Dr Ciaran McCreesh

  • Research Fellow (School of Computing Science)

Research interests

I'm interested in solving hard combinatorial problems in practice, particularly in the areas of graph theory and subgraph finding. Theoretically, these problems should take exponential time to solve, but in practice algorithms based upon symbolic artificial intelligence techniques like constraint programming and boolean satisfiability can often exactly solve large instances very quickly. My main research questions are:

  • What can we do to close the gap between theoretical worst-case results, and what we see in practice? I am particularly interested in using empirical algorithmics and computational and scientific experiments to gain an understanding that can't be reached through theory alone.
  • Can we use empirical algorithmics techniques to design better algorithms? For example, can we measure what solvers are doing during search, and use this to improve performance when a solver encounters an instance it finds hard? I have also worked on exploiting parallel hardware such as bit-parallelism, multi-core parallelism and high performance computing to accelerate algorithm performance.
  • Why should we trust the outputs of these algorithm implementations? Solvers are increasingly being used autonomously in ways which directly affect people's safety, lives, and livelihoods, without human oversight. However, we know that most solvers are buggy, and will occasionally output an incorrect answer. Conventional software engineering testing techniques fail to detect these bugs, and formal methods are too expensive to use in practice. Some of my recent research looks at proof logging or certifying as an alternative. The idea is that alongside an output, a solver produces a mathematical proof that this answer is correct, which can be stored and audited by a third party.
  • How can we make techniques developed in constraint programming and related areas more accessible to developers? We know, for example, that vanilla backtracking search is a bad idea, but techniques like restarts and nogood recording are not widely implemented due to the difficulty in programming them correctly. Similarly, we know how to do parallel search in theory, but few algorithm implementations actually do this. Could we develop libraries or algorithm skeletons to help?
  • More broadly, can we develop a discipline of algorithm engineering that focuses on how to design and implement small, efficient, correct pieces of code, rather than the large systems with uncertain requirements usually covered by software engineering?

Publications

List by: Type | Date

Jump to: 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012
Number of items: 34.

2022

Gocht, S., Mccreesh, C. and Nordström, J. (2022) An Auditable Constraint Programming Solver. In: 28th International Conference on Principles and Practice of Constraint Programming (CP2022), Haifa, Israel, 31 July-5 Aug 2022, (Accepted for Publication)

2021

Bogaerts, B., Gocht, S., McCreesh, C. and Nordstrom, J. (2021) Certified Symmetry and Dominance Breaking for Combinatorial Optimisation. In: 36th AAAI Conference on Artificial Intelligence (AAAI-22), 22 February - 1 March 2022, (Accepted for Publication)

Archibald, B. , Burns, K. , McCreesh, C. and Sevegnani, M. (2021) Practical Bigraphs via Subgraph Isomorphism. In: 27th International Conference on Principles and Practice of Constraint Programming (CP 2021), 25-29 Oct 2021, 15.1-15.17. ISBN 9783959772112

Fichte, J. K., Hecher, M., Mccreesh, C. and Shahab, A. (2021) Complications for Computational Experiments from Modern Processors. In: 27th International Conference on Principles and Practice of Constraint Programming (CP 2021), 25-29 Oct 2021,

Akgün, Ö., Enright, J. , Jefferson, C., McCreesh, C. , Prosser, P. and Zschaler, S. (2021) Finding Subgraphs With Side Constraints. In: 18th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAOIR 2021), Vienna, Austria, 5-8 July 2021, pp. 348-364. ISBN 9783030782290 (doi: 10.1007/978-3-030-78230-6_22)

Kraiczy, S. and McCreesh, C. (2021) Solving Graph Homomorphism and Subgraph Isomorphism Problems Faster Through Clique Neighbourhood Constraints. In: Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21), Montréal, Canada, 19-27 Aug 2021, pp. 1396-1402. ISBN 9780999241196 (doi: 10.24963/ijcai.2021/193)

2020

Gocht, S., McBride, R., McCreesh, C. , Nordström, J., Prosser, P. and Trimble, J. (2020) Certifying Solvers for Clique and Maximum Common (Connected) Subgraph Problems. In: 26th International Conference on Principles and Practice of Constraint Programming, Louvain-la-Neuve, Belgium, 07-11 Sep 2020, pp. 338-357. ISBN 9783030584740 (doi: 10.1007/978-3-030-58475-7_20)

Elffers, J., Gocht, S., McCreesh, C. and Nordström, J. (2020) Justifying All Differences Using Pseudo-Boolean Reasoning. In: Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, NY, USA, 07-12 Feb 2020, pp. 1486-1494.

Gocht, S., Mccreesh, C. and Nordström, J. (2020) Subgraph Isomorphism Meets Cutting Planes: Solving with Certified Solutions. In: 2020 International Joint Conference on Artificial Intelligence (IJCAI-PRICAI 2020), Yokohama, Japan, 11-17 Jul 2020, pp. 1134-1140. ISBN 9780999241165 (doi: 10.24963/ijcai.2020/158)

Mccreesh, C. , Prosser, P. and Trimble, J. (2020) The Glasgow Subgraph Solver: Using Constraint Programming to Tackle Hard Subgraph Isomorphism Problem Variants. In: 13th International Conference on Graph Transformation (ICGT 2020), Bergen, Norway, 25-26 Jun 2020, pp. 316-324. ISBN 9783030513719 (doi: 10.1007/978-3-030-51372-6)

2019

Archibald, B. , Dunlop, F., Hoffmann, R., McCreesh, C. , Prosser, P. and Trimble, J. (2019) Sequential and parallel solution-biased search for subgraph algorithms. In: 16th International Conference on Integration of Constraint Programming, Artificial Intelligence and Operations Research (CPAIOR 2019), Thessaloniki, Greece, 4-7 June 2019, pp. 20-38. ISBN 9783030192112 (doi: 10.1007/978-3-030-19212-9_2)

McCreesh, C. , Pettersson, W. and Prosser, P. (2019) Understanding the empirical hardness of random optimisation problems. In: 25th International Conference on Principles and Practice of Constraint Programming, Stamford, CT, USA, 30 Sep - 04 Oct 2019, pp. 333-349. (doi: 10.1007/978-3-030-30048-7_20)

2018

Cano, J. , White, D. R., Bordallo, A., McCreesh, C. , Michala, A. L. , Singer, J. and Nagarajan, V. (2018) Solving the task variant allocation problem in distributed robotics. Autonomous Robots, 42(7), pp. 1477-1495. (doi: 10.1007/s10514-018-9742-5)

Gent, I. P., Miguel, I., Nightingale, P., McCreesh, C. , Prosser, P. , Moore, N. C.A. and Unsworth, C. (2018) A review of literature on parallel constraint solving. Theory and Practice of Logic Programming, 18(5-6), pp. 725-758. (doi: 10.1017/S1471068418000340)

Hoffmann, R., Mccreesh, C. , Ndiaye, S. N., Prosser, P. , Reilly, C., Solnon, C. and Trimble, J. (2018) Observations from Parallelising Three Maximum Common (Connected) Subgraph Algorithms. In: 15th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2018), Delft, The Netherlands, 26-29 Jun 2018, pp. 298-315. ISBN 9783319930305 (doi: 10.1007/978-3-319-93031-2_22)

Archibald, B. , Maier, P., McCreesh, C. , Stewart, R. and Trinder, P. (2018) Replicable parallel branch and bound search. Journal of Parallel and Distributed Computing, 113, pp. 92-114. (doi: 10.1016/j.jpdc.2017.10.010)

Mccreesh, C. , Prosser, P. and Trimble, J. (2018) When subgraph isomorphism is really hard, and why this matters for graph databases. Journal of Artificial Intelligence Research, 61, pp. 723-759. (doi: 10.1613/jair.5768)

2017

Hoffmann, R., Mccreesh, C. and Reilly, C. (2017) Between Subgraph Isomorphism and Maximum Common Subgraph. In: Thirty-First AAAI Conference on Artificial Intelligence, San Francisco, CA, USA, 4-10 Feb 2017, pp. 3907-3914.

McCreesh, C. , Prosser, P. , Simpson, K. and Trimble, J. (2017) On Maximum Weight Clique Algorithms, and How They Are Evaluated. In: CP2017: The 23rd International Conference on Principles and Practice of Constraint Programming, Melbourne, Australia, 28 Aug - 1 Sept 2017, pp. 206-225. ISBN 9783319661575 (doi: 10.1007/978-3-319-66158-2_14)

McCreesh, C. , Prosser, P. and Trimble, J. (2017) A Partitioning Algorithm for Maximum Common Subgraph Problems. In: 26th International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 19-25 Aug 2017, pp. 712-719. ISBN 9780999241103 (doi: 10.24963/ijcai.2017/99)

2016

Kotthoff, L., McCreesh, C. and Solnon, C. (2016) Portfolios of Subgraph Isomorphism Algorithms. In: Learning and Intelligent OptimizatioN Conference (LION 10), Napoli, Italy, 29 May - 1 June 2016, pp. 107-122. ISBN 9783319503486 (doi: 10.1007/978-3-319-50349-3_8)

McCreesh, C., Ndiaye, S. N., Prosser, P. and Solnon, C. (2016) Clique and Constraint Models for Maximum Common (Connected) Subgraph Problems. In: CP2016: The 22nd International Conference on Principles and Practice of Constraint Programming, Toulouse, France, 5-9 Sept 2016, pp. 350-368. ISBN 9783319449524 (doi: 10.1007/978-3-319-44953-1_23)

McCreesh, C., Prosser, P. and Trimble, J. (2016) Morphing Between Stable Matching Problems. In: CP 2016: 22nd International Conference on Principles and Practices of Constraint Programming, Toulouse, France, 5-9 Sept 2016, pp. 832-840. ISBN 9783319449524 (doi: 10.1007/978-3-319-44953-1_52)

Cano, J. , White, D. R., Bordallo, A., McCreesh, C., Prosser, P. , Singer, J. and Nagarajan, V. (2016) Task Variant Allocation in Distributed Robotics. In: Robotics Science and Systems 2016, Ann Arbor, MI, USA, 18-22 June 2016, ISBN 9780992374723 (doi: 10.15607/RSS.2016.XII.045)

Mccreesh, C. and Prosser, P. (2016) Finding maximum k-cliques faster using lazy global domination. Ninth International Symposium on Combinatorial Search (SoCS 2016), Tarrytown, NY, USA, 6-8 Jul 2016.

McCreesh, C., Prosser, P. and Trimble, J. (2016) Heuristics and Really Hard Instances for Subgraph Isomorphism Problems. In: 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), New York, NY, USA, 9-15 July 2016, pp. 631-638. ISBN 9781577357704

2015

Macdonald, C. , McCreesh, C., Miller, A. and Prosser, P. (2015) Constructing sailing match race schedules: round-robin pairing lists. In: 21st International Conference on Principles and Practice of Constraint Programming (CP 2015), Cork, Ireland, 31 Aug -04 Sep 2015, pp. 671-686. ISBN 9783319232188 (doi: 10.1007/978-3-319-23219-5_46)

McCreesh, C. and Prosser, P. (2015) A Parallel, Backjumping Subgraph Isomorphism Algorithm using Supplemental Graphs. In: 21st International Conference on Principles and Practice of Constraint Programming (CP 2015), Cork, Ireland, 31 Aug -04 Sep 2015, pp. 295-312. ISBN 9783319232188 (doi: 10.1007/978-3-319-23219-5_21)

McCreesh, C. and Prosser, P. (2015) A parallel branch and bound algorithm for the maximum labelled clique problem. Optimization Letters, 9(5), pp. 949-960. (doi: 10.1007/s11590-014-0837-4)

McCreesh, C. and Prosser, P. (2015) The shape of the search tree for the maximum clique problem, and the implications for parallel branch and bound. ACM Transactions on Parallel Computing, 2(1), 8. (doi: 10.1145/2742359)

2014

McCreesh, C. and Prosser, P. (2014) Exact branch and bound algorithm with symmetry breaking for the maximum balanced induced biclique problem. In: 11th International Conference, CPAIOR 2014, Cork, Ireland, 19-23 May 2014, pp. 226-234. ISBN 9783319070452 (doi: 10.1007/978-3-319-07046-9_16)

McCreesh, C. and Prosser, P. (2014) Reducing the branching in a branch and bound algorithm for the maximum clique problem. In: 20th International Conference, CP 2014, Lyon, France, 8-12 Sep 2014, pp. 549-563. ISBN 9783319104270 (doi: 10.1007/978-3-319-10428-7_40)

2013

McCreesh, C. and Prosser, P. (2013) Multi-threading a state-of-the-art maximum clique algorithm. Algorithms, 6(4), pp. 618-635. (doi: 10.3390/a6040618)

2012

McCreesh, C. and Prosser, P. (2012) Distributing an Exact Algorithm for Maximum Clique: Maximising the Costup. Technical Report. School of Computing Science, University of Glasgow.

This list was generated on Mon Jul 4 06:22:35 2022 BST.
Number of items: 34.

Articles

Cano, J. , White, D. R., Bordallo, A., McCreesh, C. , Michala, A. L. , Singer, J. and Nagarajan, V. (2018) Solving the task variant allocation problem in distributed robotics. Autonomous Robots, 42(7), pp. 1477-1495. (doi: 10.1007/s10514-018-9742-5)

Gent, I. P., Miguel, I., Nightingale, P., McCreesh, C. , Prosser, P. , Moore, N. C.A. and Unsworth, C. (2018) A review of literature on parallel constraint solving. Theory and Practice of Logic Programming, 18(5-6), pp. 725-758. (doi: 10.1017/S1471068418000340)

Archibald, B. , Maier, P., McCreesh, C. , Stewart, R. and Trinder, P. (2018) Replicable parallel branch and bound search. Journal of Parallel and Distributed Computing, 113, pp. 92-114. (doi: 10.1016/j.jpdc.2017.10.010)

Mccreesh, C. , Prosser, P. and Trimble, J. (2018) When subgraph isomorphism is really hard, and why this matters for graph databases. Journal of Artificial Intelligence Research, 61, pp. 723-759. (doi: 10.1613/jair.5768)

McCreesh, C. and Prosser, P. (2015) A parallel branch and bound algorithm for the maximum labelled clique problem. Optimization Letters, 9(5), pp. 949-960. (doi: 10.1007/s11590-014-0837-4)

McCreesh, C. and Prosser, P. (2015) The shape of the search tree for the maximum clique problem, and the implications for parallel branch and bound. ACM Transactions on Parallel Computing, 2(1), 8. (doi: 10.1145/2742359)

McCreesh, C. and Prosser, P. (2013) Multi-threading a state-of-the-art maximum clique algorithm. Algorithms, 6(4), pp. 618-635. (doi: 10.3390/a6040618)

Research Reports or Papers

McCreesh, C. and Prosser, P. (2012) Distributing an Exact Algorithm for Maximum Clique: Maximising the Costup. Technical Report. School of Computing Science, University of Glasgow.

Conference or Workshop Item

Mccreesh, C. and Prosser, P. (2016) Finding maximum k-cliques faster using lazy global domination. Ninth International Symposium on Combinatorial Search (SoCS 2016), Tarrytown, NY, USA, 6-8 Jul 2016.

Conference Proceedings

Gocht, S., Mccreesh, C. and Nordström, J. (2022) An Auditable Constraint Programming Solver. In: 28th International Conference on Principles and Practice of Constraint Programming (CP2022), Haifa, Israel, 31 July-5 Aug 2022, (Accepted for Publication)

Bogaerts, B., Gocht, S., McCreesh, C. and Nordstrom, J. (2021) Certified Symmetry and Dominance Breaking for Combinatorial Optimisation. In: 36th AAAI Conference on Artificial Intelligence (AAAI-22), 22 February - 1 March 2022, (Accepted for Publication)

Archibald, B. , Burns, K. , McCreesh, C. and Sevegnani, M. (2021) Practical Bigraphs via Subgraph Isomorphism. In: 27th International Conference on Principles and Practice of Constraint Programming (CP 2021), 25-29 Oct 2021, 15.1-15.17. ISBN 9783959772112

Fichte, J. K., Hecher, M., Mccreesh, C. and Shahab, A. (2021) Complications for Computational Experiments from Modern Processors. In: 27th International Conference on Principles and Practice of Constraint Programming (CP 2021), 25-29 Oct 2021,

Akgün, Ö., Enright, J. , Jefferson, C., McCreesh, C. , Prosser, P. and Zschaler, S. (2021) Finding Subgraphs With Side Constraints. In: 18th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAOIR 2021), Vienna, Austria, 5-8 July 2021, pp. 348-364. ISBN 9783030782290 (doi: 10.1007/978-3-030-78230-6_22)

Kraiczy, S. and McCreesh, C. (2021) Solving Graph Homomorphism and Subgraph Isomorphism Problems Faster Through Clique Neighbourhood Constraints. In: Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21), Montréal, Canada, 19-27 Aug 2021, pp. 1396-1402. ISBN 9780999241196 (doi: 10.24963/ijcai.2021/193)

Gocht, S., McBride, R., McCreesh, C. , Nordström, J., Prosser, P. and Trimble, J. (2020) Certifying Solvers for Clique and Maximum Common (Connected) Subgraph Problems. In: 26th International Conference on Principles and Practice of Constraint Programming, Louvain-la-Neuve, Belgium, 07-11 Sep 2020, pp. 338-357. ISBN 9783030584740 (doi: 10.1007/978-3-030-58475-7_20)

Elffers, J., Gocht, S., McCreesh, C. and Nordström, J. (2020) Justifying All Differences Using Pseudo-Boolean Reasoning. In: Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, NY, USA, 07-12 Feb 2020, pp. 1486-1494.

Gocht, S., Mccreesh, C. and Nordström, J. (2020) Subgraph Isomorphism Meets Cutting Planes: Solving with Certified Solutions. In: 2020 International Joint Conference on Artificial Intelligence (IJCAI-PRICAI 2020), Yokohama, Japan, 11-17 Jul 2020, pp. 1134-1140. ISBN 9780999241165 (doi: 10.24963/ijcai.2020/158)

Mccreesh, C. , Prosser, P. and Trimble, J. (2020) The Glasgow Subgraph Solver: Using Constraint Programming to Tackle Hard Subgraph Isomorphism Problem Variants. In: 13th International Conference on Graph Transformation (ICGT 2020), Bergen, Norway, 25-26 Jun 2020, pp. 316-324. ISBN 9783030513719 (doi: 10.1007/978-3-030-51372-6)

Archibald, B. , Dunlop, F., Hoffmann, R., McCreesh, C. , Prosser, P. and Trimble, J. (2019) Sequential and parallel solution-biased search for subgraph algorithms. In: 16th International Conference on Integration of Constraint Programming, Artificial Intelligence and Operations Research (CPAIOR 2019), Thessaloniki, Greece, 4-7 June 2019, pp. 20-38. ISBN 9783030192112 (doi: 10.1007/978-3-030-19212-9_2)

McCreesh, C. , Pettersson, W. and Prosser, P. (2019) Understanding the empirical hardness of random optimisation problems. In: 25th International Conference on Principles and Practice of Constraint Programming, Stamford, CT, USA, 30 Sep - 04 Oct 2019, pp. 333-349. (doi: 10.1007/978-3-030-30048-7_20)

Hoffmann, R., Mccreesh, C. , Ndiaye, S. N., Prosser, P. , Reilly, C., Solnon, C. and Trimble, J. (2018) Observations from Parallelising Three Maximum Common (Connected) Subgraph Algorithms. In: 15th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2018), Delft, The Netherlands, 26-29 Jun 2018, pp. 298-315. ISBN 9783319930305 (doi: 10.1007/978-3-319-93031-2_22)

Hoffmann, R., Mccreesh, C. and Reilly, C. (2017) Between Subgraph Isomorphism and Maximum Common Subgraph. In: Thirty-First AAAI Conference on Artificial Intelligence, San Francisco, CA, USA, 4-10 Feb 2017, pp. 3907-3914.

McCreesh, C. , Prosser, P. , Simpson, K. and Trimble, J. (2017) On Maximum Weight Clique Algorithms, and How They Are Evaluated. In: CP2017: The 23rd International Conference on Principles and Practice of Constraint Programming, Melbourne, Australia, 28 Aug - 1 Sept 2017, pp. 206-225. ISBN 9783319661575 (doi: 10.1007/978-3-319-66158-2_14)

McCreesh, C. , Prosser, P. and Trimble, J. (2017) A Partitioning Algorithm for Maximum Common Subgraph Problems. In: 26th International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia, 19-25 Aug 2017, pp. 712-719. ISBN 9780999241103 (doi: 10.24963/ijcai.2017/99)

Kotthoff, L., McCreesh, C. and Solnon, C. (2016) Portfolios of Subgraph Isomorphism Algorithms. In: Learning and Intelligent OptimizatioN Conference (LION 10), Napoli, Italy, 29 May - 1 June 2016, pp. 107-122. ISBN 9783319503486 (doi: 10.1007/978-3-319-50349-3_8)

McCreesh, C., Ndiaye, S. N., Prosser, P. and Solnon, C. (2016) Clique and Constraint Models for Maximum Common (Connected) Subgraph Problems. In: CP2016: The 22nd International Conference on Principles and Practice of Constraint Programming, Toulouse, France, 5-9 Sept 2016, pp. 350-368. ISBN 9783319449524 (doi: 10.1007/978-3-319-44953-1_23)

McCreesh, C., Prosser, P. and Trimble, J. (2016) Morphing Between Stable Matching Problems. In: CP 2016: 22nd International Conference on Principles and Practices of Constraint Programming, Toulouse, France, 5-9 Sept 2016, pp. 832-840. ISBN 9783319449524 (doi: 10.1007/978-3-319-44953-1_52)

Cano, J. , White, D. R., Bordallo, A., McCreesh, C., Prosser, P. , Singer, J. and Nagarajan, V. (2016) Task Variant Allocation in Distributed Robotics. In: Robotics Science and Systems 2016, Ann Arbor, MI, USA, 18-22 June 2016, ISBN 9780992374723 (doi: 10.15607/RSS.2016.XII.045)

McCreesh, C., Prosser, P. and Trimble, J. (2016) Heuristics and Really Hard Instances for Subgraph Isomorphism Problems. In: 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), New York, NY, USA, 9-15 July 2016, pp. 631-638. ISBN 9781577357704

Macdonald, C. , McCreesh, C., Miller, A. and Prosser, P. (2015) Constructing sailing match race schedules: round-robin pairing lists. In: 21st International Conference on Principles and Practice of Constraint Programming (CP 2015), Cork, Ireland, 31 Aug -04 Sep 2015, pp. 671-686. ISBN 9783319232188 (doi: 10.1007/978-3-319-23219-5_46)

McCreesh, C. and Prosser, P. (2015) A Parallel, Backjumping Subgraph Isomorphism Algorithm using Supplemental Graphs. In: 21st International Conference on Principles and Practice of Constraint Programming (CP 2015), Cork, Ireland, 31 Aug -04 Sep 2015, pp. 295-312. ISBN 9783319232188 (doi: 10.1007/978-3-319-23219-5_21)

McCreesh, C. and Prosser, P. (2014) Exact branch and bound algorithm with symmetry breaking for the maximum balanced induced biclique problem. In: 11th International Conference, CPAIOR 2014, Cork, Ireland, 19-23 May 2014, pp. 226-234. ISBN 9783319070452 (doi: 10.1007/978-3-319-07046-9_16)

McCreesh, C. and Prosser, P. (2014) Reducing the branching in a branch and bound algorithm for the maximum clique problem. In: 20th International Conference, CP 2014, Lyon, France, 8-12 Sep 2014, pp. 549-563. ISBN 9783319104270 (doi: 10.1007/978-3-319-10428-7_40)

This list was generated on Mon Jul 4 06:22:35 2022 BST.

Research datasets

Jump to: 2019 | 2015
Number of items: 2.

2019

Mccreesh, C. (2019) ciaranm/certified-constraint-solver: AAAI2020. [Data Collection]

2015

Mccreesh, C. and Prosser, P. (2015) A parallel, backjumping subgraph isomorphism algorithm using supplemental graphs. [Data Collection]

This list was generated on Mon Jul 4 08:50:29 2022 BST.