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Vincent J. Koeman

dblp:162/7719 · DBLP profile ↗
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4ranked-venue papers
4as first author
0since 2021 · last 2017
0000-0002-3147-0262ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4 · 4 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
2 papers
Debugging and program repair · 91% Programming languages and type systems · 9%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Debugging and program repair › time-travel debugging
omniscient debugging
0.622017
Omniscient Debugging for GOAL Agents in Eclipse (Demonstration) · IJCAI 2017
Omniscient Debugging for Cognitive Agent Programs · IJCAI 2017
Debugging and program repair
fault localization
0.312017
Omniscient Debugging for Cognitive Agent Programs · IJCAI 2017
Programming languages and type systems › programming paradigms
agent programming
0.112017
Omniscient Debugging for GOAL Agents in Eclipse (Demonstration) · IJCAI 2017

Methods — techniques the papers use, named apart from their topics

trace visualization · 0.6tracing mechanism · 0.3source-level debugging · 0.3
YearPublicationVenuePosition
2017 Omniscient Debugging for Cognitive Agent Programs
abstract
For real-time programs reproducing a bug by rerunning the system is likely to fail, making fault localization a time-consuming process. Omniscient debugging is a technique that stores each run in such a way that it supports going backwards in time. However, the overhead of existing omniscient debugging implementations for languages like Java is so large that it cannot be effectively used in practice. In this paper, we show that for agent-oriented programming practical omniscient debugging is possible. We design a tracing mechanism for efficiently storing and exploring agent program runs. We are the first to demonstrate that this mechanism does not affect program runs by empirically establishing that the same tests succeed or fail. Usability is supported by a trace visualization method aimed at more effectively locating faults in agent programs.
Vincent J. Koeman, Koen V. Hindriks, Catholijn M. Jonker
IJCAI1
2017 Omniscient Debugging for GOAL Agents in Eclipse (Demonstration)
abstract
The main goal of our demonstration is to show how omniscient debugging can be applied in practice to cognitive agents. A concrete implementation of the mechanisms proposed in Koeman et. al [2017] has been created for the GOAL agent programming language in the Eclipse environment, integrated with the source-level debugger of Koeman et. al [2016], thus fully implementing the proposal within a state-of-the-art setting. The implementation will be used together with typical agent programs to demonstrate its practical use.
Vincent J. Koeman, Koen V. Hindriks, Catholijn M. Jonker
IJCAI1
2017 Designing a source-level debugger for cognitive agent programs
abstract
When an agent program exhibits unexpected behaviour, a developer needs to locate the fault by debugging the agent’s source code. The process of fault localisation requires an understanding of how code relates to the observed agent behaviour. The main aim of this paper is to design a source-level debugger that supports single-step execution of a cognitive agent program. Cognitive agents execute a decision cycle in which they process events and derive a choice of action from their beliefs and goals. Current state-of-the-art debuggers for agent programs provide insight in how agent behaviour originates from this cycle but less so in how it relates to the program code. As relating source code to generated behaviour is an important part of the debugging task, arguably, a developer also needs to be able to suspend an agent program on code locations. We propose a design approach for single-step execution of agent programs that supports both code-based as well as cycle-based suspension of an agent program. This approach results in a concrete stepping diagram ready for implementation and is illustrated by a diagram for both the Goal and Jason agent programming languages, and a corresponding full implementation of a source-level debugger for Goal in the Eclipse development environment. The evaluation that was performed based on this implementation shows that agent programmers prefer a source-level debugger over a purely cycle-based debugger.
Vincent J. Koeman, Koen V. Hindriks, Catholijn M. Jonker
Auton. Agents Multi Agent Syst.1
2015 Designing a Source-Level Debugger for Cognitive Agent Programs
Vincent J. Koeman, Koen V. Hindriks
PRIMA1