Name
Abstract | ||
|---|---|---|
Understanding how the search space is explored for a given constraint problem – and how it changes for different models, solvers or search strategies – is crucial for efficient solving. Yet programmers often have to rely on the crude aggregate measures of the search that are provided by solvers, or on visualisation tools that can show the search tree, but do not offer sophisticated ways to navigate and analyse it, particularly for large trees. We present an architecture for a constraint programming search that is based on a lightweight instrumentation of the solver. The architecture combines a visualisation of the search tree with various tools for convenient navigation and analysis of the search. These include identifying repeated subtrees, high-level abstraction and navigation of the tree, and the comparison of two search trees. The resulting system is akin to a traditional program profiler, which helps the user to focus on the parts of the execution where an improvement to their program would have the greatest effect. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s10601-015-9202-1 | Constraints |
Keywords | Field | DocType |
Constraint programming,Search tree,Profiling,Comparison,Visualisation | Visual search,Incremental heuristic search,Profiling (computer programming),Computer science,Depth-first search,Constraint programming,Theoretical computer science,Artificial intelligence,Solver,K-D-B-tree,Machine learning,Search tree | Journal |
Volume | Issue | ISSN |
21 | 1 | 1383-7133 |
Citations | PageRank | References |
3 | 0.40 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| maxim shishmarev | 1 | 3 | 0.40 |
| Christopher Mears | 2 | 63 | 6.20 |
| Guido Tack | 3 | 377 | 27.56 |
| Maria J. García De La Banda | 4 | 525 | 35.05 |