10.1007/978-3-662-54434-1_11
Chatterjee, Krishnendu
Krishnendu
Chatterjee0000-0002-4561-241X
Kragl, Bernhard
Bernhard
Kragl0000-0001-7745-9117
Mishra, Samarth
Samarth
Mishra
Pavlogiannis, Andreas
Andreas
Pavlogiannis
Faster algorithms for weighted recursive state machines
LNCS
Springer
2017
2018-12-11T11:49:41Z
2020-02-19T08:00:06Z
conference
https://research-explorer.app.ist.ac.at/record/1011
https://research-explorer.app.ist.ac.at/record/1011.json
03029743
Pushdown systems (PDSs) and recursive state machines (RSMs), which are linearly equivalent, are standard models for interprocedural analysis. Yet RSMs are more convenient as they (a) explicitly model function calls and returns, and (b) specify many natural parameters for algorithmic analysis, e.g., the number of entries and exits. We consider a general framework where RSM transitions are labeled from a semiring and path properties are algebraic with semiring operations, which can model, e.g., interprocedural reachability and dataflow analysis problems. Our main contributions are new algorithms for several fundamental problems. As compared to a direct translation of RSMs to PDSs and the best-known existing bounds of PDSs, our analysis algorithm improves the complexity for finite-height semirings (that subsumes reachability and standard dataflow properties). We further consider the problem of extracting distance values from the representation structures computed by our algorithm, and give efficient algorithms that distinguish the complexity of a one-time preprocessing from the complexity of each individual query. Another advantage of our algorithm is that our improvements carry over to the concurrent setting, where we improve the bestknown complexity for the context-bounded analysis of concurrent RSMs. Finally, we provide a prototype implementation that gives a significant speed-up on several benchmarks from the SLAM/SDV project.