Paolo Arcaini
- Software top 0.5%
- Software Testing and Debugging Techniques 63
- Software Reliability and Analysis Research 41
- Artificial Intelligence top 2%
- Advanced Software Engineering Methodologies 24
- Quantum Computing Algorithms and Architecture 18
- Adversarial Robustness in Machine Learning 13
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- Formal Methods in Verification 35
- Information Systems top 2%
- Software Engineering Research 21
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety 14
- Co-authors
- Elvinia RiccobenePatrizia ScandurraAngelo GargantiniShaukat AliFuyuki IshikawaTao YueXiao–Yi ZhangP. Vavassori
- Journals
- SHILAP Revista de lepidopterología (1 paper)Information Sciences (1 paper)IEEE Transactions on Software Engineering (4 papers)
In The Last Decade
Paolo Arcaini
137 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 67
- Software 598
- Artificial Intelligence 621
- Computational Theory and Mathematics 271
- Information Systems 380
- Automotive Engineering 190
Countries citing papers authored by Paolo Arcaini
This map shows the geographic impact of Paolo Arcaini'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 Paolo Arcaini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paolo Arcaini more than expected).
Fields of papers citing papers by Paolo Arcaini
This network shows the impact of papers produced by Paolo Arcaini. 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 Paolo Arcaini. The network helps show where Paolo Arcaini may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Paolo Arcaini, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 9 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 3 | |
| 7 | 2024 | 3 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 1 | |
| 10 | 2024 | 3 | |
| 11 | 2024 | 7 | |
| 12 | 2023 | 3 | |
| 13 | 2023 | 9 | |
| 14 | 2023 | 5 | |
| 15 | 2023 | 4 | |
| 16 | 2023 | 1 | |
| 17 | 2022 | 20 | |
| 18 | 2022 | 2 | |
| 19 | 2015 | 69 | |
| 20 | Automatic Review of Abstract State Machines by Meta-Property Verification ! | 2010 | 14 |
About Paolo Arcaini
Paolo Arcaini is a scholar working on Software, Computational Theory and Mathematics and Artificial Intelligence, having authored 147 papers that have together received 1.3k indexed citations. Recurring topics across this work include Software Testing and Debugging Techniques (63 papers), Software Reliability and Analysis Research (41 papers), Formal Methods in Verification (35 papers), Advanced Software Engineering Methodologies (24 papers), Software Engineering Research (21 papers), Quantum Computing Algorithms and Architecture (18 papers), Autonomous Vehicle Technology and Safety (14 papers) and Adversarial Robustness in Machine Learning (13 papers). The work is most often cited by research in Software (598 citations), Artificial Intelligence (621 citations) and Computational Theory and Mathematics (271 citations). Paolo Arcaini has collaborated with scholars based in Japan, Italy and China. Frequent co-authors include Elvinia Riccobene, Patrizia Scandurra, Angelo Gargantini, Shaukat Ali, Fuyuki Ishikawa, Tao Yue, Xiao–Yi Zhang, P. Vavassori, Zhenya Zhang and Florian Hauer. Their work appears in journals such as SHILAP Revista de lepidopterología, Information Sciences and IEEE Transactions 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.