Aryaz Eghbali

417 citations
7 papers · 190 · 1 hit paper · h-index 5

Impact in

  • Software top 5%
    • Software Testing and Debugging Techniques
    • Software Reliability and Analysis Research
    • Software Engineering Research

Papers in

    • Software Engineering Research 7
    • Web Application Security Vulnerabilities 1
    • Software Testing and Debugging Techniques 6
Journals
IEEE Transactions on Software Engineering (1 paper)Proceedings of the ACM on software engineering. (1 paper)

In The Last Decade

Aryaz Eghbali

6 papers receiving 186 citations

Aryaz Eghbali's Hit Papers

An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation 2023 · 129 citations
1290+1+2Years since publication4080120

Peers

Aryaz Eghbali
Comparison fields: 5 of 27
  • Software 107
  • Information Systems 110
  • Hardware and Architecture 16
  • Health Informatics 3
  • Signal Processing 19
Replace Yuchao Huang with:
Yuchao Huang Canada
Daoguang Zan China
Vijayaraghavan Murali United States
Moshi Wei Canada
Alexandru Marginean United Kingdom
Zoltán Porkoláb Hungary
Quanjun Zhang China
Vadim Zaytsev Netherlands
Adrian Lienhard Switzerland
Mahesh Shirole India
Aryaz Eghbali relative to Yuchao Huang Canada Yuchao Huang's profile →
Citations per field
00.5×1.5×
Yuchao Huang · 1×
Citations per year

Countries citing papers authored by Aryaz Eghbali

Since Specialization
Citations

This map shows the geographic impact of Aryaz Eghbali's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Aryaz Eghbali with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aryaz Eghbali more than expected).

Fields of papers citing papers by Aryaz Eghbali

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aryaz Eghbali. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Aryaz Eghbali. The network helps show where Aryaz Eghbali may publish in the future.

Co-authors

The 3 scholars most cited alongside Aryaz Eghbali, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Aryaz Eghbali Line = papers co-authored together Aryaz Eghbali links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1
An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation
Hit paper breakdown →
2023129
2 202217
3 202217
4 202012
5 202212
6 20223
7 20250

About Aryaz Eghbali

Aryaz Eghbali is a scholar working on Information Systems, Software, Signal Processing, Artificial Intelligence and Hardware and Architecture, having authored 7 papers that have together received 190 indexed citations. Recurring topics across this work include Software Engineering Research (7 papers), Software Testing and Debugging Techniques (6 papers), Advanced Malware Detection Techniques (3 papers), Natural Language Processing Techniques (2 papers), Parallel Computing and Optimization Techniques (1 paper), Topic Modeling (1 paper) and Web Application Security Vulnerabilities (1 paper). The work is most often cited by research in Software (107 citations), Information Systems (110 citations), Hardware and Architecture (16 citations), Health Informatics (3 citations) and Signal Processing (19 citations). Aryaz Eghbali has collaborated with scholars based in Germany, Canada and United States. Frequent co-authors include Sarah Nadi, Frank Tip and Michael Pradel. Their work appears in journals such as IEEE Transactions on Software Engineering and Proceedings of the ACM on software engineering..

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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