A Strong-Connectivity Algorithm and Its Applications in Data Flow Analysis shows how a clever new approach speeds up data-flow problems in graphs.
This nonfiction work explains how breaking a graph into strongly connected components (SCCs) can simplify analysis. It introduces a practical algorithm, SCOMPS, that finds SCCs and orders them efficiently, then uses that structure to improve a classic data-flow method.
- How SCCs help organize complex graphs and reduce redundant work.
- How the SCOMPS algorithm runs in linear time relative to nodes and edges.
- How to apply the approach to iterative data-flow analysis, including interprocedural cases.
- Concrete steps to combine SCCs with a revised Hecht-Ullman style iteration for maximal fixpoints.
Ideal for readers of compiler theory and practitioners seeking efficient data-flow solutions in large graphs.