Feng, R., Pearce, H., Liguori, P., and Sui, Y. (2025). CGP-Tuning: Structure-Aware Soft Prompt Tuning for Code Vulnerability Detection.
IEEE Transactions on Software Engineering.
DOI: 10.1109/TSE.2025.3591934
Improta, I., Liguori, P., Natella, R., Cukic, B., and Cotroneo, D. (2025). Enhancing robustness of AI offensive code generators via data augmentation.
Empirical Software Engineering.
DOI: 10.1007/s10664-024-10569-y
Cotroneo, D., De Luca, R., and Liguori, P. (2025). DeVAIC: A tool for security assessment of AI-generated code.
Information and Software Technology.
DOI: 10.1016/j.infsof.2024.107572
Cotroneo, D., Foggia, A., Improta, C., Liguori, P., and Natella, R. (2024). Automating the correctness assessment of AI-generated code for security contexts.
The Journal of Systems & Software.
DOI: 10.1016/j.jss.2024.112113
Natella, R., Liguori, P., Improta, C., Cukic, B., and Cotroneo, D. (2024). AI Code Generators for Security: Friend or Foe?
IEEE Security & Privacy.
DOI: 10.1109/MSEC.2024.3355713
Liguori, P., Improta, C., Natella, R., Cukic, B., and Cotroneo, D. (2023). Who evaluates the evaluators? On automatic metrics for assessing AI-based offensive code generators.
Expert Systems with Applications.
DOI: 10.1016/j.eswa.2023.120073
Cotroneo, D., De Simone, L., Liguori, P., and Natella, R. (2023). Run-time failure detection via non-intrusive event analysis in a large-scale cloud computing platform.
Journal of Systems and Software.
DOI: 10.1016/j.jss.2023.111611
Liguori, P., Al-Hossami, E., Cotroneo, D., Natella, R., Cukic, B., and Shaikh, S. (2022). Can We Generate Shellcodes via Natural Language? An Empirical Study.
Automated Software Engineering.
DOI: 10.1007/s10515-022-00331-3
Cotroneo, D., De Simone, L., Liguori, P., and Natella, R. (2021). Enhancing the Analysis of Software Failures in Cloud Computing Systems with Deep Learning.
Journal of Systems and Software.
DOI: 10.1016/j.jss.2021.111043
Cotroneo, D., De Simone, L., Liguori, P., and Natella, R. (2020). Fault Injection Analytics: A Novel Approach to Discover Failure Modes in Cloud-Computing Systems.
IEEE Transactions on Dependable and Secure Computing.
DOI: 10.1109/TDSC.2020.3025289
Conference Papers
Puccetti, T., De Vivo, S., Zhang, D., Liguori, P., Natella, R., and Ceccarelli, A. (2025). Creation and Use of a Representative Dataset for Advanced Persistent Threats Detection.
In International Conference on Computer Safety, Reliability, and Security (pp. 51-66). Cham: Springer Nature Switzerland.
DOI: 10.1007/978-3-032-01241-8_4
Cotroneo, D., De Rosa, G., and Liguori, P. (2025). PyResBugs: A Dataset of Residual Python Bugs for Natural Language-Driven Fault Injection.
In 2025 IEEE/ACM Second International Conference on AI Foundation Models and Software Engineering (Forge).
DOI: 10.1109/Forge66646.2025.00024
Improta, C., Tufano, R., Liguori, P., Cotroneo, D., and Bavota, G. (2025).Quality In, Quality Out: Investigating Training Data's Role in AI Code Generation.
33rd IEEE/ACM International Conference on Program Comprehension (ICPC 2024).
DOI: 10.1109/icpc66645.2025.00056
Liguori, P., Improta, I., Natella, R., Cukic, B., and Cotroneo, D. (2024).Enhancing AI-based Generation of Software Exploits with Contextual Information.
IEEE 35th International Symposium on Software Reliability Engineering (ISSRE).
DOI: 10.1109/ISSRE62328.2024.00027
Cotroneo, D., Improta, C., Liguori, P., and Natella, R. (2024). Vulnerabilities in AI Code Generators: Exploring Targeted Data Poisoning Attacks.
32nd IEEE/ACM International Conference on Program Comprehension (ICPC 2024).
DOI: 10.1145/3643916.3644416
Liguori, P., Marescalco, C., Natella, R., Orbinato, V., and Pianese, L. (2024). The Power of Words: Generating PowerShell Attacks from Natural Language.
18th USENIX WOOT Conference on Offensive Technologies.
URL: https://www.usenix.org/conference/woot24/presentation/liguori
Liguori, P., Al-Hossami, E., Orbinato, V., Natella, R., Shaikh, S., Cotroneo, D., and Cukic, B. (2021). EVIL: Exploiting Software via Natural Language.
32nd International Symposium on Software Reliability Engineering (ISSRE 2021).
DOI: 10.1109/ISSRE52982.2021.00042
Cotroneo, D., De Simone, L., Liguori, P., and Natella, R. (2020). ProFIPy: Programmable Software Fault Injection as-a-Service.
50th International Conference on Dependable Systems and Networks (DSN).
DOI: 10.1109/DSN48063.2020.00052
Cotroneo, D., De Simone, L., Liguori, P., Natella, R., and Bidokhti, N. (2019). Enhancing Failure Propagation Analysis in Cloud Computing Systems.
30th International Symposium on Software Reliability Engineering (ISSRE).
DOI: 10.1109/ISSRE.2019.00023
Cotroneo, D., De Simone, L., Liguori, P., Natella, R., and Bidokhti, N. (2019). FailViz: A Tool for Visualizing Fault Injection Experiments in Distributed Systems.
15th European Dependable Computing Conference (EDCC).
DOI: 10.1109/EDCC.2019.00036
Cotroneo, D., De Simone, L., Liguori, P., Natella, R., and Bidokhti, N. (2019). How Bad Can a Bug Get? An Empirical Analysis of Software Failures in the OpenStack Cloud Computing Platform.
27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE).
DOI: 10.1145/3338906.3338916
Workshop Papers and Supplemental Volumes
Altiero, F., Cotroneo, D., De Luca, R., and Liguori, P. (2025). Securing AI Code Generation Through Automated Pattern-Based Patching.
In 2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)
DOI: 10.1109/DSN-W65791.2025.00077
Liguori, P., Natella, R., and Cotroneo, D. (2025). Generative AI in Cybersecurity: Generating Offensive Code from Natural Language.
In 2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks-Supplemental Volume (DSN-S)
DOI: 10.1109/DSN-S65789.2025.00059
Cotroneo, D., and Liguori, P. (2024). Neural Fault Injection: Generating Software Faults from Natural Language.
54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S).
DOI: 10.1109/DSN-S60304.2024.00016
De Vivo, S., Obaidat, I., Dai, D., and Liguori, P. (2024). DDoShield-IoT: A Testbed for Simulating and Lightweight Detection of IoT Botnet DDoS Attacks.
54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S).
DOI: 10.1109/DSN-W60302.2024.00014
De Vivo, S., and Liguori, P. (2023). Simulation Environment for the Evaluation of Lightweight Intrusion Detection Systems.
34th International Symposium on Software Reliability Engineering Workshops (ISSREW).
DOI: 10.1109/ISSREW60843.2023.00061
Liguori, P., Improta, C., De Vivo, S., Natella, R., Cukic, B., and Cotroneo, D. (2022). Can NMT Understand Me? Towards Perturbation-based Evaluation of NMT Models for Code Generation.
1st International Workshop on Natural Language-Based Software Engineering (NLBSE).
DOI: 10.1145/3528588.3528653
Liguori, P., Al-Hossami, E., Cotroneo, D., Natella, R., Cukic, B., and Shaikh, S. (2021). Shellcode_IA32: A Dataset for Automatic Shellcode Generation.
NLP4Prog Workshop co-located with ACL-IJCNLP 2021.
DOI: 10.18653/v1/2021.nlp4prog-1.7
Cotroneo, D., De Simone, L., Liguori, P., Natella, R., and Scibelli, A. (2020). Towards Runtime Verification via Event Stream Processing in Cloud Computing Infrastructures.
International Workshop on Artificial Intelligence for IT Operations (AIOPS 2020).
DOI: 10.1007/978-3-030-76352-7_19
Cotroneo, D., De Simone, L., Di Martino, A., Liguori, P., and Natella, R. (2018). Enhancing the Analysis of Error Propagation and Failure Modes in Cloud Systems.
2018 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW).
DOI: 10.1109/ISSREW.2018.00-13