195,489 research outputs found
Ants: Mobile Finite State Machines
Consider the Ants Nearby Treasure Search (ANTS) problem introduced by
Feinerman, Korman, Lotker, and Sereni (PODC 2012), where mobile agents,
initially placed at the origin of an infinite grid, collaboratively search for
an adversarially hidden treasure. In this paper, the model of Feinerman et al.
is adapted such that the agents are controlled by a (randomized) finite state
machine: they possess a constant-size memory and are able to communicate with
each other through constant-size messages. Despite the restriction to
constant-size memory, we show that their collaborative performance remains the
same by presenting a distributed algorithm that matches a lower bound
established by Feinerman et al. on the run-time of any ANTS algorithm
Analysing the Control Software of the Compact Muon Solenoid Experiment at the Large Hadron Collider
The control software of the CERN Compact Muon Solenoid experiment contains
over 30,000 finite state machines. These state machines are organised
hierarchically: commands are sent down the hierarchy and state changes are sent
upwards. The sheer size of the system makes it virtually impossible to fully
understand the details of its behaviour at the macro level. This is fuelled by
unclarities that already exist at the micro level. We have solved the latter
problem by formally describing the finite state machines in the mCRL2 process
algebra. The translation has been implemented using the ASF+SDF
meta-environment, and its correctness was assessed by means of simulations and
visualisations of individual finite state machines and through formal
verification of subsystems of the control software. Based on the formalised
semantics of the finite state machines, we have developed dedicated tooling for
checking properties that can be verified on finite state machines in isolation.Comment: To appear in FSEN'11. Extended version with details of the ASF+SDF
translation of SML into mCRL
Collaborative Systems – Finite State Machines
In this paper the finite state machines are defined and formalized. There are presented the collaborative banking systems and their correspondence is done with finite state machines. It highlights the role of finite state machines in the complexity analysis and performs operations on very large virtual databases as finite state machines. It builds the state diagram and presents the commands and documents transition between the collaborative systems states. The paper analyzes the data sets from Collaborative Multicash Servicedesk application and performs a combined analysis in order to determine certain statistics. Indicators are obtained, such as the number of requests by category and the load degree of an agent in the collaborative system.Collaborative System, Finite State Machine, Inputs, States, Outputs
Finite State Machine Synthesis for Evolutionary Hardware
This article considers application of genetic algorithms for finite machine
synthesis. The resulting genetic finite state machines synthesis algorithm
allows for creation of machines with less number of states and within shorter
time. This makes it possible to use hardware-oriented genetic finite machines
synthesis algorithm in autonomous systems on reconfigurable platforms
Amorphous slicing of extended finite state machines
Slicing is useful for many Software Engineering applications and has been widely studied for three decades, but there has been comparatively little work on slicing Extended Finite State Machines (EFSMs). This paper introduces a set of dependency based EFSM slicing algorithms and an accompanying tool. We demonstrate that our algorithms are suitable for dependence based slicing. We use our tool to conduct experiments on ten EFSMs, including benchmarks and industrial EFSMs. Ours is the first empirical study of dependence based program slicing for EFSMs. Compared to the only previously published dependence based algorithm, our average slice is smaller 40% of the time and larger only 10% of the time, with an average slice size of 35% for termination insensitive slicing
Mutation testing from probabilistic finite state machines
Mutation testing traditionally involves mutating a program in order to produce a set of mutants and using these mutants in order to either estimate the effectiveness of a test suite or to drive test generation. Recently, however, this approach has been applied to specifications such as those written as finite state machines. This paper extends mutation testing to finite state machine models in which transitions have associated probabilities. The paper describes several ways of mutating a probabilistic finite state machine (PFSM) and shows how test sequences that distinguish between a PFSM and its mutants can be generated. Testing then involves applying each test sequence multiple times, observing the resultant output sequences and using results from statistical sampling theory in order to compare the observed frequency of each output sequence with that expected
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