Skip to content

Research at St Andrews

University > Research portal > Research publications > Dominion

Dominion: an architecture-driven approach to generating efficient constraint solvers

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

DOI

Open Access permissions

Open

Links

Author(s)

Dharini Balasubramaniam, Lakshitha Ramesh De Silva, Christopher Anthony Jefferson, Lars Kotthoff, Ian James Miguel, Peter Nightingale

School/Research organisations

Abstract

Constraints are used to solve combinatorial problems in a variety of industrial and academic disciplines. However most constraint solvers are designed to be general and monolithic, leading to problems with efficiency, scalability and extensibility. We propose a novel, architecture-driven constraint solver generation framework called Dominion to tackle these issues. For any given problem, Dominion generates a lean and efficient solver tailored to that problem. In this paper, we outline the Dominion approach and its implications for software architecture specification of the solver.
Close
More...

Details

Original languageEnglish
Title of host publicationProceedings of the 9th Working IEEE/IFIP Conference on Software Architecture (WICSA)
Subtitle of host publicationBoulder, Colorado, USA 20-24 June 2011
Place of PublicationLos Alamiros, CA
PublisherIEEE Computer Society
Pages228-231
Number of pages4
ISBN (Print)978-1-61284-399-5
DOIs
Publication statusPublished - Jun 2011
Additional links
Event9th Working IEEE/IFIP Conference on Software Architecture - Boulder, United States
Duration: 20 Jun 2011 → 24 Jun 2011

Conference

Conference9th Working IEEE/IFIP Conference on Software Architecture
CountryUnited States
CityBoulder
Period20/06/11 → 24/06/11

    Research areas

  • Software architecture, Constraint solver, Generative programming

Discover related content
Find related publications, people, projects and more using interactive charts.

View graph of relations

Related by author

  1. An Automated Approach to Generating Efficient Constraint Solvers

    Balasubramaniam, D., Jefferson, C. A., Kotthoff, L., Miguel, I. J. & Nightingale, P., 2012, 2012 34th international conference on software engineering (ICSE 2012): Zurich, Switzerland 2-9 June 2012. IEEE, p. 661-671 11 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  2. Athanor: High-Level Local Search Over Abstract Constraint Specifications in Essence

    Attieh, S., Dang, N., Jefferson, C., Miguel, I. & Nightingale, P., Aug 2019, p. 1056-1063.

    Research output: Contribution to conference › Paper

  3. A framework for constraint based local search using ESSENCE

    Akgun, O., Attieh, S. W. A., Gent, I. P., Jefferson, C. A., Miguel, I. J., Nightingale, P. W., Salamon, A. Z., Spracklen, P. & Wetter, J. P., 13 Jul 2018, Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. Lang, J. (ed.). International Joint Conferences on Artificial Intelligence, p. 1242-1248 7 p.

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  4. Metamorphic testing of constraint solvers

    Akgun, O., Gent, I. P., Jefferson, C. A., Miguel, I. J. & Nightingale, P. W., 2018, Principles and Practice of Constraint Programming: 24th International Conference, CP 2018, Lille, France, August 27-31, 2018, Proceedings. Hooker, J. (ed.). Springer, p. 727-736 (Lecture Notes in Computer Science; vol. 11008).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  5. Automatic discovery and exploitation of promising subproblems for tabulation

    Akgun, O., Gent, I. P., Jefferson, C. A., Miguel, I. J., Nightingale, P. W. & Salamon, A. Z., 2018, Principles and Practice of Constraint Programming: 24th International Conference, CP 2018, Lille, France, August 27-31, 2018, Proceedings. Hooker, J. (ed.). Springer, p. 3-12 (Lecture Notes in Computer Science; vol. 11008).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

ID: 11754766