Web and Semantic Web Query Languages

A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This article introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced using common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion

Understanding and evolving the Rust programming language

Rust is a young systems programming language that aims to fill the gap between high-level languages—which provide strong static guarantees like memory and thread safety—and low-level languages—which give the programmer fine-grained control over data layout and memory management. This dissertation presents two projects establishing the first formal foundations for Rust, enabling us to better understand and evolve this important language: RustBelt and Stacked Borrows. RustBelt is a formal model of Rust’s type system, together with a soundness proof establishing memory and thread safety. The model is designed to verify the safety of a number of intricate APIs from the Rust standard library, despite the fact that the implementations of these APIs use unsafe language features. Stacked Borrows is a proposed extension of the Rust specification, which enables the compiler to use the strong aliasing information in Rust’s types to better analyze and optimize the code it is compiling. The adequacy of this specification is evaluated not only formally, but also by running real Rust code in an instrumented version of Rust’s Miri interpreter that implements the Stacked Borrows semantics. RustBelt is built on top of Iris, a language-agnostic framework, implemented in the Coq proof assistant, for building higher-order concurrent separation logics. This dissertation begins by giving an introduction to Iris, and explaining how Iris enables the derivation of complex high-level reasoning principles from a few simple ingredients. In RustBelt, this technique is exploited crucially to introduce the lifetime logic, which provides a novel separation-logic account of borrowing, a key distinguishing feature of the Rust type system.Rust ist eine junge systemnahe Programmiersprache, die es sich zum Ziel gesetzt hat, die Lücke zu schließen zwischen Sprachen mit hohem Abstraktionsniveau, die vor Speicher- und Nebenläufigkeitsfehlern schützen, und Sprachen mit niedrigem Abstraktionsniveau, welche dem Programmierer detaillierte Kontrolle über die Repräsentation von Daten und die Verwaltung des Speichers ermöglichen. Diese Dissertation stellt zwei Projekte vor, welche die ersten formalen Grundlagen für Rust zum Zwecke des besseren Verständnisses und der weiteren Entwicklung dieser wichtigen Sprache legen: RustBelt und Stacked Borrows. RustBelt ist ein formales Modell des Typsystems von Rust einschließlich eines Korrektheitsbeweises, welcher die Sicherheit von Speicherzugriffen und Nebenläufigkeit zeigt. Das Modell ist darauf ausgerichtet, einige komplexe Komponenten der Standardbibliothek von Rust zu verifizieren, obwohl die Implementierung dieser Komponenten unsichere Sprachkonstrukte verwendet. Stacked Borrows ist eine Erweiterung der Spezifikation von Rust, die es dem Compiler ermöglicht, den Quelltext mit Hilfe der im Typsystem kodierten Alias-Informationen besser zu analysieren und zu optimieren. Die Tauglichkeit dieser Spezifikation wird nicht nur formal belegt, sondern auch an echten Programmen getestet, und zwar mit Hilfe einer um Stacked Borrows erweiterten Version des Interpreters Miri. RustBelt basiert auf Iris, welches die Konstruktion von Separationslogiken für beliebige Programmiersprachen im Beweisassistenten Coq ermöglicht. Diese Dissertation beginnt mit einer Einführung in Iris und erklärt, wie komplexe Beweismethoden mit Hilfe weniger einfacher Bausteine hergeleitet werden können. In RustBelt wird diese Technik für die Umsetzung der „Lebenszeitlogik“ verwendet, einer Erweiterung der Separationslogik mit dem Konzept von „Leihgaben“ (borrows), welche eine wichtige Rolle im Typsystem von Rust spielen.This research was supported in part by a European Research Council (ERC) Consolidator Grant for the project "RustBelt", funded under the European Union’s Horizon 2020 Framework Programme (grant agreement no. 683289)

Automated Verification of Practical Garbage Collectors

Garbage collectors are notoriously hard to verify, due to their low-level interaction with the underlying system and the general difficulty in reasoning about reachability in graphs. Several papers have presented verified collectors, but either the proofs were hand-written or the collectors were too simplistic to use on practical applications. In this work, we present two mechanically verified garbage collectors, both practical enough to use for real-world C# benchmarks. The collectors and their associated allocators consist of x86 assembly language instructions and macro instructions, annotated with preconditions, postconditions, invariants, and assertions. We used the Boogie verification generator and the Z3 automated theorem prover to verify this assembly language code mechanically. We provide measurements comparing the performance of the verified collector with that of the standard Bartok collectors on off-the-shelf C# benchmarks, demonstrating their competitiveness

A Tutorial on Clique Problems in Communications and Signal Processing

Since its first use by Euler on the problem of the seven bridges of K\"onigsberg, graph theory has shown excellent abilities in solving and unveiling the properties of multiple discrete optimization problems. The study of the structure of some integer programs reveals equivalence with graph theory problems making a large body of the literature readily available for solving and characterizing the complexity of these problems. This tutorial presents a framework for utilizing a particular graph theory problem, known as the clique problem, for solving communications and signal processing problems. In particular, the paper aims to illustrate the structural properties of integer programs that can be formulated as clique problems through multiple examples in communications and signal processing. To that end, the first part of the tutorial provides various optimal and heuristic solutions for the maximum clique, maximum weight clique, and $k$-clique problems. The tutorial, further, illustrates the use of the clique formulation through numerous contemporary examples in communications and signal processing, mainly in maximum access for non-orthogonal multiple access networks, throughput maximization using index and instantly decodable network coding, collision-free radio frequency identification networks, and resource allocation in cloud-radio access networks. Finally, the tutorial sheds light on the recent advances of such applications, and provides technical insights on ways of dealing with mixed discrete-continuous optimization problems

Linear planning logic: An efficient language and theorem prover for robotic task planning

In this paper, we introduce a novel logic language and theorem prover for robotic task planning. Our language, which we call Linear Planning Logic (LPL), is a fragment of linear logic whose resource-conscious semantics are well suited for reasoning with dynamic state, while its structure admits efficient theorem provers for automatic plan construction. LPL can be considered as an extension of Linear Hereditary Harrop Formulas (LHHF), whose careful design allows the minimization of nondeterminism in proof search, providing a sufficient basis for the design of linear logic programming languages such as Lolli. Our new language extends on the expressivity of LHHF, while keeping the resulting nondeterminism in proof search to a minimum for efficiency. This paper introduces the LPL language, presents the main ideas behind our theorem prover on a smaller fragment of this language and finally provides an experimental illustration of its operation on the problem of task planning for the hexapod robot RHex. © 2014 IEEE

Research in the Language, Information and Computation Laboratory of the University of Pennsylvania

This report takes its name from the Computational Linguistics Feedback Forum (CLiFF), an informal discussion group for students and faculty. However the scope of the research covered in this report is broader than the title might suggest; this is the yearly report of the LINC Lab, the Language, Information and Computation Laboratory of the University of Pennsylvania. It may at first be hard to see the threads that bind together the work presented here, work by faculty, graduate students and postdocs in the Computer Science and Linguistics Departments, and the Institute for Research in Cognitive Science. It includes prototypical Natural Language fields such as: Combinatorial Categorial Grammars, Tree Adjoining Grammars, syntactic parsing and the syntax-semantics interface; but it extends to statistical methods, plan inference, instruction understanding, intonation, causal reasoning, free word order languages, geometric reasoning, medical informatics, connectionism, and language acquisition. Naturally, this introduction cannot spell out all the connections between these abstracts; we invite you to explore them on your own. In fact, with this issue it’s easier than ever to do so: this document is accessible on the “information superhighway”. Just call up http://www.cis.upenn.edu/~cliff-group/94/cliffnotes.html In addition, you can find many of the papers referenced in the CLiFF Notes on the net. Most can be obtained by following links from the authors’ abstracts in the web version of this report. The abstracts describe the researchers’ many areas of investigation, explain their shared concerns, and present some interesting work in Cognitive Science. We hope its new online format makes the CLiFF Notes a more useful and interesting guide to Computational Linguistics activity at Penn