OASIcs: OpenAccess Series in Informatics

http://drops.dagstuhl.de/opus/institut_oasics.php

List of Papers (Total 612)

Harnessing AI For Research

Artificial Intelligence is increasingly being used to both augment existing fields of research and open up new avenues of discovery. From quality control for imaging flow cytometry to computational musicology, modern AI is an exciting new tool for research and thus knowing how to engineer AI systems in a research context is a vital new skill for RSEs to acquire. In this talk, I...

The iBUG Eye Segmentation Dataset

This paper presents the first dataset for eye segmentation in low resolution images. Although eye segmentation has long been a vital preprocessing step in biometric applications, this work is the first to focus on low resolutions image that can be expected from a consumer-grade camera under conventional human-computer interaction and / or video-chat scenarios. Existing eye...

Data-Driven Chinese Walls

Security policy and access control models are often based on qualitative attributes, e.g. security labels, cryptographic credentials. In this paper, we enrich one such model, namely the Chinese Walls model, with quantitative attributes derived from data. Therefore, we advocate a data-driven approach that considers a quantitative definition of access we term, working relations.

Observing the Uptake of a Language Change Making Strings Immutable

To address security concerns, a major change was introduced to the OCaml language and compiler which made strings immutable and introduced array of bytes as replacement for mutable strings. The change is progressively being pushed so that ultimately strings will be immutable. We have investigated the way OCaml package developers undertook the change. In this paper we report on a...

Identifying Barriers to Adoption for Rust through Online Discourse

Rust is a low-level programming language known for its unique approach to memory-safe systems programming and for its steep learning curve. To understand what makes Rust difficult to adopt, we surveyed the top Reddit and Hacker News posts and comments about Rust; from these online discussions, we identified three hypotheses about Rust's barriers to adoption. We found that certain...

A Randomized Controlled Trial on the Impact of Polyglot Programming in a Database Context

Using more than one programming language in the same project is common practice. Often, additional languages might be introduced to projects to solve specific issues. While the practice is common, it is unclear whether it has an impact on developer productivity. In this paper, we present a pilot study investigating what happens when programmers switch between programming...

A Simple Near-Linear Pseudopolynomial Time Randomized Algorithm for Subset Sum

Given a multiset S of n positive integers and a target integer t, the Subset Sum problem asks to determine whether there exists a subset of S that sums up to t. The current best deterministic algorithm, by Koiliaris and Xu [SODA'17], runs in O~(sqrt{n}t) time, where O~ hides poly-logarithm factors. Bringmann [SODA'17] later gave a randomized O~(n + t) time algorithm using two...

Selection from Heaps, Row-Sorted Matrices, and X+Y Using Soft Heaps

We use soft heaps to obtain simpler optimal algorithms for selecting the k-th smallest item, and the set of k smallest items, from a heap-ordered tree, from a collection of sorted lists, and from X+Y, where X and Y are two unsorted sets. Our results match, and in some ways extend and improve, classical results of Frederickson (1993) and Frederickson and Johnson (1982). In...

Natural Language Generation From Ontologies Using Grammatical Framework

The paper addresses the problem of automatic generation of natural language descriptions for ontology-described artifacts. The motivation for the work is the challenge of providing textual descriptions of automatically generated scientific workflows (e.g., paragraphs that scientists can include in their publications). The extended abstract presents a system which generates...

Knowledge Authoring and Question Answering via Controlled Natural Language

Knowledge acquisition from text is the process of automatically acquiring, organizing and structuring knowledge from text which can be used to perform question answering or complex reasoning. However, current state-of-the-art systems are limited by the fact that they are not able to construct the knowledge base with high quality as knowledge representation and reasoning (KRR) has...

Speeding up Lazy-Grounding Answer Set Solving

The grounding bottleneck is an important open issue in Answer Set Programming. Lazy grounding addresses it by interleaving grounding and search. The performance of current lazy-grounding solvers is not yet comparable to that of ground-and-solve systems, however. The aim of this thesis is to extend prior work on lazy grounding by novel heuristics and other techniques like non...

Translating P-log, LPMLN, LPOD, and CR-Prolog2 into Standard Answer Set Programs

Answer set programming (ASP) is a particularly useful approach for nonmonotonic reasoning in knowledge representation. In order to handle quantitative and qualitative reasoning, a number of different extensions of ASP have been invented, such as quantitative extensions LP^{MLN} and P-log, and qualitative extensions LPOD, and CR-Prolog_2. Although each of these formalisms...

Explaining Actual Causation via Reasoning About Actions and Change

In causality, an actual cause is often defined as an event responsible for bringing about a given outcome in a scenario. In practice, however, identifying this event alone is not always sufficient to provide a satisfactory explanation of how the outcome came to be. In this paper, we motivate this claim using well-known examples and present a novel framework for reasoning more...

Probabilistic Action Language pBC+

We present an ongoing research on a probabilistic extension of action language BC+. Just like BC+ is defined as a high-level notation of answer set programs for describing transition systems, the proposed language, which we call pBC+, is defined as a high-level notation of LP^{MLN} programs - a probabilistic extension of answer set programs. As preliminary results accomplished...

Explanations Generation For Web Service Workflow

The motivation for the work is the challenge of providing textual explanations of automatically generated scientific workflows (e.g., paragraphs that scientists can include in their publications). The extended abstract presents a system which generates explanations for a web service workflow from sets of atoms derived from a collection of ontologies. The system, called...

Application of Logic-Based Methods to Machine Component Design

This paper describes an application worked out in collaboration with a company that produces made-to-order machine components. The goal of the project is to develop a system that can support the company's engineers by automating parts of their component design process. We propose a knowledge extraction methodology based on the recent DMN (Decision Model and Notation) standard and...

Learning Commonsense Knowledge Through Interactive Dialogue

One of the most difficult problems in Artificial Intelligence is related to acquiring commonsense knowledge - to create a collection of facts and information that an ordinary person should know. In this work, we present a system that, from a limited background knowledge, is able to learn to form simple concepts through interactive dialogue with a user. We approach the problem...

SMT-Based Answer Set Solver CMODELS(DIFF) (System Description)

Many answer set solvers utilize Satisfiability solvers for search. Satisfiability Modulo Theory solvers extend Satisfiability solvers. This paper presents the CMODELS(DIFF) system that uses Satisfiability Modulo Theory solvers to find answer sets of a logic program. Its theoretical foundation is based on Niemala's characterization of answer sets of a logic program via so called...

Towards Static Performance Guarantees for Programs with Run-Time Checks

This document is an extended abstract of the Technical Report CLIP-1/2018.0.

Declarative Algorithms in Datalog with Extrema: Their Formal Semantics Simplified

Recent advances are making possible the use of aggregates in recursive queries thus enabling the declarative expression classic algorithms and their efficient and scalable implementation. These advances rely the notion of Pre-Mappability (PreM) of constraints that, along with the seminaive-fixpoint operational semantics, guarantees formal non-monotonic semantics for recursive...

Improving Candidate Quality of Probabilistic Logic Models

Many real-world phenomena exhibit both relational structure and uncertainty. Probabilistic Inductive Logic Programming (PILP) uses Inductive Logic Programming (ILP) extended with probabilistic facts to produce meaningful and interpretable models for real-world phenomena. This merge between First Order Logic (FOL) theories and uncertainty makes PILP a very adequate tool for...

CHR^vis: Syntax and Semantics

The work in the paper presents an animation extension (CHR^{vis}) to Constraint Handling Rules (CHR). Visualizations have always helped programmers understand data and debug programs. A picture is worth a thousand words. It can help identify where a problem is or show how something works. It can even illustrate a relation that was not clear otherwise. CHR^{vis} aims at embedding...

A New Proof-Theoretical Linear Semantics for CHR

Constraint handling rules are a committed-choice language consisting of multiple-heads guarded rules that rewrite constraints into simpler ones until they are solved. We propose a new proof-theoretical declarative linear semantics for Constraint Handling Rules. We demonstrate completeness and soundness of our semantics w.r.t. operational omega_t. semantics. We propose also a...

Introspecting Preferences in Answer Set Programming

This paper develops a logic programming language, ASP^EP, that extends answer set programming language with a new epistemic operator >~_x where x in {#,supseteq}. The operator are used between two literals in rules bodies, and thus allows for the representation of introspections of preferences in the presence of multiple belief sets: G >~_# F expresses that G is preferred to F by...