Fabio Calefato

1.7k total citations
68 papers, 844 citations indexed

About

Fabio Calefato is a scholar working on Information Systems, Artificial Intelligence and Computer Science Applications. According to data from OpenAlex, Fabio Calefato has authored 68 papers receiving a total of 844 indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Information Systems, 23 papers in Artificial Intelligence and 17 papers in Computer Science Applications. Recurrent topics in Fabio Calefato's work include Software Engineering Techniques and Practices (24 papers), Software Engineering Research (22 papers) and Open Source Software Innovations (14 papers). Fabio Calefato is often cited by papers focused on Software Engineering Techniques and Practices (24 papers), Software Engineering Research (22 papers) and Open Source Software Innovations (14 papers). Fabio Calefato collaborates with scholars based in Italy, Brazil and United States. Fabio Calefato's co-authors include Filippo Lanubile, Nicole Novielli, Daniela Damian, Rafael Prikladnicki, Bogdan Vasilescu, Christof Ebert, Tayana Conte, Pasquale Minervini, Marco Aurélio Gerosa and Marcos Kalinowski and has published in prestigious journals such as IEEE Software, Journal of Systems and Software and Information and Software Technology.

In The Last Decade

Fabio Calefato

61 papers receiving 800 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Fabio Calefato Italy 17 570 263 221 115 99 68 844
Vibha Singhal Sinha India 13 517 0.9× 494 1.9× 184 0.8× 170 1.5× 52 0.5× 36 1.0k
John Noll Ireland 17 606 1.1× 133 0.5× 301 1.4× 93 0.8× 159 1.6× 60 977
Alexey Zagalsky Canada 12 528 0.9× 228 0.9× 397 1.8× 50 0.4× 136 1.4× 15 814
Sherlock A. Licorish New Zealand 17 597 1.0× 122 0.5× 272 1.2× 75 0.7× 56 0.6× 69 1.0k
Juan Manuel Dodero Spain 18 423 0.7× 201 0.8× 462 2.1× 65 0.6× 44 0.4× 125 1.1k
Susan Elliott Sim United States 16 796 1.4× 285 1.1× 222 1.0× 37 0.3× 34 0.3× 49 1.1k
H. Ulrich Hoppe Germany 17 352 0.6× 185 0.7× 342 1.5× 102 0.9× 86 0.9× 100 967
Budi Arief United Kingdom 12 369 0.6× 102 0.4× 123 0.6× 161 1.4× 76 0.8× 58 654
Davor Čubranić Canada 12 1.1k 1.9× 278 1.1× 281 1.3× 41 0.4× 59 0.6× 23 1.3k
Igor Wiese Brazil 18 787 1.4× 162 0.6× 644 2.9× 59 0.5× 275 2.8× 86 1.1k

Countries citing papers authored by Fabio Calefato

Since Specialization
Citations

This map shows the geographic impact of Fabio Calefato'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 Fabio Calefato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabio Calefato more than expected).

Fields of papers citing papers by Fabio Calefato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fabio Calefato. 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 Fabio Calefato. The network helps show where Fabio Calefato may publish in the future.

Co-authorship network of co-authors of Fabio Calefato

This figure shows the co-authorship network connecting the top 25 collaborators of Fabio Calefato. A scholar is included among the top collaborators of Fabio Calefato based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fabio Calefato. Fabio Calefato is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Calefato, Fabio, et al.. (2025). Diffusion Models for Neuroimaging Data Augmentation: Assessing Realism and Clinical Relevance. Journal of Medical Systems. 49(1). 161–161.
2.
Trinkenreich, Bianca, Fabio Calefato, Geir Kjetil Hanssen, et al.. (2025). Get on the Train or be Left on the Station: Using LLMs for Software Engineering Research. IT University Of Copenhagen (IT University of Copenhagen). 1503–1507.
3.
Calefato, Fabio, et al.. (2024). A multivocal literature review on the benefits and limitations of industry-leading AutoML tools. Information and Software Technology. 178. 107608–107608. 5 indexed citations
4.
Kalinowski, Marcos, et al.. (2024). Professional Insights into Benefits and Limitations of Implementing MLOps Principles. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 305–312. 4 indexed citations
5.
Calefato, Fabio, et al.. (2024). An MLOps Approach for Deploying Machine Learning Models in Healthcare Systems. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 6832–6837. 1 indexed citations
6.
Calefato, Fabio, et al.. (2024). Pynblint: A quality assurance tool to improve the quality of Python Jupyter notebooks. SoftwareX. 28. 101959–101959. 1 indexed citations
7.
Calefato, Fabio, et al.. (2022). Will you come back to contribute? Investigating the inactivity of OSS core developers in GitHub. Empirical Software Engineering. 27(3). 18 indexed citations
8.
Calefato, Fabio, et al.. (2018). [Journal First] Sentiment Polarity Detection for Software Development. International Conference on Software Engineering. 2 indexed citations
9.
Begel, Andrew, Fabio Calefato, & Christoph Treude. (2016). Proceedings of the 8th International Workshop on Social Software Engineering. 1 indexed citations
10.
Calefato, Fabio & Filippo Lanubile. (2016). A Hub-and-Spoke Model for Tool Integration in Distributed Development. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 129–133. 10 indexed citations
11.
Calefato, Fabio, et al.. (2015). Mining Successful Answers in Stack Overflow. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 430–433. 28 indexed citations
12.
Calefato, Fabio, et al.. (2015). Product Line Engineering for NGO Projects. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 6287. 3–6. 1 indexed citations
13.
Calefato, Fabio & Filippo Lanubile. (2012). Augmenting social awareness in a collaborative development environment. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 59. 12–14. 9 indexed citations
14.
Calefato, Fabio & Filippo Lanubile. (2011). A Planning Poker Tool for Supporting Collaborative Estimation in Distributed Agile Development. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 14–19. 7 indexed citations
15.
Calefato, Fabio, et al.. (2007). Towards Social Semantic Suggestive Tagging.. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 2 indexed citations
16.
Calefato, Fabio & Filippo Lanubile. (2006). Plugging presence awareness into Mozilla thunderbird. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 109–114. 2 indexed citations
17.
Lanubile, Filippo, et al.. (2004). Assessing the impact of active guidance for defect detection: a replicated experiment. 269–279. 6 indexed citations
18.
Calefato, Fabio, et al.. (2004). Function clone detection in web applications: a semiautomated approach. Journal of Web Engineering. 3(1). 3–21. 37 indexed citations
19.
Calefato, Fabio. (2004). Peer-to-peer remote conferencing. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 2004. 34–38. 3 indexed citations
20.
Lanubile, Filippo, et al.. (2003). Tool support for geographically dispersed inspection teams. Software Process Improvement and Practice. 8(4). 217–231. 58 indexed citations

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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