7 citations · 7 across the 10 of their papers we have counts for
11 papers
Why Do LLMs Fail at OCL Generation? A Graph Reasoning Perspective
Hamza Attarwala, Moataz Chouchen, Mohammad Hamdaqa +1
Large Language Models (LLMs) are increasingly used to generate Object Constraint Language (OCL) constraints from natural language specifications and UML class diagrams. However, ex…
Multi-Agent LLM Governance for Safe Two-Timescale Reinforcement Learning in SDN-IoT Defense
Saeid Jamshidi, Negar Shahabi, Foutse Khomh +2
Software-Defined Networking (SDN) is increasingly adopted to secure Internet-of-Things (IoT) networks due to its centralized control and programmable forwarding. However, SDN-IoT d…
Adversarial Moral Stress Testing of Large Language Models
Saeid Jamshidi, Foutse Khomh, Arghavan Moradi Dakhel +3
Evaluating the ethical robustness of large language models (LLMs) deployed in software systems remains challenging, particularly under sustained adversarial user interaction. Exist…
Dynasto: Validity-Aware Dynamic-Static Parameter Optimization for Autonomous Driving Testing
Dmytro Humeniuk, Mohammad Hamdaqa, Houssem Ben Braiek +2
Extensive simulation-based testing is important for assuring the safety of autonomous driving systems (ADS). However, generating safety-critical traffic scenarios remains challengi…
Verifiable Manifest Signing and Transparency Enforcement for Secure MCP-Based LLM Pipelines
Saeid Jamshidi, Kawser Wazed Nafi, Arghavan Moradi Dakhel +2
Large Language Models (LLMs) are increasingly deployed in tool-driven environments such as healthcare analytics, financial systems, retrieval-augmented generation (RAG), and multi-…
Refactoring with LLMs: Bridging Human Expertise and Machine Understanding
Yonnel Chen Kuang Piao, Jean Carlors Paul, Leuson Da Silva +3
Code refactoring is a fundamental software engineering practice aimed at improving code quality and maintainability. Despite its importance, developers often neglect refactoring du…
PRIMG : Efficient LLM-driven Test Generation Using Mutant Prioritization
Mohamed Salah Bouafif, Mohammad Hamdaqa, Edward Zulkoski
Mutation testing is a widely recognized technique for assessing and enhancing the effectiveness of software test suites by introducing deliberate code mutations. However, its appli…
PathOCL: Path-Based Prompt Augmentation for OCL Generation with GPT-4
Seif Abukhalaf, Mohammad Hamdaqa, Foutse Khomh
The rapid progress of AI-powered programming assistants, such as GitHub Copilot, has facilitated the development of software applications. These assistants rely on large language m…
A Context-Driven Approach for Co-Auditing Smart Contracts with The Support of GPT-4 code interpreter
Mohamed Salah Bouafif, Chen Zheng, Ilham Ahmed Qasse +3
The surge in the adoption of smart contracts necessitates rigorous auditing to ensure their security and reliability. Manual auditing, although comprehensive, is time-consuming and…
Exploring Security Practices in Infrastructure as Code: An Empirical Study
Alexandre Verdet, Mohammad Hamdaqa, Leuson Da Silva +1
Cloud computing has become popular thanks to the widespread use of Infrastructure as Code (IaC) tools, allowing the community to conveniently manage and configure cloud infrastruct…
On Codex Prompt Engineering for OCL Generation: An Empirical Study
Seif Abukhalaf, Mohammad Hamdaqa, Foutse Khomh
The Object Constraint Language (OCL) is a declarative language that adds constraints and object query expressions to MOF models. Despite its potential to provide precision and conc…