3 citations · 10 across the 28 of their papers we have counts for
12 papers · 1 filter
Empirical Study for Structured Output Control in LLMs for Software Engineering
Yewei Song, Prateek Rajput, Tiezhu Sun +3
LLM-generated outputs in software engineering rarely exist in isolation. They must plug into toolchains, APIs, and data pipelines that impose strict, often organization-specific st…
Dialect2SQL: A Novel Text-to-SQL Dataset for Arabic Dialects with a Focus on Moroccan Darija
Salmane Chafik, Saad Ezzini, Ismail Berrada
The task of converting natural language questions (NLQs) into executable SQL queries, known as text-to-SQL, has gained significant interest in recent years, as it enables non-techn…
CallNavi, A Challenge and Empirical Study on LLM Function Calling and Routing
Yewei Song, Xunzhu Tang, Cedric Lothritz +6
API-driven chatbot systems are increasingly integral to software engineering applications, yet their effectiveness hinges on accurately generating and executing API calls. This is…
CodeAgent: Autonomous Communicative Agents for Code Review
Xunzhu Tang, Kisub Kim, Yewei Song +6
Code review, which aims at ensuring the overall quality and reliability of software, is a cornerstone of software development. Unfortunately, while crucial, Code review is a labor-…
Enhancing Text-to-SQL Translation for Financial System Design
Yewei Song, Saad Ezzini, Xunzhu Tang +6
Text-to-SQL, the task of translating natural language questions into SQL queries, is part of various business processes. Its automation, which is an emerging challenge, will empowe…
Patch-CLIP: A Patch-Text Pre-Trained Model
Xunzhu Tang, Zhenghan Chen, Saad Ezzini +3
In recent years, patch representation learning has emerged as a necessary research direction for exploiting the capabilities of machine learning in software generation. These repre…
Hyperbolic Code Retrieval: A Novel Approach for Efficient Code Search Using Hyperbolic Space Embeddings
Xunzhu Tang, zhenghan Chen, Saad Ezzini +4
Within the realm of advanced code retrieval, existing methods have primarily relied on intricate matching and attention-based mechanisms. However, these methods often lead to compu…
Multilevel Semantic Embedding of Software Patches: A Fine-to-Coarse Grained Approach Towards Security Patch Detection
Xunzhu Tang, zhenghan Chen, Saad Ezzini +4
The growth of open-source software has increased the risk of hidden vulnerabilities that can affect downstream software applications. This concern is further exacerbated by softwar…
Learning to Represent Patches
Xunzhu Tang, Haoye Tian, Zhenghan Chen +6
Patch representation is crucial in automating various software engineering tasks, like determining patch accuracy or summarizing code changes. While recent research has employed de…
AI-based Question Answering Assistance for Analyzing Natural-language Requirements
Saad Ezzini, Sallam Abualhaija, Chetan Arora +1
By virtue of being prevalently written in natural language (NL), requirements are prone to various defects, e.g., inconsistency and incompleteness. As such, requirements are freque…
TAPHSIR: Towards AnaPHoric Ambiguity Detection and ReSolution In Requirements
Saad Ezzini, Sallam Abualhaija, Chetan Arora +1
We introduce TAPHSIR, a tool for anaphoric ambiguity detection and anaphora resolution in requirements. TAPHSIR facilities reviewing the use of pronouns in a requirements specifica…
WikiDoMiner: Wikipedia Domain-specific Miner
Saad Ezzini, Sallam Abualhaija, Mehrdad Sabetzadeh
We introduce WikiDoMiner, a tool for automatically generating domain-specific corpora by crawling Wikipedia. WikiDoMiner helps requirements engineers create an external knowledge r…