Massimo Narizzano

1.1k total citations
23 papers, 377 citations indexed

About

Massimo Narizzano is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Software. According to data from OpenAlex, Massimo Narizzano has authored 23 papers receiving a total of 377 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computational Theory and Mathematics, 11 papers in Artificial Intelligence and 8 papers in Software. Recurrent topics in Massimo Narizzano's work include Formal Methods in Verification (16 papers), Software Testing and Debugging Techniques (6 papers) and Logic, programming, and type systems (5 papers). Massimo Narizzano is often cited by papers focused on Formal Methods in Verification (16 papers), Software Testing and Debugging Techniques (6 papers) and Logic, programming, and type systems (5 papers). Massimo Narizzano collaborates with scholars based in Italy, Germany and Spain. Massimo Narizzano's co-authors include Armando Tacchella, Enrico Giunchiglia, Francesco Cardinale, Gabriele Arnulfo, Marco Fato, Luca Pulina, Elena De Momi, J. Matias Palva, Martin Tisdall and Serena Ricci and has published in prestigious journals such as BMC Bioinformatics, Artificial Intelligence and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

In The Last Decade

Massimo Narizzano

20 papers receiving 355 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Massimo Narizzano Italy 11 120 115 104 81 65 23 377
Narayanan Krishnamurthy United States 11 46 0.4× 17 0.1× 55 0.5× 6 0.1× 78 1.2× 34 476
Thomas Klotz Germany 11 73 0.6× 45 0.4× 21 0.2× 5 0.1× 57 0.9× 35 353
Bernhard H. C. Sputh United Kingdom 7 25 0.2× 137 1.2× 60 0.6× 7 0.1× 14 0.2× 26 266
John V. Guttag United States 4 15 0.1× 296 2.6× 62 0.6× 53 0.7× 6 0.1× 6 386
Ryan Cunningham United Kingdom 9 11 0.1× 11 0.1× 72 0.7× 10 0.1× 61 0.9× 27 258
Serdar Kadıoğlu United States 8 19 0.2× 46 0.4× 120 1.2× 8 0.1× 3 0.0× 27 298
Mitra Mirzarezaee Iran 10 18 0.1× 70 0.6× 73 0.7× 20 0.2× 15 0.2× 36 280
Yannick Moy France 8 96 0.8× 22 0.2× 92 0.9× 4 0.0× 113 1.7× 25 245
Josefa Díaz‐Álvarez Spain 10 8 0.1× 63 0.5× 69 0.7× 65 0.8× 4 0.1× 23 242
Fariborz Mahmoudi Iran 12 12 0.1× 80 0.7× 113 1.1× 69 0.9× 52 478

Countries citing papers authored by Massimo Narizzano

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Narizzano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Massimo Narizzano

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Narizzano. A scholar is included among the top collaborators of Massimo Narizzano 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 Massimo Narizzano. Massimo Narizzano 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.
Narizzano, Massimo, et al.. (2019). Poster: Automatic Consistency Checking of Requirements with ReqV. CINECA IRIS Institutial Research Information System (University of Genoa). 363–366. 7 indexed citations
2.
Narizzano, Massimo, et al.. (2019). Property specification patterns at work: verification and inconsistency explanation. Innovations in Systems and Software Engineering. 15(3-4). 307–323. 7 indexed citations
3.
Narizzano, Massimo, et al.. (2019). Automata Based Test Generation with SpecPro. CINECA IRIS Institutial Research Information System (University of Genoa). 16. 13–16.
4.
Cardinale, Francesco, Michele Rizzi, Piergiorgio d’Orio, et al.. (2017). A new tool for touch-free patient registration for robot-assisted intracranial surgery: application accuracy from a phantom study and a retrospective surgical series. Neurosurgical FOCUS. 42(5). E8–E8. 82 indexed citations
5.
Narizzano, Massimo, et al.. (2017). Learning middleware models for verification of distributed control programs. Robotics and Autonomous Systems. 92. 139–151. 3 indexed citations
6.
Momi, Elena De, et al.. (2017). Retrospective evaluation and SEEG trajectory analysis for interactive multi-trajectory planner assistant. International Journal of Computer Assisted Radiology and Surgery. 12(10). 1727–1738. 19 indexed citations
7.
Narizzano, Massimo, Gabriele Arnulfo, Serena Ricci, et al.. (2017). SEEG assistant: a 3DSlicer extension to support epilepsy surgery. BMC Bioinformatics. 18(1). 124–124. 57 indexed citations
8.
Narizzano, Massimo, et al.. (2016). Twelve Years of QBF Evaluations: QSAT Is PSPACE-Hard and It Shows. Fundamenta Informaticae. 149(1-2). 133–158. 7 indexed citations
9.
Arnulfo, Gabriele, Massimo Narizzano, Francesco Cardinale, Marco Fato, & J. Matias Palva. (2015). Automatic segmentation of deep intracerebral electrodes in computed tomography scans. BMC Bioinformatics. 16(1). 99–99. 42 indexed citations
10.
Narizzano, Massimo, et al.. (2015). An Empirical Perspective on Ten Years of QBF Solving.. CINECA IRIS Institutial Research Information System (University of Genoa). 62–75. 1 indexed citations
11.
Lewis, Matthew, et al.. (2011). Parallel QBF Solving with Advanced Knowledge Sharing. Fundamenta Informaticae. 107(2-3). 139–166. 2 indexed citations
12.
Giunchiglia, Enrico, et al.. (2010). QuBE7.0. 7(2-3). 83–88. 3 indexed citations
13.
Narizzano, Massimo, et al.. (2009). Evaluating and certifying QBFs: A comparison of state-of-the-art tools. AI Communications. 22(4). 191–210. 13 indexed citations
14.
Giunchiglia, Enrico, et al.. (2009). Automatic Test Generation for Coverage Analysis of ERTMS Software. CINECA IRIS Institutial Research Information System (University of Genoa). 303–306. 2 indexed citations
15.
Narizzano, Massimo, et al.. (2009). Comparison of knowledge sharing strategies in a parallel QBF solver. CINECA IRIS Institutial Research Information System (University of Genoa). 161–167. 2 indexed citations
16.
Giunchiglia, Enrico, et al.. (2008). Preprocessing Techniques for QBFs.
17.
Giunchiglia, Enrico, Massimo Narizzano, & Armando Tacchella. (2007). Quantifier Structure in Search-Based Procedures for QBFs. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 26(3). 497–507. 12 indexed citations
18.
Narizzano, Massimo, Luca Pulina, & Armando Tacchella. (2006). Report of the Third QBF Solvers Evaluation1. 2(1-4). 145–164. 18 indexed citations
19.
Giunchiglia, Enrico, Massimo Narizzano, & Armando Tacchella. (2003). Backjumping for Quantified Boolean Logic satisfiability. Artificial Intelligence. 145(1-2). 99–120. 13 indexed citations
20.
Giunchiglia, Enrico, Massimo Narizzano, & Armando Tacchella. (2002). Learning for quantified boolean logic satisfiability. National Conference on Artificial Intelligence. 649–654. 26 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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