FORGE - researchr conference series publications

researchr

You are not signed in
Sign in
Sign up

Viewing Publication 1 - 49 from 49

2025

PerfCodeGen: Improving Performance of LLM Generated Code with Execution FeedbackYun Peng 0003, Akhilesh Deepak Gotmare, Michael R. Lyu, Caiming Xiong, Silvio Savarese, Doyen Sahoo. forge 2025: 1-13 [doi]

Cyber-Attack Detection and Localization for SCADA system of CPSsDan Li 0016, Junnan Tang, Shunyu Wu, Zibin Zheng, See-Kiong Ng. forge 2025: 269-279 [doi]

IEEE/ACM Second International Conference on AI Foundation Models and Software Engineering, Forge@ICSE 2025, Ottawa, ON, Canada, April 27-28, 2025IEEE, 2025. [doi]

Augmenting Large Language Models with Static Code Analysis for Automated Code Quality ImprovementsSeyed Moein Abtahi, Akramul Azim. forge 2025: 82-92 [doi]

Resource-Efficient & Effective Code SummarizationSaima Afrin, Joseph Call, Khai-Nguyen Nguyen, Oscar Chaparro, Antonio Mastropaolo. forge 2025: 224-235 [doi]

Benchmarking Prompt Engineering Techniques for Secure Code Generation with GPT ModelsMarc Bruni, Fabio Gabrielli, Mohammad Ghafari, Martin Kropp. forge 2025: 93-103 [doi]

PyResBugs: A Dataset of Residual Python Bugs for Natural Language-Driven Fault InjectionDomenico Cotroneo, Giuseppe De Rosa, Pietro Liguori. forge 2025: 146-150 [doi]

Automated Codebase Reconciliation using Large Language ModelsAneri Gandhi, Sanjukta De, Marsha Chechik, Vinay Pandit, Max Kiehn, Matthieu Chan Chee, Yonas Bedasso. forge 2025: 1-11 [doi]

Vulnerability-Triggering Test Case Generation from Third-Party LibrariesYi Gao, Xing Hu 0008, Zirui Chen, Tongtong Xu, Xiaohu Yang 0001. forge 2025: 125-135 [doi]

"So what if I used GenAI?" - Legal Implications of Using Cloud-based GenAI in Software Engineering ResearchGouri Ginde. forge 2025: 241-245 [doi]

A Comprehensive Study of Bug Characteristics on Foundation Language ModelsJunxiao Han, Guanqi Wang, Jiakun Liu, Lingfeng Bao, Xing Hu 0008, Jinling Wei, ShuiGuang Deng. forge 2025: 257-268 [doi]

ELDetector: An Automated Approach Detecting Endless-loop in Mini ProgramsNan Hu, Ming Fan 0002, Jingyi Lei, Jiaying He, Zhe Hou. forge 2025: 104-112 [doi]

Enhancing Pull Request Reviews: Leveraging Large Language Models to Detect Inconsistencies Between Issues and Pull RequestsAli Tunahan Isik, Hatice Kübra Çaglar, Eray Tüzün. forge 2025: 168-178 [doi]

The Heap: A Contamination-Free Multilingual Code Dataset for Evaluating Large Language ModelsJonathan Katzy, Razvan Mihai Popescu, Arie van Deursen, Maliheh Izadi. forge 2025: 151-155 [doi]

CodeFlow: Program Behavior Prediction with Dynamic Dependencies LearningCuong Chi Le, Hoang Nhat Phan, Huy Nhat Phan, Tien N. Nguyen, Nghi D. Q. Bui. forge 2025: 192-203 [doi]

HyRACC: A Hybrid Retrieval-Augmented Framework for More Efficient Code CompletionChuanyi Li, Jiwei Shang, Yi Feng 0005, Bin Luo 0003. forge 2025: 61-66 [doi]

OptCodeTrans: Boost LLMs on Low-Resource Programming Language TranslationJianbo Lin, Yi Shen, Chuanyi Li, Changan Niu, Bin Luo 0003. forge 2025: 67-72 [doi]

Testing Android Third Party Libraries with LLMs to Detect Incompatible APIsTarek Mahmud, Bin Duan, Meiru Che, Anne H. H. Ngu, Guowei Yang 0001. forge 2025: 280-291 [doi]

Microservices Performance Testing with Causality-enhanced Large Language ModelsCristian Mascia, Antonio Guerriero, Luca Giamattei, Roberto Pietrantuono, Stefano Russo 0001. forge 2025: 136-140 [doi]

Skill over Scale: The Case for Medium, Domain-Specific Models for SEManisha Mukherjee, Vincent J. Hellendoorn. forge 2025: 212-223 [doi]

AgileCoder: Dynamic Collaborative Agents for Software Development based on Agile MethodologyMinh Huynh Nguyen, Thang Phan Chau, Phong X. Nguyen, Nghi D. Q. Bui. forge 2025: 156-167 [doi]

MaRV: A Manually Validated Refactoring DatasetHenrique Nunes, Tushar Sharma, Eduardo Figueiredo. forge 2025: 141-145 [doi]

Towards Generating App Feature Descriptions Automatically with LLMs: the Setapp Case StudyYevhenii Peteliev, Ivan Synytsia, Nataliia Stulova. forge 2025: 252-256 [doi]

SwiftEval: Developing a Language-Specific Benchmark for LLM-generated Code EvaluationIvan Petrukha, Yana Kurliak, Nataliia Stulova. forge 2025: 73-77 [doi]

RepoHyper: Search-Expand-Refine on Semantic Graphs for Repository-Level Code CompletionHuy Nhat Phan, Hoang Nhat Phan, Tien N. Nguyen, Nghi D. Q. Bui. forge 2025: 14-25 [doi]

Extracting Fix Ingredients using Language ModelsJulian Aron Prenner, Romain Robbes. forge 2025: 179-191 [doi]

Evaluating the Ability of GPT-4o to Generate Verifiable Specifications in VeriFastMarilyn Rego, Wen Fan, Xin Hu, Sanya Dod, Zhaorui Ni, Danning Xie, Jenna DiVincenzo, Lin Tan 0001. forge 2025: 246-251 [doi]

SoTaNa: An Open-Source Software Engineering Instruction-Tuned ModelEnsheng Shi, Yanlin Wang 0001, Fengji Zhang, Bei Chen, Hongyu Zhang 0002, Yanli Wang, Daya Guo, Lun Du, Shi Han, Dongmei Zhang 0001, Hongbin Sun 0001. forge 2025: 1-12 [doi]

AI-Powered, But Power-Hungry? Energy Efficiency of LLM-Generated CodeLola Solovyeva, Sophie Weidmann, Fernando Castor. forge 2025: 49-60 [doi]

How Developers Interact with AI: A Taxonomy of Human-AI Collaboration in Software EngineeringChristoph Treude, Marco Aurélio Gerosa. forge 2025: 236-240 [doi]

Testing Refactoring Engine via Historical Bug Report driven LLMHaibo Wang, Zhuolin Xu, Shin Hwei Tan. forge 2025: 113-124 [doi]

Addressing Specific and Complex Scenarios in Semantic ParsingYu Wang, Ming Fan, Ting Liu. forge 2025: 204-211 [doi]

SE Arena: An Interactive Platform for Evaluating Foundation Models in Software EngineeringZhiMin Zhao. forge 2025: 78-81 [doi]

2024

Proceedings of the 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering, FORGE 2024, Lisbon, Portugal, 14 April 2024David Lo 0001, Xin Xia 0001, Massimiliano Di Penta, Xing Hu 0008, editors, ACM, 2024. [doi]

PathOCL: Path-Based Prompt Augmentation for OCL Generation with GPT-4Seif Abukhalaf, Mohammad Hamdaqa, Foutse Khomh. forge 2024: 108-118 [doi]

Creative and Correct: Requesting Diverse Code Solutions from AI Foundation ModelsScott Blyth, Christoph Treude, Markus Wagner 0007. forge 2024: 119-123 [doi]

Planning to Guide LLM for Code Coverage PredictionHridya Dhulipala, Aashish Yadavally, Tien N. Nguyen. forge 2024: 24-34 [doi]

An Exploratory Investigation into Code License Infringements in Large Language Model Training DatasetsJonathan Katzy, Razvan Mihai Popescu, Arie van Deursen, Maliheh Izadi. forge 2024: 74-85 [doi]

Fine Tuning Large Language Model for Secure Code GenerationJunjie Li, Aseem Sangalay, Cheng Cheng, Yuan Tian, Jinqiu Yang 0001. forge 2024: 86-90 [doi]

Exploring the Impact of the Output Format on the Evaluation of Large Language Models for Code TranslationMarcos Macedo, Yuan Tian 0008, Filipe Roseiro Côgo, Bram Adams. forge 2024: 57-68 [doi]

On Evaluating the Efficiency of Source Code Generated by LLMsChangan Niu, Ting Zhang, Chuanyi Li, Bin Luo 0003, Vincent Ng 0001. forge 2024: 103-107 [doi]

Assessing the Impact of GPT-4 Turbo in Generating Defeaters for Assurance CasesKimya Khakzad Shahandashti, Mithila Sivakumar, Mohammad Mahdi Mohajer, Alvine Boaye Belle, Song Wang 0009, Timothy Lethbridge. forge 2024: 52-56 [doi]

Investigating the Performance of Language Models for Completing Code in Functional Programming Languages: a Haskell Case StudyTim van Dam, Frank van der Heijden, Philippe de Bekker, Berend Nieuwschepen, Marc Otten, Maliheh Izadi. forge 2024: 91-102 [doi]

The Emergence of Large Language Models in Static Analysis: A First Look through Micro-BenchmarksAshwin Prasad Shivarpatna Venkatesh, Samkutty Sabu, Amir M. Mir, Sofia Reis, Eric Bodden. forge 2024: 35-39 [doi]

Is Attention All You Need? Toward a Conceptual Model for Social Awareness in Large Language ModelsGianmario Voria, Gemma Catolino, Fabio Palomba. forge 2024: 69-73 [doi]

Deep Multiple Assertions GenerationHailong Wang, Tongtong Xu, Bei Wang. forge 2024: 1-11 [doi]

MeTMaP: Metamorphic Testing for Detecting False Vector Matching Problems in LLM Augmented GenerationGuanyu Wang, Yuekang Li, Yi Liu, Gelei Deng, Tianlin Li, Guosheng Xu 0001, Yang Liu, Haoyu Wang 0001, Kailong Wang. forge 2024: 12-23 [doi]

Reality Bites: Assessing the Realism of Driving Scenarios with Large Language ModelsJiahui Wu, Chengjie Lu, Aitor Arrieta, Tao Yue 0002, Shaukat Ali 0001. forge 2024: 40-51 [doi]

Commit Message Generation via ChatGPT: How Far Are We?Yifan Wu, Ying Li, Siyu Yu. forge 2024: 124-129 [doi]

Sign in or sign up to see more results.

runs on WebDSL