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Software systems should be explainable, that is, they should help us to answer questions while exploring, developing or using them. Textual documentation is a very weak form of explanation, since it is not causally connected to the code, so…

Software Engineering · Computer Science 2024-09-04 Oscar Nierstrasz , Andrei Chiş , Tudor Gîrba

Though end-to-end neural approaches have recently been dominating NLP tasks in both performance and ease-of-use, they lack interpretability and robustness. We propose Binder, a training-free neural-symbolic framework that maps the task…

This introduction aims to tell the story of how we put words into computers. It is part of the story of the field of natural language processing (NLP), a branch of artificial intelligence. It targets a wide audience with a basic…

Computation and Language · Computer Science 2020-04-20 Noah A. Smith

Many logic programming based approaches can be used to describe and solve combinatorial search problems. On the one hand there are definite programs and constraint logic programs that compute a solution as an answer substitution to a query…

Logic in Computer Science · Computer Science 2007-05-23 Nikolay Pelov , Emmanuel De Mot , Maurice Bruynooghe

We propose here to look at how abstract a model of a usable system can be, but still say something useful and interesting, so this paper is an exercise in abstraction and formalisation, with usability-of-design as an example target use. We…

Human-Computer Interaction · Computer Science 2024-03-14 Steve Reeves

Deobfuscating binary code remains a fundamental challenge in reverse engineering, as obfuscation is widely used to hinder analysis and conceal program logic. Although large language models (LLMs) have shown promise in recovering semantics…

Software Engineering · Computer Science 2026-04-10 Li Hu , Xiuwei Shang , Jieke Shi , Shaoyin Cheng , Junqi Zhang , Gangyang Li , Zhou Yang , Weiming Zhang , David Lo

Testing has become an indispensable activity of software development, yet writing good and relevant tests remains a quite challenging task. One well-known problem is that it often is impossible or unrealistic to test for every outcome, as…

Programming Languages · Computer Science 2017-08-18 Dimitri Racordon , Didier Buchs

In this paper we study the logical foundations of automated inductive theorem proving. To that aim we first develop a theoretical model that is centered around the difficulty of finding induction axioms which are sufficient for proving a…

Logic in Computer Science · Computer Science 2023-06-22 Stefan Hetzl , Tin Lok Wong

Substructural type systems, such as affine (and linear) type systems, are type systems which impose restrictions on copying (and discarding) of variables, and they have found many applications in computer science, including quantum…

Logic in Computer Science · Computer Science 2021-01-27 Vladimir Zamdzhiev

This paper summarizes our experience in communicating the elements of reasoning about correctness, and the central role of formal specifications in reasoning about modular, component-based software using a language and an integrated Web IDE…

Software Engineering · Computer Science 2015-08-20 Nabil M. Kabbani , Daniel Welch , Caleb Priester , Stephen Schaub , Blair Durkee , Yu-Shan Sun , Murali Sitaraman

We analyse the expressiveness of the two-valued semantics of abstract argumentation frameworks, normal logic programs and abstract dialectical frameworks. By expressiveness we mean the ability to encode a desired set of two-valued…

Artificial Intelligence · Computer Science 2014-05-06 Hannes Strass

Syntactic structures used to play a vital role in natural language processing (NLP), but since the deep learning revolution, NLP has been gradually dominated by neural models that do not consider syntactic structures in their design. One…

Computation and Language · Computer Science 2023-11-28 Haoyi Wu , Kewei Tu

We present evidence that language models (LMs) of code can learn to represent the formal semantics of programs, despite being trained only to perform next-token prediction. Specifically, we train a Transformer model on a synthetic corpus of…

Machine Learning · Computer Science 2024-08-06 Charles Jin , Martin Rinard

We present the CIFF proof procedure for abductive logic programming with constraints, and we prove its correctness. CIFF is an extension of the IFF proof procedure for abductive logic programming, relaxing the original restrictions over…

Artificial Intelligence · Computer Science 2009-06-08 P. Mancarella , G. Terreni , F. Sadri , F. Toni , U. Endriss

Deductive verification is an effective method to ensure that a given system exposes the intended behavior. In spite of its proven usefulness and feasibility in selected projects, deductive verification is still not a mainstream technique.…

Software Engineering · Computer Science 2026-01-26 Lea Salome Brugger , Xavier Denis , Peter Müller

We present two logical systems based on dependent types that are comparable to ZFC, both in terms of simplicity and having natural set theoretic interpretations. Our perspective is that of a mathematician trained in classical logic, but…

Logic · Mathematics 2025-08-07 Tristan Bice

Deep pre-trained contextualized encoders like BERT (Delvin et al., 2019) demonstrate remarkable performance on a range of downstream tasks. A recent line of research in probing investigates the linguistic knowledge implicitly learned by…

Computation and Language · Computer Science 2020-05-01 Ilia Kuznetsov , Iryna Gurevych

We propose a novel logic, called Frame Logic (FL), that extends first-order logic (with recursive definitions) using a construct Sp(.) that captures the implicit supports of formulas -- the precise subset of the universe upon which their…

Logic in Computer Science · Computer Science 2022-09-27 Adithya Murali , Lucas Peña , Christof Löding , P. Madhusudan

It is widely acknowledged that function symbols are an important feature in answer set programming, as they make modeling easier, increase the expressive power, and allow us to deal with infinite domains. The main issue with their…

Artificial Intelligence · Computer Science 2020-02-19 Marco Calautti , Sergio Greco , Cristian Molinaro , Irina Trubitsyna

This paper describes how automated deduction methods for natural language processing can be applied more efficiently by encoding context in a more elaborate way. Our work is based on formal approaches to context, and we provide a tableau…

Artificial Intelligence · Computer Science 2007-05-23 Christof Monz
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