Leonardo de Moura
- Software top 0.2%
- Information Systems top 0.5%
- Artificial Intelligence top 2%
- Computational Theory and Mathematics top 0.5%
- Signal Processing top 2%
- Co-authors
- Nikolaj BjørnerM. M. Sant’AnnaIra D. BaxterBruno DutertreGrégoire HamonJohn RushbyNatarajan ShankarSam Owre
- Topics
- Formal Methods in Verification (31 papers)Logic, programming, and type systems (23 papers)Software Testing and Debugging Techniques (13 papers)
- Partner nations
- United StatesUnited KingdomSweden
In The Last Decade
Leonardo de Moura
42 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 62
- Software 1.1k
- Information Systems 1.0k
- Artificial Intelligence 827
- Computational Theory and Mathematics 718
- Signal Processing 454
Countries citing papers authored by Leonardo de Moura
This map shows the geographic impact of Leonardo de Moura'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 Leonardo de Moura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leonardo de Moura more than expected).
Fields of papers citing papers by Leonardo de Moura
This network shows the impact of papers produced by Leonardo de Moura. 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 Leonardo de Moura. The network helps show where Leonardo de Moura may publish in the future.
Co-authorship network of co-authors of Leonardo de Moura
This figure shows the co-authorship network connecting the top 25 collaborators of Leonardo de Moura. A scholar is included among the top collaborators of Leonardo de Moura 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 Leonardo de Moura. Leonardo de Moura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 9 | |
| 3 | 1 | |
| 4 | 11 | |
| 5 | 12 | |
| 6 | 11 | |
| 7 | 31 | |
| 8 | Satisfiability modulo theoriesbreakdown → | 392 |
| 9 | 1 | |
| 10 | 54 | |
| 11 | Deciding Effectively Propositional Logic with Equality | 7 |
| 12 | Relevancy Propagation | 7 |
| 13 | A Fast Linear-Arithmetic Solver for DPLL(T) | 1 |
| 14 | Integrating Simplex with DPLL(T ) | 18 |
| 15 | 12 | |
| 16 | Automated Test Generation with SAL | 25 |
| 17 | 56 | |
| 18 | 12 | |
| 19 | Lazy Theorem Proving for Bounded Model Checking over Infinite Domains | 16 |
| 20 | Clone detection using abstract syntax treesbreakdown → | 874 |
About Leonardo de Moura
Leonardo de Moura is a scholar working on Software, Computational Theory and Mathematics and Artificial Intelligence, having authored 43 papers that have together received 2.1k indexed citations. Recurring topics across this work include Formal Methods in Verification (31 papers), Logic, programming, and type systems (23 papers) and Software Testing and Debugging Techniques (13 papers). The work is most often cited by research in Software (1.1k citations), Information Systems (1.0k citations) and Computational Theory and Mathematics (718 citations). Leonardo de Moura has collaborated with scholars based in United States, United Kingdom and Sweden. Frequent co-authors include Nikolaj Bjørner, M. M. Sant’Anna, Ira D. Baxter, Bruno Dutertre, Grégoire Hamon, John Rushby, Natarajan Shankar, Sam Owre, Dejan Jovanović and Clark Barrett. Their work appears in journals such as Communications of the ACM, Lecture notes in computer science and Journal of Automated Reasoning.
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.