The complexity of reverse engineering problems for conjunctive queries
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Abstract (arXiv)
Reverse engineering problems for conjunctive queries (CQs), such as query by example (QBE) or definability, take a set of user examples and convert them into an explanatory CQ. Despite their importance, the complexity of these problems is prohibitively high (coNEXPTIME-complete). We isolate their two main sources of complexity and propose relaxations of them that reduce the complexity while having meaningful theoretical interpretations. The first relaxation is based on the idea of using existential pebble games for approximating homomorphism tests. We show that this characterizes QBE/definability for CQs up to treewidth k, while reducing the complexity to EXPTIME. As a side result, we obtain that the complexity of the QBE/definability problems for CQs of treewidth k is EXPTIME-complete for each k ≥ 1. The second relaxation is based on the idea of "desynchronizing" direct products, which characterizes QBE/definability for unions of CQs and reduces the complexity to coNP. The combination of these two relaxations yields tractability for QBE and characterizes it in terms of unions of CQs of treewidth at most k. We also study the complexity of these problems for conjunctive regular path queries over graph databases, showing them to be no more difficult than for CQs.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Jun 2016.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 3; 2024: 0; 2025: 2; 2026: 1.
7 papers.
- 2023Characterizing Nexus of Similarity within Knowledge Bases: A Logic-based Framework and its Computational Complexity Aspectscited by 1
- 2023Reverse Engineering of Temporal Queries Mediated by LTL Ontologiescited by 1
- 2025Fitting Ontologies and Constraints to Relational Structurescited by 1
- 2021QDEF and Its Approximations in OBDMcited by 0
- 2023Unique Characterisability and Learnability of Temporal Queries Mediated by an Ontologycited by 0
- 2025Navigating Taxonomic Expansions of Entity Sets Driven by Knowledge Basescited by 0
- 2026Fitting Horn DL Ontologies to ABox and Query Examples: A Tale of Simulation Quantifiers and Finite Modelscited by 0
- 2026Fitting Horn DL Ontologies to ABox and Query Examples: A Tale of Simulation Quantifiers and Finite Models28 Apr 2026
- 2025Navigating Taxonomic Expansions of Entity Sets Driven by Knowledge Bases17 Dec 2025
- 2025Fitting Ontologies and Constraints to Relational Structures11 Aug 2025
- 2023Unique Characterisability and Learnability of Temporal Queries Mediated by an Ontology13 Jun 2023
- 2023Reverse Engineering of Temporal Queries Mediated by LTL Ontologies2 May 2023
- 2023Characterizing Nexus of Similarity within Knowledge Bases: A Logic-based Framework and its Computational Complexity Aspects19 Mar 2023
- 2021QDEF and Its Approximations in OBDM23 Aug 2021