publications

2025

1. TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance

   Waris Gill, Ali Anwar, and Muhammad Ali Gulzar

   In 2025 IEEE/ACM 47th International Conference on Software Engineering (ICSE), 2025

   Bib PDF Code

   @inproceedings{gill2025tracefl,
     author = {Gill, Waris and Anwar, Ali and Gulzar, Muhammad Ali},
     booktitle = {2025 IEEE/ACM 47th International Conference on Software Engineering (ICSE)},
     keywords = {interpretability;explainability;debugging;federated learning;transformer;machine learning},
     organization = {IEEE},
     title = {{TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance}},
     year = {2025}
   }

2. MeanCache: User-Centric Semantic Caching for LLM Web Services

   Waris Gill, Mohamed Elidrisi, Pallavi Kalapatapu, and 2 more authors

   In 2025 IEEE 39th International Parallel & Distributed Processing Symposium (IPDPS), 2025

   Bib PDF

   @inproceedings{gill2025MeanCache,
     author = {Gill, Waris and Elidrisi, Mohamed and Kalapatapu, Pallavi and Anwar, Ali and Gulzar, Muhammad Ali},
     booktitle = {{2025 IEEE 39th International Parallel & Distributed Processing Symposium (IPDPS)}},
     organization = {IEEE},
     title = {{MeanCache: User-Centric Semantic Caching for LLM Web Services}},
     year = {2025}
   }

3. Advancing Semantic Caching for LLMs with Domain-Specific Embeddings and Synthetic Data

   Waris Gill, Justin Cechmanek, Tyler Hutcherson, and 5 more authors

   2025

   Bib PDF Code

   @misc{gill2025advancingsemanticcachingllms,
     archiveprefix = {arXiv},
     author = {Gill, Waris and Cechmanek, Justin and Hutcherson, Tyler and Rajamohan, Srijith and Agarwal, Jen and Gulzar, Muhammad Ali and Singh, Manvinder and Dion, Benoit},
     eprint = {2504.02268},
     primaryclass = {cs.LG},
     title = {Advancing Semantic Caching for LLMs with Domain-Specific Embeddings and Synthetic Data},
     url = {https://arxiv.org/abs/2504.02268},
     year = {2025}
   }

4. Are the Majority of Public Computational Notebooks Pathologically Non-Executable?

   Tien Nguyen, Waris Gill, and Muhammad Ali Gulzar

   In 2025 IEEE/ACM 22nd International Conference on Mining Software Repositories (MSR), 2025

   Bib PDF Code

   @inproceedings{nguyen2025majority,
     author = {Nguyen, Tien and Gill, Waris and Gulzar, Muhammad Ali},
     booktitle = {{2025 IEEE/ACM 22nd International Conference on Mining Software Repositories (MSR)}},
     title = {Are the Majority of Public Computational Notebooks Pathologically Non-Executable?},
     year = {2025}
   }

5. How Accurately Do Large Language Models Understand Code?

   Sabaat Haroon, Ahmad Faraz Khan, Ahmad Humayun, and 5 more authors

   2025

   Bib PDF

   @misc{haroon2025accuratelylargelanguagemodels,
     archiveprefix = {arXiv},
     author = {Haroon, Sabaat and Khan, Ahmad Faraz and Humayun, Ahmad and Gill, Waris and Amjad, Abdul Haddi and Butt, Ali R. and Khan, Mohammad Taha and Gulzar, Muhammad Ali},
     eprint = {2504.04372},
     primaryclass = {cs.SE},
     title = {How Accurately Do Large Language Models Understand Code?},
     url = {https://arxiv.org/abs/2504.04372},
     year = {2025}
   }

2023

1. FedDebug: Systematic Debugging for Federated Learning Applications

   Waris Gill, Ali Anwar, and Muhammad Ali Gulzar

   In 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), 2023

   Bib PDF Code

   @inproceedings{gill2023FedDebug,
     author = {Gill, Waris and Anwar, Ali and Gulzar, Muhammad Ali},
     booktitle = {2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)},
     issn = {1558-1225},
     keywords = {},
     pages = {512-523},
     title = {{FedDebug: Systematic Debugging for Federated Learning Applications}},
     year = {2023}
   }

2. FedDefender: Backdoor Attack Defense in Federated Learning

   Waris Gill, Ali Anwar, and Muhammad Ali Gulzar

   In Proceedings of the 1st International Workshop on Dependability and Trustworthiness of Safety-Critical Systems with Machine Learned Components, , San Francisco, CA, USA, , 2023

   Bib PDF Code

   @inproceedings{gill2023FedDefender,
     address = {New York, NY, USA},
     author = {Gill, Waris and Anwar, Ali and Gulzar, Muhammad Ali},
     booktitle = {Proceedings of the 1st International Workshop on Dependability and Trustworthiness of Safety-Critical Systems with Machine Learned Components},
     isbn = {9798400703799},
     keywords = {fault localization, testing, differential testing, poisoning attack, federated learning, backdoor attack, deep learning},
     location = {, San Francisco, CA, USA, },
     numpages = {4},
     pages = {6–9},
     publisher = {Association for Computing Machinery},
     series = {SE4SafeML 2023},
     title = {{FedDefender: Backdoor Attack Defense in Federated Learning}},
     year = {2023}
   }