Maliheh Izadi

Orcid: 0000-0001-5093-5523

Affiliations:
  • Delft University of Technology, The Netherlands


According to our database1, Maliheh Izadi authored at least 53 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
The Impact of Generative AI on Creativity in Software Development: A Research Agenda.
ACM Trans. Softw. Eng. Methodol., June, 2025

Human-AI Experience in Integrated Development Environments: A Systematic Literature Review.
CoRR, March, 2025

Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Enhancement Protocol.
CoRR, March, 2025

Code Red! On the Harmfulness of Applying Off-the-Shelf Large Language Models to Programming Tasks.
Proc. ACM Softw. Eng., 2025

Enhancing Human-IDE Interaction in the SDLC using LLM-based Mediator Agents.
Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering, 2025

HyperSeq: A Hyper-Adaptive Representation for Predictive Sequencing of States.
Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering, 2025

A Multi-agent Onboarding Assistant based on Large Language Models, Retrieval Augmented Generation, and Chain-of-Thought.
Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering, 2025

A Qualitative Investigation into LLM-Generated Multilingual Code Comments and Automatic Evaluation Metrics.
Proceedings of the 21st International Conference on Predictive Models and Data Analytics in Software Engineering, 2025

Message from NLBSE 2025 Program Chairs.
Proceedings of the IEEE/ACM International Workshop on Natural Language-Based Software Engineering, 2025

How Much Do Code Language Models Remember? An Investigation on Data Extraction Attacks Before and After Fine-tuning.
Proceedings of the 22nd IEEE/ACM International Conference on Mining Software Repositories, 2025

Automating the Detection of Code Vulnerabilities by Analyzing GitHub Issues.
Proceedings of the IEEE/ACM International Workshop on Large Language Models for Code, 2025

When People Come First: A Human-Centered Approach to Computer Science Education.
Proceedings of the 30th ACM Conference on Innovation and Technology in Computer Science Education V. 2, 2025

Rethinking IDE Customization for Enhanced HAX: A Hyperdimensional Perspective.
Proceedings of the IEEE/ACM Second IDE Workshop, 2025

Leveraging Large Language Models for Enhancing the Understandability of Generated Unit Tests.
Proceedings of the 47th IEEE/ACM International Conference on Software Engineering, 2025

The Heap: A Contamination-Free Multilingual Code Dataset for Evaluating Large Language Models.
Proceedings of the IEEE/ACM Second International Conference on AI Foundation Models and Software Engineering, 2025

2024
Correction to: The potential of an adaptive computerized dynamic assessment tutor in diagnosing and assessing learners' listening comprehension.
Educ. Inf. Technol., October, 2024

The potential of an adaptive computerized dynamic assessment tutor in diagnosing and assessing learners' listening comprehension.
Educ. Inf. Technol., February, 2024

Generative AI in Software Engineering Must Be Human-Centered: The Copenhagen Manifesto.
J. Syst. Softw., 2024

The Design Space of in-IDE Human-AI Experience.
CoRR, 2024

Long Code Arena: a Set of Benchmarks for Long-Context Code Models.
CoRR, 2024

Creativity, Generative AI, and Software Development: A Research Agenda.
CoRR, 2024

In-IDE Human-AI Experience in the Era of Large Language Models; A Literature Review.
Proceedings of the 1st ACM/IEEE Workshop on Integrated Development Environments, 2024

Maven Unzipped: Exploring the Impact of Library Packaging on the Ecosystem.
Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2024

Language Models for Code Completion: A Practical Evaluation.
Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024

Traces of Memorisation in Large Language Models for Code.
Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024

An Exploratory Investigation into Code License Infringements in Large Language Model Training Datasets.
Proceedings of the 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering, 2024

Investigating the Performance of Language Models for Completing Code in Functional Programming Languages: a Haskell Case Study.
Proceedings of the 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering, 2024

A Transformer-Based Approach for Smart Invocation of Automatic Code Completion.
Proceedings of the 1st ACM International Conference on AI-Powered Software, 2024

2023
On the Impact of Language Selection for Training and Evaluating Programming Language Models.
Dataset, August, 2023

Semantically-enhanced topic recommendation systems for software projects.
Empir. Softw. Eng., March, 2023

Targeted Attack on GPT-Neo for the SATML Language Model Data Extraction Challenge.
CoRR, 2023

Extending Source Code Pre-Trained Language Models to Summarise Decompiled Binaries.
CoRR, 2023

Extending Source Code Pre-Trained Language Models to Summarise Decompiled Binarie.
Proceedings of the IEEE International Conference on Software Analysis, 2023

On the Impact of Language Selection for Training and Evaluating Programming Language Models.
Proceedings of the 23rd IEEE International Working Conference on Source Code Analysis and Manipulation, 2023

The NLBSE'23 Tool Competition.
Proceedings of the 2nd IEEE/ACM International Workshop on Natural Language-Based Software Engineering, 2023

STACC: Code Comment Classification using SentenceTransformers.
Proceedings of the 2nd IEEE/ACM International Workshop on Natural Language-Based Software Engineering, 2023

The (ab)use of Open Source Code to Train Large Language Models.
Proceedings of the 2nd IEEE/ACM International Workshop on Natural Language-Based Software Engineering, 2023

Enriching Source Code with Contextual Data for Code Completion Models: An Empirical Study.
Proceedings of the 20th IEEE/ACM International Conference on Mining Software Repositories, 2023

2022
CAPYBARA: Decompiled Binary Functions and Related Summaries.
Dataset, October, 2022

BinT5: Binary Code Summarisation Model.
Dataset, October, 2022

Predicting the objective and priority of issue reports in software repositories.
Empir. Softw. Eng., 2022

LinkFormer: Automatic Contextualised Link Recovery of Software Artifacts in both Project-based and Transfer Learning Settings.
CoRR, 2022

Semantically-enhanced Topic Recommendation System for Software Projects.
CoRR, 2022

On the Evaluation of NLP-based Models for Software Engineering.
Proceedings of the 2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE 2022), 2022

CatIss: An Intelligent Tool for Categorizing Issues Reports using Transformers.
Proceedings of the 2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE 2022), 2022

CodeFill: Multi-token Code Completion by Jointly learning from Structure and Naming Sequences.
Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

2021
Topic recommendation for software repositories using multi-label classification algorithms.
Empir. Softw. Eng., 2021

Automated Recovery of Issue-Commit Links Leveraging Both Textual and Non-textual Data.
Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2021

2020
Generating summaries for methods of event-driven programs: An Android case study.
J. Syst. Softw., 2020

Predicting the Objective and Priority of Issue Reports in a Cross project Context.
CoRR, 2020

Topic Recommendation for Software Repositories using Multi-label Classification Algorithms.
CoRR, 2020

Improving Quality of a Post's Set of Answers in Stack Overflow.
Proceedings of the 46th Euromicro Conference on Software Engineering and Advanced Applications, 2020

2018
Evaluating Collaborative Filtering Recommender Algorithms: A Survey.
IEEE Access, 2018


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