Omniscient Debugging for Cognitive Agent Programs

Vincent J. Koeman; Koen V. Hindriks; Catholijn M. Jonker

doi:10.24963/ijcai.2017/38

Omniscient Debugging for Cognitive Agent Programs

Vincent J. Koeman, Koen V. Hindriks, Catholijn M. Jonker

Interactive Intelligence

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

4 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the 26th International Joint Conference on Artificial Intelligence, IJCAI 2017
Editors	Carles Sierra
Pages	265-272
Number of pages	8
ISBN (Electronic)	978-0-9992411-0-3
DOIs	https://doi.org/10.24963/ijcai.2017/38
Publication status	Published - 2017
Event	IJCAI 2017: 26th International Joint Conference on Artificial Intelligence - Melbourne, Australia Duration: 19 Aug 2017 → 25 Aug 2017 Conference number: 26 http://ijcai-17.org/

Conference

Conference	IJCAI 2017
Abbreviated title	IJCAI 2017
Country	Australia
City	Melbourne
Period	19/08/17 → 25/08/17
Internet address	http://ijcai-17.org/

Keywords

Agent-based and Multi-agent Systems
Multidisciplinary Topics and Applications

Access to Document

10.24963/ijcai.2017/38

Link to publication in Scopus

Cite this

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title = "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.",

keywords = "Agent-based and Multi-agent Systems, Multidisciplinary Topics and Applications",

author = "Koeman, {Vincent J.} and Hindriks, {Koen V.} and Jonker, {Catholijn M.}",

year = "2017",

doi = "10.24963/ijcai.2017/38",

language = "English",

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editor = "Carles Sierra",

booktitle = "Proceedings of the 26th International Joint Conference on Artificial Intelligence, IJCAI 2017",

note = "IJCAI 2017 : 26th International Joint Conference on Artificial Intelligence, IJCAI 2017 ; Conference date: 19-08-2017 Through 25-08-2017",

url = "http://ijcai-17.org/",

}

Omniscient Debugging for Cognitive Agent Programs. / Koeman, Vincent J.; Hindriks, Koen V.; Jonker, Catholijn M.

Proceedings of the 26th International Joint Conference on Artificial Intelligence, IJCAI 2017. ed. / Carles Sierra. 2017. p. 265-272.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Hindriks, Koen V.

AU - Jonker, Catholijn M.

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PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - Agent-based and Multi-agent Systems

KW - Multidisciplinary Topics and Applications

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M3 - Conference contribution

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Y2 - 19 August 2017 through 25 August 2017

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Omniscient Debugging for Cognitive Agent Programs

Abstract

Conference

Keywords

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