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Automatic Program Repair (APR) aims at fixing buggy source code with less manual debugging efforts, which plays a vital role in improving software reliability and development productivity. Recent APR works have achieved remarkable progress…

Software Engineering · Computer Science 2022-12-06 Wei Yuan , Quanjun Zhang , Tieke He , Chunrong Fang , Nguyen Quoc Viet Hung , Xiaodong Hao , Hongzhi Yin

In this paper we address an issue that has been brought to the attention of the database community with the advent of the Semantic Web, i.e. the issue of how ontologies (and semantics conveyed by them) can help solving typical database…

Logic in Computer Science · Computer Science 2010-03-15 Francesca A. Lisi

Semantic parsing solves knowledge base (KB) question answering (KBQA) by composing a KB query, which generally involves node extraction (NE) and graph composition (GC) to detect and connect related nodes in a query. Despite the strong…

Computation and Language · Computer Science 2022-07-11 Minhao Zhang , Ruoyu Zhang , Yanzeng Li , Lei Zou

Recent standardization efforts for graph databases lead to standard query languages like GQL and SQL/PGQ, and constraint languages like Property Graph Constraints (PG-Constraints). In this paper, we embark on the study of repairing property…

Databases · Computer Science 2026-02-06 Christopher Spinrath , Angela Bonifati , Rachid Echahed

Contextual information plays a vital role for software developers when understanding and fixing a bug. Consequently, deep learning-based program repair techniques leverage context for bug fixes. However, existing techniques treat context in…

Software Engineering · Computer Science 2022-12-07 Mifta Sintaha , Noor Nashid , Ali Mesbah

A general framework is proposed for integration of rules and external first order theories. It is based on the well-founded semantics of normal logic programs and inspired by ideas of Constraint Logic Programming (CLP) and constructive…

Logic in Computer Science · Computer Science 2010-12-08 W. Drabent , J. Maluszynski

Numeric tabular datasets are the dominant data format in scientific practice, yet large language models lack native mechanisms for representing numeric datasets in a meaningful way across heterogeneous feature spaces. Existing approaches…

Machine Learning · Computer Science 2026-05-29 M. Ross Kunz , John Merickel , Keith Wilson

Reasoning in the Semantic Web (SW) commonly uses Description Logics (DL) via OWL2 DL ontologies, or SWRL for variables and Horn clauses. The Rule Interchange Format (RIF) offers more expressive rules but is defined outside RDF and rarely…

Databases · Computer Science 2025-08-19 Dörthe Arndt , William Van Woensel , Dominik Tomaszuk

We investigate the complexity of computing an optimal repair of an inconsistent database, in the case where integrity constraints are Functional Dependencies (FDs). We focus on two types of repairs: an optimal subset repair (optimal…

Databases · Computer Science 2017-12-22 Ester Livshits , Benny Kimelfeld , Sudeepa Roy

Relational databases excel at structured data analysis, but real-world queries increasingly require capabilities beyond standard SQL, such as semantically matching entities across inconsistent names, extracting information not explicitly…

Databases · Computer Science 2026-05-15 Yin Lin , Tianjing Zeng , Zhongjun Ding , Rong Zhu , Bolin Ding , H. V. Jagadish , Jingren Zhou

Despite advances in large language model (LLM)-based natural language interfaces for databases, scaling to enterprise-level data catalogs remains an under-explored challenge. Prior works addressing this challenge rely on domain-specific…

Computation and Language · Computer Science 2025-08-01 Jeffrey Eben , Aitzaz Ahmad , Stephen Lau

A non-deterministic call-by-need lambda-calculus \calc with case, constructors, letrec and a (non-deterministic) erratic choice, based on rewriting rules is investigated. A standard reduction is defined as a variant of left-most outermost…

Programming Languages · Computer Science 2007-05-23 Manfred Schmidt-Schauß , Michael Huber

One major deficiency of most semantic representation techniques is that they usually model a word type as a single point in the semantic space, hence conflating all the meanings that the word can have. Addressing this issue by learning…

Computation and Language · Computer Science 2016-08-08 Mohammad Taher Pilehvar , Nigel Collier

Complex reasoning over tabular data is crucial in real-world data analysis, yet large language models (LLMs) often underperform due to complex queries, noisy data, and limited numerical capabilities. To address these issues, we propose…

Artificial Intelligence · Computer Science 2025-11-06 Changjiang Jiang , Fengchang Yu , Haihua Chen , Wei Lu , Jin Zeng

Rule-based information extraction has lately received a fair amount of attention from the database community, with several languages appearing in the last few years. Although information extraction systems are intended to deal with…

Databases · Computer Science 2018-01-01 Francisco Maturana , Cristian Riveros , Domagoj Vrgoč

We describe a paradigm for combining manual and automatic error correction of noisy structured lexicographic data. Modifications to the structure and underlying text of the lexicographic data are expressed in a simple, interpreted…

Computation and Language · Computer Science 2014-10-30 David Zajic , Michael Maxwell , David Doermann , Paul Rodrigues , Michael Bloodgood

Data extracted from software repositories is used intensively in Software Engineering research, for example, to predict defects in source code. In our research in this area, with data from open source projects as well as an industrial…

Machine Learning · Computer Science 2018-12-27 Tobias Baum , Steffen Herbold , Kurt Schneider

We consider the following \emph{model repair problem}: given a finite Kripke structure $M$ and a specification formula $\eta$ in some modal or temporal logic, determine if $M$ contains a substructure $M'$ (with the same initial state) that…

Logic in Computer Science · Computer Science 2008-04-15 Paul C. Attie , Jad Saklawi

Inferring causal relations in timeseries data with delayed effects is a fundamental challenge, especially when the underlying system exhibits complex dynamics that cannot be captured by simple functional mappings. Traditional approaches…

Machine Learning · Computer Science 2026-02-23 Preetom Biswas , Giulia Pedrielli , K. Selçuk Candan

Tables on the Web contain a vast amount of knowledge in a structured form. To tap into this valuable resource, we address the problem of table retrieval: answering an information need with a ranked list of tables. We investigate this…

Information Retrieval · Computer Science 2021-05-14 Shuo Zhang , Krisztian Balog