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Fatemeh Hendijani Fard
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2020 – today
- 2024
- [j6]Iman Saberi, Fatemeh H. Fard, Fuxiang Chen:
Utilization of pre-trained language models for adapter-based knowledge transfer in software engineering. Empir. Softw. Eng. 29(4): 94 (2024) - [j5]Mohamad Khajezade, Fatemeh H. Fard, Mohamed S. Shehata:
Evaluating few-shot and contrastive learning methods for code clone detection. Empir. Softw. Eng. 29(6): 163 (2024) - [c35]Fatemeh H. Fard:
Technical Briefing on Parameter Efficient Fine-Tuning of (Large) Language Models for Code-Intelligence. ICSE Companion 2024: 434-435 - [c34]Mohamad Khajezade, Jie JW Wu, Fatemeh Hendijani Fard, Gema Rodríguez-Pérez, Mohamed Sami Shehata:
Investigating the Efficacy of Large Language Models for Code Clone Detection. ICPC 2024: 161-165 - [c33]Zixiao Zhao, Millon Madhur Das, Fatemeh H. Fard:
Studying Vulnerable Code Entities in R. ICPC 2024: 328-332 - [i28]Mohamad Khajezade, Jie JW Wu, Fatemeh Hendijani Fard, Gema Rodríguez-Pérez, Mohamed Sami Shehata:
Investigating the Efficacy of Large Language Models for Code Clone Detection. CoRR abs/2401.13802 (2024) - [i27]Zixiao Zhao, Millon Madhur Das, Fatemeh H. Fard:
Studying Vulnerable Code Entities in R. CoRR abs/2402.04421 (2024) - [i26]Amirreza Esmaeili, Iman Saberi, Fatemeh H. Fard:
Empirical Studies of Parameter Efficient Methods for Large Language Models of Code and Knowledge Transfer to R. CoRR abs/2405.01553 (2024) - [i25]Jie JW Wu, Fatemeh H. Fard:
Benchmarking the Communication Competence of Code Generation for LLMs and LLM Agent. CoRR abs/2406.00215 (2024) - [i24]Davit Abrahamyan, Fatemeh H. Fard:
StackRAG Agent: Improving Developer Answers with Retrieval-Augmented Generation. CoRR abs/2406.13840 (2024) - [i23]Meghdad Dehghan, Jie JW Wu, Fatemeh H. Fard, Ali Ouni:
MergeRepair: An Exploratory Study on Merging Task-Specific Adapters in Code LLMs for Automated Program Repair. CoRR abs/2408.09568 (2024) - [i22]Emmanuel Iko-Ojo Simon, Chirath Hettiarachchi, Alex Potanin, Hanna Suominen, Fatemeh Hendijani Fard:
Automated Detection of Algorithm Debt in Deep Learning Frameworks: An Empirical Study. CoRR abs/2408.10529 (2024) - [i21]Sathvik Joel, Jie JW Wu, Fatemeh H. Fard:
Survey on Code Generation for Low resource and Domain Specific Programming Languages. CoRR abs/2410.03981 (2024) - [i20]Zixiao Zhao, Fatemeh H. Fard:
Do Current Language Models Support Code Intelligence for R Programming Language? CoRR abs/2410.07793 (2024) - 2023
- [j4]Mohammad Abdul Hadi, Fatemeh H. Fard:
Evaluating pre-trained models for user feedback analysis in software engineering: a study on classification of app-reviews. Empir. Softw. Eng. 28(4): 88 (2023) - [c32]Emmanuel Iko-Ojo Simon, Melina C. Vidoni, Fatemeh H. Fard:
Algorithm Debt: Challenges and Future Paths. CAIN 2023: 90-91 - [c31]Ramin Shahbazi, Fatemeh Hendijani Fard:
APIContext2Com: Code Comment Generation by Incorporating Pre-Defined API Documentation. ICPC 2023: 13-24 - [c30]Iman Saberi, Fatemeh H. Fard:
Model-Agnostic Syntactical Information for Pre-Trained Programming Language Models. MSR 2023: 183-193 - [i19]Ramin Shahbazi, Fatemeh H. Fard:
APIContext2Com: Code Comment Generation by Incorporating Pre-Defined API Documentation. CoRR abs/2303.01645 (2023) - [i18]Iman Saberi, Fatemeh H. Fard:
Model-Agnostic Syntactical Information for Pre-Trained Programming Language Models. CoRR abs/2303.06233 (2023) - [i17]Iman Saberi, Fatemeh H. Fard, Fuxiang Chen:
Multilingual Adapter-based Knowledge Aggregation on Code Summarization for Low-Resource Languages. CoRR abs/2307.07854 (2023) - [i16]Iman Saberi, Fatemeh H. Fard, Fuxiang Chen:
Utilization of Pre-trained Language Model for Adapter-based Knowledge Transfer in Software Engineering. CoRR abs/2307.08540 (2023) - 2022
- [j3]Rishab Sharma, Ramin Shahbazi, Fatemeh H. Fard, Zadia Codabux, Melina C. Vidoni:
Self-admitted technical debt in R: detection and causes. Autom. Softw. Eng. 29(2): 53 (2022) - [j2]Steffen Herbold, Alexander Trautsch, Benjamin Ledel, Alireza Aghamohammadi, Taher Ahmed Ghaleb, Kuljit Kaur Chahal, Tim Bossenmaier, Bhaveet Nagaria, Philip Makedonski, Matin Nili Ahmadabadi, Kristof Szabados, Helge Spieker, Matej Madeja, Nathaniel Hoy, Valentina Lenarduzzi, Shangwen Wang, Gema Rodríguez-Pérez, Ricardo Colomo Palacios, Roberto Verdecchia, Paramvir Singh, Yihao Qin, Debasish Chakroborti, Willard Davis, Vijay Walunj, Hongjun Wu, Diego Marcilio, Omar Alam, Abdullah Aldaeej, Idan Amit, Burak Turhan, Simon Eismann, Anna-Katharina Wickert, Ivano Malavolta, Matús Sulír, Fatemeh H. Fard, Austin Z. Henley, Stratos Kourtzanidis, Eray Tuzun, Christoph Treude, Simin Maleki Shamasbi, Ivan Pashchenko, Marvin Wyrich, James Davis, Alexander Serebrenik, Ella Albrecht, Ethem Utku Aktas, Daniel Strüber, Johannes Erbel:
A fine-grained data set and analysis of tangling in bug fixing commits. Empir. Softw. Eng. 27(6): 125 (2022) - [j1]Melina C. Vidoni, Zadia Codabux, Fatemeh H. Fard:
Infinite technical debt. J. Syst. Softw. 190: 111336 (2022) - [c29]Rishab Sharma, Fuxiang Chen, Fatemeh H. Fard:
LAMNER: code comment generation using character language model and named entity recognition. ICPC 2022: 48-59 - [c28]Divyam Goel, Ramansh Grover, Fatemeh H. Fard:
On the cross-modal transfer from natural language to code through adapter modules. ICPC 2022: 71-81 - [c27]Mohammad Abdul Hadi, Imam Nur Bani Yusuf, Ferdian Thung, Kien Gia Luong, Lingxiao Jiang, Fatemeh H. Fard, David Lo:
On the effectiveness of pretrained models for API learning. ICPC 2022: 309-320 - [c26]Kien Luong, Mohammad Abdul Hadi, Ferdian Thung, Fatemeh H. Fard, David Lo:
ARSeek: identifying API resource using code and discussion on stack overflow. ICPC 2022: 331-342 - [c25]Fuxiang Chen, Fatemeh H. Fard, David Lo, Timofey Bryksin:
On the transferability of pre-trained language models for low-resource programming languages. ICPC 2022: 401-412 - [c24]Rishab Sharma, Fuxiang Chen, Fatemeh H. Fard, David Lo:
An exploratory study on code attention in BERT. ICPC 2022: 437-448 - [i15]Yue Cao, Fatemeh H. Fard:
Pre-Trained Neural Language Models for Automatic Mobile App User Feedback Answer Generation. CoRR abs/2202.02294 (2022) - [i14]Mohammad Abdul Hadi, Imam Nur Bani Yusuf, Ferdian Thung, Kien Gia Luong, Lingxiao Jiang, Fatemeh H. Fard, David Lo:
On the Effectiveness of Pretrained Models for API Learning. CoRR abs/2204.03498 (2022) - [i13]Mohamad Khajezade, Fatemeh Hendijani Fard, Mohamed S. Shehata:
Evaluating few shot and Contrastive learning Methods for Code Clone Detection. CoRR abs/2204.07501 (2022) - [i12]Divyam Goel, Ramansh Grover, Fatemeh H. Fard:
On The Cross-Modal Transfer from Natural Language to Code through Adapter Modules. CoRR abs/2204.08653 (2022) - [i11]Fuxiang Chen, Fatemeh H. Fard, David Lo, Timofey Bryksin:
On the Transferability of Pre-trained Language Models for Low-Resource Programming Languages. CoRR abs/2204.09653 (2022) - [i10]Rishab Sharma, Fuxiang Chen, Fatemeh H. Fard:
LAMNER: Code Comment Generation Using Character Language Model and Named Entity Recognition. CoRR abs/2204.09654 (2022) - [i9]Rishab Sharma, Fuxiang Chen, Fatemeh H. Fard, David Lo:
An Exploratory Study on Code Attention in BERT. CoRR abs/2204.10200 (2022) - 2021
- [c23]Mohamad Khajezade, Milad Ramezankhani, Fatemeh Hendijani Fard, Mohamed S. Shehata, Abbas S. Milani:
Toward Using Few-Shot Learning for Prediction of Complex In-Service Defects of Composite Products: A case Study. CCECE 2021: 1-7 - [c22]Rishab Sharma, Fatemeh H. Fard, Apurva Narayan:
Retrieval Enhanced Ensemble Model Framework For Rumor Detection On Micro-blogging Platforms. ICMLA 2021: 227-232 - [c21]Ramin Shahbazi, Rishab Sharma, Fatemeh H. Fard:
API2Com: On the Improvement of Automatically Generated Code Comments Using API Documentations. ICPC 2021: 411-421 - [c20]Yue Cao, Fatemeh H. Fard:
Pre-Trained Neural Language Models for Automatic Mobile App User Feedback Answer Generation. ASE Workshops 2021: 120-125 - [c19]Zadia Codabux, Melina C. Vidoni, Fatemeh H. Fard:
Technical Debt in the Peer-Review Documentation of R Packages: a rOpenSci Case Study. MSR 2021: 195-206 - [i8]Zadia Codabux, Melina C. Vidoni, Fatemeh H. Fard:
Technical Debt in the Peer-Review Documentation of R Packages: a rOpenSci Case Study. CoRR abs/2103.09340 (2021) - [i7]Ramin Shahbazi, Rishab Sharma, Fatemeh H. Fard:
API2Com: On the Improvement of Automatically Generated Code Comments Using API Documentations. CoRR abs/2103.10668 (2021) - [i6]Mohammad Abdul Hadi, Fatemeh H. Fard:
Evaluating Pre-Trained Models for User Feedback Analysis in Software Engineering: A Study on Classification of App-Reviews. CoRR abs/2104.05861 (2021) - [i5]Kien Luong, Mohammad Abdul Hadi, Ferdian Thung, Fatemeh H. Fard, David Lo:
FACOS: Finding API Relevant Contents on Stack Overflow with Semantic and Syntactic Analysis. CoRR abs/2111.07238 (2021) - 2020
- [c18]Mohammad Abdul Hadi, Fatemeh Hendijani Fard, Irene Vrbik:
Geo-Spatial Data Visualization and Critical Metrics Predictions for Canadian Elections. CCECE 2020: 1-7 - [c17]Mohammad Abdul Hadi, Fatemeh Hendijani Fard:
ReviewViz: assisting developers perform empirical study on energy consumption related reviews for mobile applications. MOBILESoft@ICSE 2020: 27-30 - [c16]Aman Yadav, Fatemeh Hendijani Fard:
Semantic analysis of issues on Google play and Twitter. ICSE (Companion Volume) 2020: 308-309 - [c15]Mohammad Abdul Hadi, Fatemeh H. Fard:
AOBTM: Adaptive Online Biterm Topic Modeling for Version Sensitive Short-texts Analysis. ICSME 2020: 593-604 - [c14]Aman Yadav, Rishab Sharma, Fatemeh Hendijani Fard:
A Semantic-Based Framework for Analyzing App Users' Feedback. SANER 2020: 572-576 - [i4]Mohammad Abdul Hadi, Fatemeh H. Fard, Irene Vrbik:
Geo-Spatial Data Visualization and Critical Metrics Predictions for Canadian Elections. CoRR abs/2009.05936 (2020) - [i3]Mohammad Abdul Hadi, Fatemeh H. Fard:
ReviewViz: Assisting Developers Perform Empirical Study on Energy Consumption Related Reviews for Mobile Applications. CoRR abs/2009.06027 (2020) - [i2]Mohammad Abdul Hadi, Fatemeh H. Fard:
AOBTM: Adaptive Online Biterm Topic Modeling for Version Sensitive Short-texts Analysis. CoRR abs/2009.09930 (2020) - [i1]Steffen Herbold, Alexander Trautsch, Benjamin Ledel, Alireza Aghamohammadi, Taher Ahmed Ghaleb, Kuljit Kaur Chahal, Tim Bossenmaier, Bhaveet Nagaria, Philip Makedonski, Matin Nili Ahmadabadi, Kristóf Szabados, Helge Spieker, Matej Madeja, Nathaniel Hoy, Valentina Lenarduzzi, Shangwen Wang, Gema Rodríguez-Pérez, Ricardo Colomo Palacios, Roberto Verdecchia, Paramvir Singh, Yihao Qin, Debasish Chakroborti, Willard Davis, Vijay Walunj, Hongjun Wu, Diego Marcilio, Omar Alam, Abdullah Aldaeej, Idan Amit, Burak Turhan, Simon Eismann, Anna-Katharina Wickert, Ivano Malavolta, Matús Sulír, Fatemeh H. Fard, Austin Z. Henley, Stratos Kourtzanidis, Eray Tuzun, Christoph Treude, Simin Maleki Shamasbi, Ivan Pashchenko, Marvin Wyrich, James Davis, Alexander Serebrenik, Ella Albrecht, Ethem Utku Aktas, Daniel Strüber, Johannes Erbel:
Large-Scale Manual Validation of Bug Fixing Commits: A Fine-grained Analysis of Tangling. CoRR abs/2011.06244 (2020)
2010 – 2019
- 2019
- [c13]Xukun Wang, Matthias Lee, Angie Pinchbeck, Fatemeh H. Fard:
Where Does LDA Sit for GitHub? ASE Workshops 2019: 94-97 - 2018
- [c12]Anja Slama, Fatemeh Hendijani Fard, Behrouz H. Far:
A Hybrid System for Detection of Implied Scenarios in Distributed Software Systems (S). SEKE 2018: 360-359 - 2017
- [c11]Fatemeh Hendijani Fard, Cooper Davies, Frank Maurer:
Agile Emergency Responses Using Collaborative Planning HTN. ISCRAM 2017 - 2016
- [b1]Fatemeh Hendijani Fard:
Detecting and Fixing Emergent Behaviors in Distributed Software Systems Using a Message Content Independent Method. University of Calgary, Alberta, Canada, 2016 - [c10]Dianna Yim, Garance Nicole Loison, Fatemeh Hendijani Fard, Edwin Chan, Alec McAllister, Frank Maurer:
Gesture-driven Interactions on a Virtual Hologram in Mixed Reality. ISS Companion 2016: 55-61 - [c9]Cooper Davies, Jade White, Alec McAllister, Adam Saroka, Omar Addam, Fatemeh Hendijani Fard, Frank Maurer:
A Toolkit for Building Collaborative Immersive Multi-Surface Applications. ISS 2016: 485-488 - 2014
- [c8]Fatemeh Hendijani Fard, Behrouz H. Far:
Detection of implied scenarios in multiagent systems with clustering agents' communications. IRI 2014: 237-244 - [p2]Fatemeh Hendijani Fard, Behrouz H. Far:
Detecting Neutral Nodes in a Network of Heterogeneous Agent Based System. Social Networks: Analysis and Case Studies 2014: 41-60 - [p1]Fatemeh Hendijani Fard, Behrouz H. Far:
On the Usage of Network Visualization for Multiagent System Verification. Online Social Media Analysis and Visualization 2014: 201-228 - 2013
- [c7]Fatemeh Hendijani Fard, Behrouz H. Far:
Visualizing the network of software agents for verification of multiagent systems. ASONAM 2013: 1280-1281 - [c6]Fatemeh Hendijani Fard, Behrouz H. Far:
Detecting a certain kind of emergent behavior in multi agent systems applied on mase methodology. CCECE 2013: 1-4 - [c5]Fatemeh Hendijani Fard, Behrouz H. Far:
Detecting distributed software components that will not cause emergent behavior in asynchronous communication style. IRI 2013: 201-208 - [c4]Fatemeh Hendijani Fard:
Detecting and fixing emergent behaviors in Distributed Software Systems using a message content independent method. ASE 2013: 746-749 - 2012
- [c3]Fatemeh Hendijani Fard, Behrouz H. Far:
Clustering Social Networks to Remove Neutral Nodes. ASONAM 2012: 1289-1294 - [c2]Fatemeh Hendijani Fard, Behrouz H. Far:
A method for detecting agents that will not cause emergent behavior in agent based systems - A case study in agent based auction systems -. IRI 2012: 185-192 - [c1]Fatemeh Hendijani Fard, Behrouz H. Far:
Detecting emergent behavior in autonomous distributed systems with many components of the same type. SMC 2012: 1924-1929
Coauthor Index
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last updated on 2024-11-19 20:49 CET by the dblp team
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