Leonardo de Moura

13.4k total citations · 2 hit papers
43 papers, 2.1k citations indexed

About

Leonardo de Moura is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Software. According to data from OpenAlex, Leonardo de Moura has authored 43 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computational Theory and Mathematics, 28 papers in Artificial Intelligence and 18 papers in Software. Recurrent topics in Leonardo de Moura's work include Formal Methods in Verification (31 papers), Logic, programming, and type systems (23 papers) and Software Testing and Debugging Techniques (13 papers). Leonardo de Moura is often cited by papers focused on Formal Methods in Verification (31 papers), Logic, programming, and type systems (23 papers) and Software Testing and Debugging Techniques (13 papers). Leonardo de Moura collaborates with scholars based in United States, United Kingdom and Sweden. Leonardo de Moura's co-authors include Nikolaj Bjørner, Ira D. Baxter, M. M. Sant’Anna, Bruno Dutertre, Grégoire Hamon, John Rushby, Natarajan Shankar, Sam Owre, Dejan Jovanović and Clark Barrett and has published in prestigious journals such as Communications of the ACM, Lecture notes in computer science and Journal of Automated Reasoning.

In The Last Decade

Leonardo de Moura

42 papers receiving 1.9k citations

Hit Papers

Clone detection using abstract syntax trees 2002 2026 2010 2018 2002 2011 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Clone detection using abstract syntax trees
    2002 874 citations Leonardo de Moura et al. profile →
  2. Satisfiability modulo theories
    2011 392 citations Leonardo de Moura, Nikolaj Bjørner Communications of the ACM profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Leonardo de Moura United States 17 1.1k 1.0k 827 718 454 43 2.1k
Işıl Dillig United States 27 1.2k 1.0× 1.3k 1.2× 1.2k 1.5× 338 0.5× 717 1.6× 98 2.4k
Daniel Jackson United States 21 1.2k 1.1× 1.2k 1.2× 1.3k 1.6× 561 0.8× 196 0.4× 81 2.3k
Wolfram Schulte United States 29 1.4k 1.3× 1.1k 1.1× 1.0k 1.2× 647 0.9× 264 0.6× 117 2.7k
Mauro Pezzè Italy 34 2.4k 2.1× 2.1k 2.1× 908 1.1× 604 0.8× 394 0.9× 184 3.6k
Yu Lei United States 24 2.2k 1.9× 1.0k 1.0× 359 0.4× 255 0.4× 265 0.6× 114 2.6k
Constance Heitmeyer United States 23 1.2k 1.1× 631 0.6× 1.0k 1.2× 1.1k 1.5× 125 0.3× 84 2.2k
Geguang Pu China 17 657 0.6× 823 0.8× 643 0.8× 210 0.3× 499 1.1× 118 1.7k
Jonathan Aldrich United States 23 436 0.4× 1.1k 1.1× 1.7k 2.0× 382 0.5× 180 0.4× 152 2.2k
J.M. Wing United States 18 485 0.4× 1.3k 1.3× 745 0.9× 415 0.6× 639 1.4× 38 2.4k
Mats P. E. Heimdahl United States 24 2.1k 1.9× 972 0.9× 758 0.9× 1.0k 1.4× 74 0.2× 130 2.8k

Countries citing papers authored by Leonardo de Moura

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Ullrich, Sebastian & Leonardo de Moura. (2022). ‘do’ unchained: embracing local imperativity in a purely functional language (functional pearl). Proceedings of the ACM on Programming Languages. 6(ICFP). 512–539.
2.
Ullrich, Sebastian & Leonardo de Moura. (2019). Counting immutable beans. 1–12. 9 indexed citations
3.
Avigad, Jeremy, Leonardo de Moura, & Soonho Kong. (2018). Theorem Proving in Lean. Figshare. 1 indexed citations
4.
Moura, Leonardo de. (2017). Automated Deduction – CADE 26. Lecture notes in computer science. 3 indexed citations
5.
Tompa, Frank Wm., et al.. (2016). Intelligent Computer Mathematics. Lecture notes in computer science. 8 indexed citations
6.
Reynolds, Andrew, Cesare Tinelli, & Leonardo de Moura. (2014). Finding Conflicting Instances of Quantified Formulas in SMT. 195–202. 11 indexed citations
7.
Wintersteiger, Christoph M., Youssef Hamadi, & Leonardo de Moura. (2012). Efficiently solving quantified bit-vector formulas. Formal Methods in System Design. 42(1). 3–23. 31 indexed citations
8.
Barrett, Clark, Morgan Deters, Leonardo de Moura, Albert Oliveras, & Aaron Stump. (2012). 6 Years of SMT-COMP. Journal of Automated Reasoning. 50(3). 243–277. 26 indexed citations
9.
Moura, Leonardo de & Nikolaj Bjørner. (2011). Satisfiability modulo theories. Communications of the ACM. 54(9). 69–77. 392 indexed citations breakdown →
10.
Moura, Leonardo de & Nikolaj Bjørner. (2009). Generalized, efficient array decision procedures. 45–52. 54 indexed citations
11.
Moura, Leonardo de, et al.. (2009). Superfluous S-polynomials in Strategy-Independent Groebner Bases. 72. 45–53. 1 indexed citations
12.
Moura, Leonardo de, et al.. (2009). On locally minimal Nullstellensatz proofs. 35–42. 2 indexed citations
13.
Piskač, Ružica, Leonardo de Moura, & Nikolaj Bjørner. (2008). Deciding Effectively Propositional Logic with Equality. 25. 7 indexed citations
14.
Dutertre, Bruno & Leonardo de Moura. (2006). A Fast Linear-Arithmetic Solver for DPLL(T). 1 indexed citations
15.
Dutertre, Bruno & Leonardo de Moura. (2006). Integrating Simplex with DPLL(T ). 18 indexed citations
16.
Moura, Leonardo de, Harald Rueß, & Natarajan Shankar. (2005). Justifying Equality. Electronic Notes in Theoretical Computer Science. 125(3). 69–85. 12 indexed citations
17.
Barrett, Clark, Leonardo de Moura, & Aaron Stump. (2005). Design and Results of the First Satisfiability Modulo Theories Competition (SMT-COMP 2005). Journal of Automated Reasoning. 35(4). 373–390. 17 indexed citations
18.
Hamon, Grégoire, Leonardo de Moura, & John Rushby. (2004). Generating efficient test sets with a model checker. 261–270. 56 indexed citations
19.
Moura, Leonardo de, et al.. (2004). From simulation to verification (and back). 68. 888–896. 12 indexed citations
20.
Moura, Leonardo de, Harald Rueß, & Maria Sorea. (2002). Lazy Theorem Proving for Bounded Model Checking over Infinite Domains. 16 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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