Algorithms for Algebraic Path Properties in Concurrent Systems of Constant Treewidth Components

TL;DR

This paper introduces efficient algorithms for algebraic path properties in concurrent systems with constant treewidth components, enabling faster query responses and tradeoffs between preprocessing and query time.

Contribution

It presents novel algorithms that improve worst-case running times for algebraic path queries in concurrent systems, with tradeoffs based on the number of queries.

Findings

Significantly faster algorithms for algebraic path queries in systems with constant treewidth.

Tradeoff strategies between preprocessing time and query response time.

Conditional optimality results indicating the limits of current algorithmic improvements.

Abstract

We study algorithmic questions for concurrent systems where the transitions are labeled from a complete, closed semiring, and path properties are algebraic with semiring operations. The algebraic path properties can model dataflow analysis problems, the shortest path problem, and many other natural problems that arise in program analysis. We consider that each component of the concurrent system is a graph with constant treewidth, a property satisfied by the controlflow graphs of most programs. We allow for multiple possible queries, which arise naturally in demand driven dataflow analysis. The study of multiple queries allows us to consider the tradeoff between the resource usage of the one-time preprocessing and for each individual query. The traditional approach constructs the product graph of all components and applies the best-known graph algorithm on the product. In this approach, even the answer to a single query requires the transitive closure, which provides no room for tradeoff between preprocessing and query time. Our main contributions are algorithms that significantly improve the worst-case running time of the traditional approach, and provide various tradeoffs depending on the number of queries. For example, in a concurrent system of two components, the traditional approach requires hexic time in the worst case for answering one query as well as computing the transitive closure, whereas we show that with one-time preprocessing in almost cubic time, each subsequent query can be answered in at most linear time, and even the transitive closure can be computed in almost quartic time. Furthermore, we establish conditional optimality results showing that the worst-case running time of our algorithms cannot be improved without achieving major breakthroughs in graph algorithms.