Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering

Large Language Models for Software Engineering: A Systematic Literature Review

Hou, X., Zhao, Y., Liu, Y., Yang, Z., Wang, K., Li, L., Luo, X., Lo, D., Grundy, J., & Wang, H. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3695988 · Cited by 1,029 · see citing works

Many-Objective Software Remodularization Using NSGA-III

Mkaouer, M. W., Kessentini, M., Shaout, A., Koligheu, P., Bechikh, S., Deb, K., & Ouni, A. (2015) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/2729974 · Cited by 269 · see citing works

A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models

Zhang, H., Yu, P. S., & Zhang, J. (2025) · ACM Computing Surveys · doi:10.1145/3731445 · Cited by 159 · see citing works

Deep learning-based software engineering: progress, challenges, and opportunities

Chen, X., Hu, X., Huang, Y., Jiang, H., Ji, W., Jiang, Y., Jiang, Y., Liu, B., Liu, H., Li, X., et al. (2024) · Science China Information Sciences · doi:10.1007/s11432-023-4127-5 · Cited by 114 · see citing works

Toward Understanding Deep Learning Framework Bugs

Chen, J., Liang, Y., Shen, Q., Jiang, J., & Li, S. (2023) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3587155 · Cited by 89 · see citing works

SoK: Security and Privacy of Blockchain Interoperability

Augusto, A., Belchior, R., Correia, M. P., Vasconcelos, A., Zhang, L., & T, T. H. M. I. (2024) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp54263.2024.00255 · Cited by 82 · see citing works

On the Effectiveness of Large Language Models in Domain-Specific Code Generation

Gu, X., Chen, M., Lin, Y., Hu, Y., Zhang, H., Wan, C., Wei, Z., Xu, Y., & Wang, J. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3697012 · Cited by 64 · see citing works

The Current Challenges of Software Engineering in the Era of Large Language Models

Gao, C., Hu, X., Gao, S., Xia, X., & Jin, Z. G. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3712005 · Cited by 65 · see citing works

GPTSniffer: A CodeBERT-based classifier to detect source code written by ChatGPT

Nguyen, P. T., Rocco, J. D., Sipio, C. D., Rubei, R., Ruscio, D. D., & Penta, M. D. (2024) · Journal of Systems and Software · doi:10.1016/j.jss.2024.112059 · Cited by 61 · see citing works

Artificial intelligence in oncology: ensuring safe and effective integration of language models in clinical practice

Verlingue, L., Boyer, C., Olgiati, L., Brutti-Mairesse, C., Morel, D., & Blay, J. (2024) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2024.101064 · Cited by 50 · see citing works

Anomaly diagnosis of connected autonomous vehicles: A survey

Fang, Y., Min, H., Wu, X., Wang, W., Zhao, X., Martínez‐Pastor, B., & Teixeira, R. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102223 · Cited by 45 · see citing works

"It would work for me too": How Online Communities Shape Software Developers' Trust in AI-Powered Code Generation Tools

Cheng, R., Wang, R., Zimmermann, T., & Ford, D. (2024) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3651990 · Cited by 47 · see citing works

Exploring the Capabilities of LLMs for Code-Change-Related Tasks

Fan, L., Liu, J., Liu, Z., Lo, D., Xia, X., & Li, S. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3709358 · Cited by 41 · see citing works

LogGT: Cross-system log anomaly detection via heterogeneous graph feature and transfer learning

Wang, P., Zhang, X., Cao, Z., Xu, W., & Li, W. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.124082 · Cited by 41 · see citing works

CrossFuzz: Cross-contract fuzzing for smart contract vulnerability detection

Yang, H., Gu, X., Chen, X., Zheng, L., & Cui, Z. (2024) · Science of Computer Programming · doi:10.1016/j.scico.2023.103076 · Cited by 38 · see citing works

Optimizing Autonomous Driving for Safety: A Human-Centric Approach with LLM-Enhanced RLHF

Sun, Y., Pargoo, N. S., Jin, P. J., & Ortiz, J. (2024) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/3675094.3677588 · Cited by 34 · see citing works

Advancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmap

Tekkesinoglu, S., Habibovic, A., & Kunze, L. (2025) · ACM Transactions on Human-Robot Interaction · doi:10.1145/3714478 · Cited by 34 · see citing works

Mining and searching app reviews for requirements engineering: Evaluation and replication studies

Dąbrowski, J., Letier, E., Perini, A., & Susi, A. (2023) · Information Systems · doi:10.1016/j.is.2023.102181 · Cited by 34 · see citing works

Test Optimization in DNN Testing: A Survey

Hu, Q., Guo, Y., Xie, X., Cordy, M., Ma, L., Papadakis, M., & Traon, Y. L. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3643678 · Cited by 33 · see citing works

Vulnerability detection techniques for smart contracts: A systematic literature review

Vidal, F. R., Ivaki, N., & Laranjeiro, N. (2024) · Journal of Systems and Software · doi:10.1016/j.jss.2024.112160 · Cited by 38 · see citing works

ContrastRepair : Enhancing Conversation-Based Automated Program Repair via Contrastive Test Case Pairs

Kong, J., Xie, X., Cheng, M., Liu, S., Du, X., & Guo, Q. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3719345 · Cited by 41 · see citing works

Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions

Vasconcelos, H., Bansal, G., Fourney, A., Liao, Q. V., & Vaughan, J. W. (2023) · arXiv · doi:10.48550/arxiv.2302.07248 · Cited by 23

Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions

Vasconcelos, H., Bansal, G., Fourney, A., Liao, Q. V., & Vaughan, J. W. (2024) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3702320 · Cited by 43 · see citing works

Hybrid Automated Program Repair by Combining Large Language Models and Program Analysis

Li, F., Jiang, J., Sun, J., & Zhang, H. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3715004 · Cited by 30 · see citing works

An inclusive analysis for performance and efficiency of graph neural network models for node classification

Ratna, S., Singh, S., & Sharma, A. (2025) · Computer Science Review · doi:10.1016/j.cosrev.2024.100722 · Cited by 21 · see citing works

One Size Does Not Fit All: Multi-granularity Patch Generation for Better Automated Program Repair

Lin, B., Wang, S., Wen, M., Chen, L., & Mao, X. (2024) · ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) · doi:10.1145/3650212.3680381 · Cited by 20 · see citing works

Greybox Fuzzing for Concurrency Testing

Wolff, D., Shi, Z., Duck, G. J., Mathur, U., & Roychoudhury, A. (2024) · International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) · doi:10.1145/3620665.3640389 · Cited by 20 · see citing works

Unveiling vulnerable smart contracts: Toward profiling vulnerable smart contracts using genetic algorithm and generating benchmark dataset

HajiHosseinKhani, S., Lashkari, A. H., & Oskui, A. M. (2023) · Blockchain Research and Applications · doi:10.1016/j.bcra.2023.100171 · Cited by 19 · see citing works

Technical debt management automation: State of the art and future perspectives

Biazotto, J. P., Feitosa, D., Avgeriou, P., & Nakagawa, E. Y. (2023) · Information and Software Technology · doi:10.1016/j.infsof.2023.107375 · Cited by 18 · see citing works

Prioritizing user requirements for digital products using explainable artificial intelligence: A data-driven analysis on video conferencing apps

Bai, S., Shi, S., Han, C., Yang, M., Gupta, B. B., & Arya, V. (2024) · Future Generation Computer Systems · doi:10.1016/j.future.2024.04.037 · Cited by 18 · see citing works

Large-Scale Study of Vulnerability Scanners for Ethereum Smart Contracts

Sendner, C., Petzi, L., Stang, J., & Dmitrienko, A. (2024) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp54263.2024.00230 · Cited by 18 · see citing works

Bridging language models and computational materials science: A prompt-driven framework for material property prediction

Lv, S., Peng, L., Wu, W., Yao, Y., Jiao, S., & Hu, W. (2025) · Materials Genome Engineering Advances · doi:10.1002/mgea.70013 · Cited by 18 · see citing works

Undefined-oriented Programming: Detecting and Chaining Prototype Pollution Gadgets in Node.js Template Engines for Malicious Consequences

Liu, Z., An, K., & Cao, Y. (2024) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp54263.2024.00121 · Cited by 17 · see citing works

Training-free retrieval-based log anomaly detection with pre-trained language model considering token-level information

No, G., Lee, Y., Kang, H., & Kang, P. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.108613 · Cited by 19 · see citing works

Deep learning for code generation: a survey

Zhang, H., Zhang, K., Li, Z., Li, J., Li, J., Li, Y., Zhao, Y., Zhu, Y. S., Liu, F., Li, G., et al. (2024) · Science China Information Sciences · doi:10.1007/s11432-023-3956-3 · Cited by 17 · see citing works

Predecessor-aware Directed Greybox Fuzzing

Zhang, Y., Liu, Y., Xu, J., & Wang, Y. (2024) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp54263.2024.00040 · Cited by 15 · see citing works

Fuzzing MLIR Compiler Infrastructure via Operation Dependency Analysis

Suo, C., Chen, J., Liu, S., Jiang, J., Zhao, Y., & Wang, J. (2024) · ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) · doi:10.1145/3650212.3680360 · Cited by 14 · see citing works

CXXCrafter: An LLM-Based Agent for Automated C/C++ Open Source Software Building

Yu, Z., Zhang, Y., Wen, M., Nie, Y., Zhang, W., & Yang, M. (2025) · Proceedings of the ACM on software engineering. · doi:10.1145/3729386 · Cited by 13 · see citing works

VulTR: Software vulnerability detection model based on multi-layer key feature enhancement

He, H., Wang, S., Wang, Y., Liu, K., & Yu, L. (2024) · Computers & Security · doi:10.1016/j.cose.2024.104139 · Cited by 13 · see citing works

Translation of Low-Resource COBOL to Logically Correct and Readable Java leveraging High-Resource Java Refinement

Gandhi, S., Patwardhan, M. S., Khatri, J., Vig, L., & Medicherla, R. K. (2024) · International Workshop on Large Language Models for Code (LLM4Code) · doi:10.1145/3643795.3648388 · Cited by 12 · see citing works

Architecture decisions in quantum software systems: An empirical study on Stack Exchange and GitHub

Aktar, M. S., Liang, P., Waseem, M., Tahir, A., Ahmad, A., Zhang, B., & Li, Z. (2024) · Information and Software Technology · doi:10.1016/j.infsof.2024.107587 · Cited by 12 · see citing works

QFAS-KE: Query focused answer summarization using keyword extraction

Goyal, R., Kumar, P., & Singh, V. P. (2025) · Information Processing & Management · doi:10.1016/j.ipm.2025.104104 · Cited by 12 · see citing works

Efficient Detection of Java Deserialization Gadget Chains via Bottom-up Gadget Search and Dataflow-aided Payload Construction

Chen, B., Zhang, L., Huang, X., Cao, Y., Lian, K., Zhang, Y., & Yang, M. (2024) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp54263.2024.00150 · Cited by 11 · see citing works

Intelligent question answering for water conservancy project inspection driven by knowledge graph and large language model collaboration

Yang, Y., Chen, S., Zhu, Y., Liu, X., Pan, S., & Wang, X. (2024) · La Houille Blanche · doi:10.1080/27678490.2024.2397337 · Cited by 11 · see citing works

Patch Correctness Assessment: A Survey

Fei, Z., Ge, J., Li, C., Wang, T., Li, Y., Zhang, H., Huang, L., & Luo, B. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3702972 · Cited by 11 · see citing works

When Fine-Tuning LLMs Meets Data Privacy: An Empirical Study of Federated Learning in LLM-Based Program Repair

Luo, W., Keung, J., Yang, B., Ye, H., Goues, C. L., Bissyandé, T. F., Tian, H., & Le, X.-B. D. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3733599 · Cited by 18 · see citing works

Comprehensive review of smart contract and DeFi security: Attack, vulnerability detection, and automated repair

Qian, P., Cao, R., Liu, Z., Li, W., Li, M., Zhang, L., Xu, Y., Chen, J., & He, Q. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128431 · Cited by 26 · see citing works

Risk assessment in autonomous driving: a comprehensive survey of risk sources, methodologies, and system architectures

Lu, D., Du, H., Wu, Z., & Yang, S. (2025) · Autonomous Intelligent Systems · doi:10.1007/s43684-025-00112-1 · Cited by 10 · see citing works

VM Matters: A Comparison of WASM VMs and EVMs in the Performance of Blockchain Smart Contracts

Zhang, Y., Zheng, S., Wang, H., Wu, L., Huang, G., & Liu, X. (2024) · ACM Transactions on Modeling and Performance Evaluation of Computing Systems · doi:10.1145/3641103 · Cited by 10 · see citing works

On the effect of incompleteness to check requirement-to-method traces

Hammoudi, M., Mayr‐Dorn, C., Mashkoor, A., & Egyed, A. F. (2021) · ACM Symposium on Applied Computing · doi:10.1145/3412841.3442021 · Cited by 10 · see citing works

Automated Commit Intelligence by Pre-training

Liu, S., Li, Y., Xie, X., Ma, W., Meng, G., & Liu, Y. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3674731 · Cited by 9 · see citing works

A Review of Learning-based Smart Contract Vulnerability Detection: A Perspective on Code Representation

Wang, B., Tong, Y., Ji, S., Dong, H., Luo, X., & Zhang, P. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3750042 · Cited by 8 · see citing works

Breaking the Loop: AWARE is the New MAPE-K

Sanwouo, B., Quinton, C., & Temple, P. (2025) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3696630.3728512 · Cited by 8 · see citing works

Language models can prioritize patches for practical program patching

Kang, S., & Yoo, S. (2022) · IEEE/ACM International Workshop on Automated Program Repair (APR) · doi:10.1145/3524459.3527343 · Cited by 8 · see citing works

Mitigating Emergent Malware Label Noise in DNN-Based Android Malware Detection

Li, H., Cheng, X. Y., Zhang, G., Xu, G., Xu, G., & Wang, H. (2025) · Proceedings of the ACM on software engineering. · doi:10.1145/3715769 · Cited by 7 · see citing works

Your “Notice” Is Missing: Detecting and Fixing Violations of Modification Terms in Open Source Licenses during Forking

Huang, K., Xia, Y., Chen, B., He, S., Zeng, H., Zhou, Z., Guo, J., & Peng, X. (2024) · ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) · doi:10.1145/3650212.3680339 · Cited by 6 · see citing works

ROSE: An IDE-Based Interactive Repair Framework for Debugging

Reiss, S. P., Wei, X., Yuan, J. P., & Xin, Q. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3705306 · Cited by 5 · see citing works

The Road to Hybrid Quantum Programs: Characterizing the Evolution from Classical to Hybrid Quantum Software

Maio, V. D., Brandić, I., Deelman, E., & Cito, J. (2025) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3696630.3731623 · Cited by 6 · see citing works

Demystifying React Native Android Apps for Static Analysis

Liu, Y., Chen, X., Liu, P., Samhi, J., Grundy, J., Chen, C., & Li, L. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3702977 · Cited by 5 · see citing works

A non-functional requirements classification model based on cooperative attention mechanism fused with label embedding

Dai, Z., & Yi-fu, H. (2024) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2024.109856 · Cited by 5 · see citing works

DyLin: A Dynamic Linter for Python

Eghbali, A., Burk, F., & Pradel, M. (2025) · Proceedings of the ACM on software engineering. · doi:10.1145/3729395 · Cited by 5 · see citing works

Collaboration is all you need: LLM Assisted Safe Code Translation

Karanjai, R., Blackshear, S., Xu, L., & Shi, W. (2025) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3696630.3728521 · Cited by 5 · see citing works

Assessing Effectiveness of Test Suites: What Do We Know and What Should We Do?

Zhang, P., Wang, Y., Liu, X., Lu, Z., Yang, Y., Li, Y., Chen, L., Wang, Z., Sun, C., Yu, X., et al. (2023) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3635713 · Cited by 4 · see citing works

End-Users Know Best: Identifying Undesired Behavior of Alexa Skills Through User Review Analysis

Aldeen, M. S., Young, J. A., Liao, S., Chang, T.-Y., Cheng, L., Cai, H., Luo, X., & Hu, H. (2024) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3678517 · Cited by 4 · see citing works

Efficient software product-line model checking using induction and a SAT solver

He, F., Gao, Y., & Yin, L. (2018) · Frontiers of Computer Science · doi:10.1007/s11704-016-6048-7 · Cited by 4 · see citing works

Semantic-based Architecture Smell Analysis

Chondamrongkul, N., Sun, J., Warren, I., & Lee, S. U.-J. (2020) · doi:10.1145/3372020.3391564 · Cited by 4 · see citing works

C-CORE: Clustering by Code Representation to Prioritize Test Cases in Compiler Testing

Zhou, W. J., Jiang, X., & Qin, C. (2024) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2023.043248 · Cited by 4 · see citing works

Security Vulnerabilities in Infrastructure as Code: What, How Many, and Who?Preprint

War, A., Habib, A., Diallo, A., Klein, J., & Bissyandé, T. F. (2023) · Research Square · doi:10.21203/rs.3.rs-3600645/v1 · Cited by 4 · see citing works

Evaluating Large Language Models for Requirements Question Answering in Industrial Aerospace Software

Yang, L.-X., Luo, Y.-X., Gao, H., Fan, Y.-S., Zhang, J., Li, X.-F., Dong, X., Gu, B., Jin, Z., & Yang, M.-F. (2025) · SIGSOFT FSE Companion · doi:10.1145/3696630.3728560 · Cited by 6 · see citing works

Introducing Repository Stability

Destefanis, G., Bartolucci, S., Graziotin, D., Neykova, R., & Ortu, M. (2025) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3696630.3728498 · Cited by 3 · see citing works

Metamorphic Testing of Deep Code Models: A Systematic Literature Review

Asgari, A., de Koning, M., Derakhshanfar, P., & Panichella, A. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3766552 · Cited by 3 · see citing works

Exploring the Motivations and the Concerns Behind Self-Managed Medication Abortion Done by Purchasing Medication Online: Qualitative Interview Study With US Abortion Seekers Post-Roe

Bosco, C., Otenen, E., & Shih, P. C. (2025) · Journal of Medical Internet Research · doi:10.2196/75780 · Cited by 3 · see citing works

A Comparative Study of Android Performance Issues in Real-World Applications and Literature

Liao, D., Pan, S., Yang, S., Zhao, Y., Xing, Z., & Sun, X. (2026) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3771932 · Cited by 4 · see citing works

Extraction and empirical evaluation of GUI-level invariants as GUI Oracles in mobile app testing

Yarifard, A. A., Araban, S., Paydar, S., Garousi, V., Morisio, M., & Coppola, R. (2024) · Information and Software Technology · doi:10.1016/j.infsof.2024.107531 · Cited by 3 · see citing works

FCEVAL: An effective and quantitative platform for evaluating fuzzer combinations fairly and easily

Zhao, X., Yang, C., Jia, Z., Wang, Y., & Ma, J. (2023) · Computers & Security · doi:10.1016/j.cose.2023.103354 · Cited by 3 · see citing works

An Empirical Study on the Stability of Explainable Software Defect Prediction

Shin, J., Aleithan, R., Nam, J., Wang, J., Harzevili, N. S., & Wang, S. (2023) · Asia-Pacific Software Engineering Conference (APSEC) · doi:10.1109/apsec60848.2023.00024 · Cited by 3 · see citing works

DFL: A DOM sample generation oriented fuzzing framework for browser rendering engines

Duan, G., Hai, Z., Cai, M., Sun, J., & Chen, H. (2024) · Information and Software Technology · doi:10.1016/j.infsof.2024.107591 · Cited by 3 · see citing works

Broken Agreement: The Evolution of Solidity Error Handling

Mitropoulos, C., Kechagia, M., Maschas, C., Ioannidis, S., Sarro, F., & Mitropoulos, D. (2024) · Proceedings of the ... ACM-IEEE International Symposium on Empirical Software Engineering and Measurement/International Symposium on Empirical Software Engineering and Measurement · doi:10.1145/3674805.3686686 · Cited by 3 · see citing works

A systematic literature review on cross-language source code clone detection

Alshabeeb, E. S., Mahmood, S., & Alshayeb, M. (2025) · Computer Science Review · doi:10.1016/j.cosrev.2025.100786 · Cited by 2 · see citing works

LLPut: Investigating Large Language Models for Bug Report-Based Input Generation

Hasan, A. A., Saha, S., Imran, M. M., & Zaman, T. S. (2025) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3696630.3728701 · Cited by 3 · see citing works

Enhancing Code LLM Training with Programmer Attention

Zhang, Y., Huang, C., Karas, Z., Nguyen, T. D., Leach, K., & Huang, Y. (2025) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3696630.3728510 · Cited by 5 · see citing works

Drop the Golden Apples: Identifying Third-Party Reuse by DB-Less Software Composition Analysis

Zhang, L., Liu, C., Wu, J., ZHANG, S., Liu, C., Xu, Z., Chen, S., & Liu, Y. (2025) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3696630.3728525 · Cited by 2 · see citing works

Risk-guided efficient scenario selection for autonomous driving testing

Yao, B., Huang, S., Li, L., Wu, H., & Liu, C. (2025) · Future Generation Computer Systems · doi:10.1016/j.future.2025.108173 · Cited by 2 · see citing works

Deep Learning Representations of Programs: A Systematic Literature Review

Shanmugasundaram, D., Arivukkarasu, P., Chen, H., & Cai, H. (2025) · ACM Computing Surveys · doi:10.1145/3769008 · Cited by 3 · see citing works

Evolving Software: Combining Online Learning with Mutation-Based Stochastic Search

Renzullo, J., Weimer, W. R., & Forrest, S. (2023) · ACM Transactions on Evolutionary Learning and Optimization · doi:10.1145/3597617 · Cited by 2 · see citing works

Rationale Dataset and Analysis for the Commit Messages of the Linux Kernel Out-of-Memory Killer

Dhaouadi, M., Oakes, B., & Famelis, M. (2024) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1145/3643916.3644413 · Cited by 2 · see citing works

Preserving Reactiveness: Understanding and Improving the Debugging Practice of Blocking-Call Bugs

Shahoor, A., Yi, J., & Kim, D. (2024) · ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) · doi:10.1145/3650212.3680319 · Cited by 2 · see citing works

Trend analysis in competitive programming using topic modeling

Ramahalim, A. Y., Karuniawan, C. E., Purwanto, E. S., & Ario, M. K. (2024) · Procedia Computer Science · doi:10.1016/j.procs.2024.10.286 · Cited by 2 · see citing works

You Don’t Have to Say Where to Edit! jLED—Joint Learning to Localize and Edit Source Code

Pian, W., Li, Y., Tian, H., Sun, T., Song, Y., Tang, X., Habib, A., Klein, J., & Bissyandé, T. F. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3712187 · Cited by 2 · see citing works

The CAMINOS interconnection networks simulator

Camarero, C., Postigo, D., & Fuentes, P. (2025) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2025.105136 · Cited by 2 · see citing works

CKTyper: Enhancing Type Inference for Java Code Snippets by Leveraging Crowdsourcing Knowledge in Stack Overflow

Li, A., Zhang, N., Zou, Y., Chen, Z., Wang, J., & Zheng, Z. (2025) · Proceedings of the ACM on software engineering. · doi:10.1145/3715724 · Cited by 2 · see citing works

Improving Code Refinement for Code Review Via Input Reconstruction and Ensemble Learning

Lu, J., Tang, Z., & Liu, Z. (2023) · Asia-Pacific Software Engineering Conference (APSEC) · doi:10.1109/apsec60848.2023.00026 · Cited by 2 · see citing works

An Empirical Study on Common Sense-Violating Bugs in Mobile Apps

Fan, F., Jiang, Y., Chen, T., Zhang, H., Zhang, Y., Niu, N., & Liu, H. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3709356 · Cited by 1 · see citing works

BaSFuzz: Fuzz testing based on difference analysis for seed bytes

Lan, W., Huang, C., Yu, T., Li, L. L., & Cui, Z. (2025) · Journal of Systems and Software · doi:10.1016/j.jss.2025.112340 · Cited by 1 · see citing works

RCFuzzer: Recommendation-based Collaborative Fuzzer

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dl²: Detecting Communication Deadlocks in Deep Learning Jobs

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Hybrid approach for multilevel multi-class requirement classification: Impact of stop-word removal and data augmentation

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Towards the generalization of multi-view learning: An information-theoretical analysis

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Covertvasion: Depicting threats through covert channels based novel evasive attacks in android

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Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

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Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering

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