Extending the logical update view with transaction support

Since the database update view was standardised in the Prolog ISO standard, the so called logical update view is available in all actively maintained Prolog systems. While this update view provided a well defined update semantics and allows for efficient handling of dynamic code, it does not help in maintaining consistency of the dynamic database. With the introduction of multiple threads and deployment of Prolog in continuously running server applications, consistency of the dynamic database becomes important. In this article, we propose an extension to the generation-based implementation of the logical update view that supports transactions. Generation-based transactions have been implemented according to this description in the SWI-Prolog RDF store. The aim of this paper is to motivate transactions, outline an implementation and generate discussion on the desirable semantics and interface prior to implementation.Comment: Appeared in CICLOPS 2012. 9 Pages, 0 Figure

Why It's Nice to be Quoted: Quasiquoting for Prolog

Prolog's support for dynamic programming, meta programming and text processing using context free grammars make the language highly suitable for defining domain specific languages (DSL) as well as analysing, refactoring or generating expression states in other (programming) languages. Well known DSLs are the DCG (Definite Clause Grammar) notation and constraint languages such as CHR. These extensions use Prolog operator declarations and the {...} notation to realise a good syntax. When external languages, such as HTML, SQL or JavaScript enter the picture, operators no longer satisfy for embedding snippets of these languages into a Prolog source file. In addition, Prolog has poor support for quoting long text fragments. Haskell introduced quasi quotationsto resolve this problem. In this paper we `ported' the Haskell mechanism for quasi quoting to Prolog. We show that this can be done cleanly and that quasi quoting can solve the above mentioned problems.Comment: Part of WLPE 2013 proceedings (arXiv:1308.2055

KBSET -- Knowledge-Based Support for Scholarly Editing and Text Processing with Declarative LaTeX Markup and a Core Written in SWI-Prolog

KBSET is an environment that provides support for scholarly editing in two flavors: First, as a practical tool KBSET/Letters that accompanies the development of editions of correspondences (in particular from the 18th and 19th century), completely from source documents to PDF and HTML presentations. Second, as a prototypical tool KBSET/NER for experimentally investigating novel forms of working on editions that are centered around automated named entity recognition. KBSET can process declarative application-specific markup that is expressed in LaTeX notation and incorporate large external fact bases that are typically provided in RDF. KBSET includes specially developed LaTeX styles and a core system that is written in SWI-Prolog, which is used there in many roles, utilizing that it realizes the potential of Prolog as a unifying language.Comment: To appear in DECLARE 2019 Revised Selected Paper

Measuring Coverage of Prolog Programs Using Mutation Testing

Testing is an important aspect in professional software development, both to avoid and identify bugs as well as to increase maintainability. However, increasing the number of tests beyond a reasonable amount hinders development progress. To decide on the completeness of a test suite, many approaches to assert test coverage have been suggested. Yet, frameworks for logic programs remain scarce. In this paper, we introduce a framework for Prolog programs measuring test coverage using mutations. We elaborate the main ideas of mutation testing and transfer them to logic programs. To do so, we discuss the usefulness of different mutations in the context of Prolog and empirically evaluate them in a new mutation testing framework on different examples.Comment: 16 pages, Accepted for presentation in WFLP 201

Lazy Stream Programming in Prolog

In recent years, stream processing has become a prominent approach for incrementally handling large amounts of data, with special support and libraries in many programming languages. Unfortunately, support in Prolog has so far been lacking and most existing approaches are ad-hoc. To remedy this situation, we present lazy stream generators as a unified Prolog interface for stateful computations on both finite and infinite sequences of data that are produced incrementally through I/O and/or algorithmically. We expose stream generators to the application programmer in two ways: 1) through an abstract sequence manipulation API, convenient for defining custom generators, and 2) as idiomatic lazy lists, compatible with many existing list predicates. We define an algebra of stream generator operations that extends Prolog via an embedded language interpreter, provides a compact notation for composing generators and supports moving between the two isomorphic representations. As a special instance, we introduce answer stream generators that encapsulate the work of coroutining first-class logic engines and support interoperation between forward recursive AND-streams and backtracking-generated OR-streams. Keywords: lazy stream generators, lazy lists, first-class logic engines, stream combinators, AND-stream / OR-stream interoperation, Prolog extensionsComment: In Proceedings ICLP 2019, arXiv:1909.0764

Probabilistic inference in SWI-Prolog

Probabilistic Logic Programming (PLP) emerged as one of the most prominent approaches to cope with real-world domains. The distribution semantics is one of most used in PLP, as it is followed by many languages, such as Independent Choice Logic, PRISM, pD, Logic Programs with Annotated Disjunctions (LPADs) and ProbLog. A possible system that allows performing inference on LPADs is PITA, which transforms the input LPAD into a Prolog program containing calls to library predicates for handling Binary Decision Diagrams (BDDs). In particular, BDDs are used to compactly encode explanations for goals and efficiently compute their probability. However, PITA needs mode-directed tabling (also called tabling with answer subsumption), which has been implemented in SWI-Prolog only recently. This paper shows how SWI-Prolog has been extended to include correct answer subsumption and how the PITA transformation has been changed to use SWI-Prolog implementation

Using Prolog as the Fundament for Applications on the Semantic Web

This article describes the experiences developing a Semantic Web application entirely in Prolog. The application, a demonstrator that provides access to multiple art collections and linking these using cultural heritage vocabul