for Probabilistic Programs. CSF 2018: 313-327 - [c92]Andrew Hill, Corina S. Pasareanu, Kathryn T. Stolee:
Automated program repair with canonical constraints. ICSE (Companion Volume) 2018: 339-341 - [c91]Sarfraz Khurshid, Corina S. Pasareanu, Willem Visser:
Test input generation with Java PathFinder: then and now (invited talk abstract). ISSTA 2018: 1-2 - [c90]Tegan Brennan, Seemanta Saha, Tevfik Bultan, Corina S. Pasareanu:
Symbolic path cost analysis for side-channel detection. ISSTA 2018: 27-37 - [c89]Heron Yang, Robert Morris, Corina S. Pasareanu:
Analysing the effect of uncertainty in airport surface operations. ISSTA/ECOOP Workshops 2018: 132-137 - [c88]Yannic Noller, Rody Kersten, Corina S. Pasareanu:
Badger: complexity analysis with fuzzing and symbolic execution. ISSTA 2018: 322-332 - [c87]Rui Qiu, Sarfraz Khurshid, Corina S. Pasareanu, Junye Wen, Guowei Yang:
Using Test Ranges to Improve Symbolic Execution. NFM 2018: 416-434 - [c86]Kasper Søe Luckow, Corina S. Pasareanu, Willem Visser:
Monte Carlo Tree Search for Finding Costly Paths in Programs. SEFM 2018: 123-138 - [p2]Dimitra Giannakopoulou, Kedar S. Namjoshi, Corina S. Pasareanu:
Compositional Reasoning. Handbook of Model Checking 2018: 345-383 - [e10]Gary T. Leavens, Alessandro Garcia, Corina S. Pasareanu:
Proceedings of the 2018 ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/SIGSOFT FSE 2018, Lake Buena Vista, FL, USA, November 04-09, 2018. ACM 2018, ISBN 978-1-4503-5573-5 [contents] - [i11]Yannic Noller, Rody Kersten, Corina S. Pasareanu:
Badger: Complexity Analysis with Fuzzing and Symbolic Execution. CoRR abs/1806.03283 (2018) - [i10]Divya Gopinath, Kaiyuan Wang, Mengshi Zhang, Corina S. Pasareanu, Sarfraz Khurshid:
Symbolic Execution for Deep Neural Networks. CoRR abs/1807.10439 (2018) - [i9]Corina S. Pasareanu, Divya Gopinath, Huafeng Yu:
Compositional Verification for Autonomous Systems with Deep Learning Components. CoRR abs/1810.08303 (2018) - [i8]Shirin Nilizadeh, Yannic Noller, Corina S. Pasareanu:
DifFuzz: Differential Fuzzing for Side-Channel Analysis. CoRR abs/1811.07005 (2018) - [i7]Pasquale Malacaria, M. H. R. Khouzani, Corina S. Pasareanu, Quoc-Sang Phan, Kasper Søe Luckow:
Symbolic Side-Channel Analysis for Probabilistic Programs. IACR Cryptol. ePrint Arch. 2018: 329 (2018) - 2017
- [j33]Huafeng Yu, Stanley Bak, Xin Li, Corina S. Pasareanu, Ramesh S., Qi Zhu:
Guest Editorial. IET Cyper-Phys. Syst.: Theory & Appl. 2(2): 55-56 (2017) - [c85]Rody Kersten, Kasper Søe Luckow, Corina S. Pasareanu:
POSTER: AFL-based Fuzzing for Java with Kelinci. CCS 2017: 2511-2513 - [c84]Quoc-Sang Phan, Lucas Bang, Corina S. Pasareanu, Pasquale Malacaria, Tevfik Bultan:
Synthesis of Adaptive Side-Channel Attacks. CSF 2017: 328-342 - [c83]Rui Qiu, Sarfraz Khurshid, Corina S. Pasareanu, Guowei Yang:
A synergistic approach for distributed symbolic execution using test ranges. ICSE (Companion Volume) 2017: 130-132 - [c82]Kasper Søe Luckow, Rody Kersten, Corina S. Pasareanu:
Symbolic Complexity Analysis Using Context-Preserving Histories. ICST 2017: 58-68 - [c81]