Demo Data from SIGIR 2026 / reviewers in the wild / expert
Agustín Borda
dblp:414/7256
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0001-8548-2998ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Software testing · 75% Program verification · 25% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing
combinatorial testing |
0.9 | 1 | 2025 | Automated Combinatorial Test Generation for Alloy · ASE 2025 |
Program verification › specification analysis
formal specification analysis |
0.9 | 1 | 2025 | Automated Combinatorial Test Generation for Alloy · ASE 2025 |
Software testing
specification-based testing |
0.9 | 1 | 2025 | Automated Combinatorial Test Generation for Alloy · ASE 2025 |
Software testing
test generation |
0.9 | 1 | 2025 | Automated Combinatorial Test Generation for Alloy · ASE 2025 |
Methods — techniques the papers use, named apart from their topics
state space partitioning · 0.9incremental SAT solving · 0.9combinatorial testing · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Automated Combinatorial Test Generation for AlloyabstractSpecifications are an essential component of software development, and getting specifications right, especially formal specifications, can be very challenging. While the use of tools such as model finders and model checkers can be very effective for specification analysis through property checking, researchers have also realized that by the explicit provision of wanted and unwanted specification scenarios, in the style of testing in programs, specification assessment can be significantly enhanced. Thus, various testing and test generation techniques have been recently proposed for assessing formal specifications.In this paper, we present such a specification testing approach, in the form of a novel combinatorial testing technique for Alloy specifications, called COMBA. COMBA implements an automated partitioning of the state space of Alloy specifications solely based on elements of the specification (thus not requiring user intervention), and defines a family of test criteria, that indicate how such partitions are to be covered. The coverage of the partitions is defined by a family of combinatorial criteria that, given a positive integer t, require to cover through test cases all feasible t-uples of elements from different partitions. Finally, COMBA introduces an efficient algorithm to generate test cases that satisfy the combinatorial criteria. By leveraging on incremental SAT solving techniques, COMBA achieves significantly better performance in test generation.We experimentally assess COMBA against existing test generation approaches for Alloy, using a large number of specifications with known errors. The results show that COMBA(with t = 2) runs faster, produces smaller test suites, and finds a significantly larger number of real bugs than related approaches. Agustín Borda, Germán Regis, Nazareno Aguirre, Marcelo F. Frias, Pablo Ponzio |
ASE | 1 |