Abstract We present a new streaming algorithm to validate JSON documents against a set of constraints given as a JSON schema. Among the possible values a JSON document can hold, objects are unordered collections of key-value pairs while arrays are ordered collections of values. We prove that there always exists a visibly pushdown automaton (VPA) that accepts the same set of JSON documents as a JSON schema. Leveraging this result, our approach relies on learning a VPA for the provided schema. As the learned VPA assumes a fixed order on the key-value pairs of the objects, we abstract its transitions in a special kind of graph, and propose an efficient streaming algorithm using the VPA and its graph to decide whether a JSON document is valid for the schema. We evaluate the implementation of our algorithm on a number of random JSON documents, and compare it to the classical validation algorithm.

Abstract We present a new learning algorithm for realtime one-counter automata. Our algorithm uses membership and equivalence queries as in Angluin’s $${L}^*$$ L ∗ algorithm, as well as counter value queries and partial equivalence queries. In a partial equivalence query, we ask the teacher whether the language of a given finite-state automaton coincides with a counter-bounded subset of the target language. We evaluate an implementation of our algorithm on a number of random benchmarks and on a use case regarding efficient JSON-stream validation.

Consistent Query Answering (CQA) with respect to primary keys is the following problem. Given a database instance that is possibly inconsistent with respect to its primary key constraints, define a repair as an inclusion-maximal consistent subinstance. Given a Boolean query q, the problem CERTAINTY(q) takes a database instance as input, and asks whether q is true in every repair. For every Boolean conjunctive query q, the complement of CERTAINTY(q) can be straightforwardly implemented in Answer Set Programming (ASP) by means of a generate-and-test approach: first generate a repair, and then test whether it falsifies the query. Theoretical research has recently revealed that for every self-join-free Boolean conjunctive query q, the complexity class of CERTAINTY(q) is one of FO, L-complete, or coNP-complete. Faced with this complexity trichotomy, one can hypothesize that in practice, the full power of generate-and-test is a computational overkill when CERTAINTY(q) is in the low complexity classes FO or L. We investigate part of this hypothesis within the context of ASP, by asking the following question: whenever CERTAINTY(q) is in FO, does a dedicated first-order algorithm exhibit significant performance gains compared to a generic generate-and-test implementation? We first elaborate on the construction of such dedicated first-order algorithms in ASP, and then empirically address this question.