Tools and Algorithms for the Construction and Analysis of Systems

Armin Biere,David Parker

doi:10.1007/978-3-030-45237-7

Abstract

This open access two-volume set constitutes the proceedings of the 26th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The total of 60 regular papers presented in these volumes was carefully reviewed and selected from 155 submissions. The papers are organized in topical sections as follows: Part I: Program verification; SAT and SMT; Timed and Dynamical Systems; Verifying Concurrent Systems; Probabilistic Systems; Model Checking and Reachability; and Timed and Probabilistic Systems. Part II: Bisimulation; Verification and Efficiency; Logic and Proof; Tools and Case Studies; Games and Automata; and SV-COMP 2020.

Highlights

Branching bisimilarity [8] is an alternative to weak bisimilarity [17]
The results show that when applied to practical cases, JGKW20 is generally the fastest algorithm, and even when other algorithms have similar runtimes, it uses almost always the least memory
We describe the operational behaviour of a configuration as a probabilistic labelled transition system, where probabilistic transitions arise naturally because measuring a quantum system can entail a probability distribution of post-measurement quantum systems

Summary

Introduction

One of the distinct advantages of branching bisimilarity is that, from the outset, an efficient algorithm has been available [10], which can be used to calculate whether two states are equivalent and to calculate a quotient LTS It has complexity O(mn) with m the number of transitions and n the number of states. Arnold posited computing transitive closures of statically derived program call graphs as the fundamental technique for change impact analysis [3]. Prior work has studied RTS for various programming languages (e.g., C, C++, and Java), built dependency graphs statically or dynamically, and used various granularities of code elements (e.g., statements, methods, and classes). Ekstazi [26], a recent RTS tool for Java projects, builds and maintains Java class file dependency graphs dynamically, and when a class file is modified, Ekstazi uses change impact analysis to select all test classes that depend, directly or indirectly, on the modified class

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Discussion

Conclusion