The Science of Solving Hard Subgraph Problems

子图查找问题涉及识别结构化数据中的模式。理论上，这些问题对于算法来说在计算上很难解决，但在实践中，基于约束的智能算法可以快速解决甚至是大问题。这项研究将使用科学（而不是纯粹的数学）技术来增加我们对理论与实践之间差距的理解，并使我们能够在未来设计更好的算法。这项研究基于对证明日志的分析，证明日志是对算法如何得出答案的数学描述。

Subgraph-finding problems involve identifying patterns in structured data. In theory these problems should be computationally hard for an algorithm to solve, but in practice intelligent constraint-based algorithms can quickly solve even large problems. This research will uses scientific (rather than purely mathematical) techniques to increase our understanding of this gap between theory and practice, and will allow us to design better algorithms in the future. The research is based upon analysing proof logs, which are a mathematical description of how an algorithm reached its answer.