Debugging constraint programs

Meier, Micha

doi:10.1007/3-540-60299-2_13

Cited by 25 publications

(12 citation statements)

References 1 publication

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“…14 indicates that the swap between the variables (3,9) and (3,17) removes existing conflicts in columns 9 and 17 and introduces a new conflict in column 17. In turn, Fig.…”

Section: Model Concepts and Their Operationsmentioning

confidence: 99%

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Model-driven visualizations of constraint-based local search

2009

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Visualization is often invaluable to understand the behavior of optimization algorithms, identify their bottlenecks or pathological behaviors, and suggest remedial techniques. Yet developing visualizations is often a tedious activity requiring significant time and expertise. This paper presents a framework for the visualization of constraint-based local search (CBLS) algorithms. Given a high-level model and a declarative visualization specification, the CBLS visualizer systematically produces animations to visualize constraints and objectives, violations, and conflicts, as well as the temporal behavior of these measures. The visualization specification is declarative and typically composed of a triple (what,where,how) indicating what to display, where, and with which graphical objects. The visualizer architecture is compositional and extensible. It provides building blocks which can be assembled freely by the user and focuses almost exclusively on static aspects, the dynamic aspects being automated by the use of invariants. The paper highlights various functionalities of the visualizer and describes a blueprint for its implementation.

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“…14 indicates that the swap between the variables (3,9) and (3,17) removes existing conflicts in columns 9 and 17 and introduces a new conflict in column 17. In turn, Fig.…”

Section: Model Concepts and Their Operationsmentioning

confidence: 99%

“…It led to some exciting developments such as the Grace debugger [9], the visualization of search trees (e.g., [3,10,11,17]), global constraints (e.g., [2,6,12]), the effect of propagation on the variable domains (e.g., [11,17]) and the DISCiPl project [4]. High-level visualization tools are desirable for at least two reasons.…”

Section: Introductionmentioning

confidence: 99%

Model-driven visualizations of constraint-based local search

2009

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“…While the focus of this paper is tree search visualisation, it is important to note that there has been significant work in related areas such as matrix-based visualisations of the variables and/or their domains (e.g. [3,6,14,22,27]), visualisation of the constraint-network (e.g. [16,17,24]), and problem-specific and/or custom visualisations (e.g.…”

Section: Related Workmentioning

confidence: 99%

“…For constraint programs the existing profiling tools (e.g. [1,3,8,11,14,18,21,22]) mostly focus on visualising the search tree (for those based on tree-search), visualising constraints and variables and their domains, showing solutions or gathering crude aggregate measures. While these tools can provide very useful information, they are also somewhat limited.…”

Section: Introductionmentioning

confidence: 99%

Visual search tree profiling

et al. 2015

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Understanding how the search space is explored for a given constraint problemand 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 profiling 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.

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“…The most used approach to debug programs in a standard programming language is by tracing, i.e., executing the program step by step, while inspecting the values variables get. Also, debugging by tracing has proven to be useful in many declarative programming contexts such as Prolog [18,4], Haskell [16], ILP [21], constraint programming [14] and deductive databases [10]. This suggests to debug MX theories by tracing an MX solver.…”

Section: Introductionmentioning

confidence: 99%

Debugging for Model Expansion

2009

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Abstract. Due to the development of efficient solvers, declarative problem solving frameworks based on model generation are becoming more and more applicable in practice. However, there are almost no tools to support debugging in these frameworks. For several reasons, current solvers are not suitable for debugging by tracing. In this paper, we propose a new solver algorithm for one of these frameworks, namely Model Expansion, that allows for debugging by tracing. We explain how to explore the trace of this solver in order to quickly locate a bug and we compare our debugging method with existing ones for Answer Set Programming and the Alloy system.

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Debugging constraint programs

Cited by 25 publications

References 1 publication

Model-driven visualizations of constraint-based local search

Model-driven visualizations of constraint-based local search

Visual search tree profiling

Debugging for Model Expansion

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