Software model checking

Jhala, Ranjit; Majumdar, Rupak

doi:10.1145/1592434.1592438

Cited by 306 publications

(179 citation statements)

References 156 publications

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“…A completely general solution is ruled out by the undecidability of the halting problem; however, much research has been conducted on restricted instances of this problem. Model checking [6]- [8] is a very successful technique in which a program is mapped to a Kripke system -a state-based transition system where states are labeled with sets of propositions,. The instructions in the program map from one state to a successor state.…”

Section: Prior Workmentioning

confidence: 99%

Getting it right the first time: Robot mission guarantees in the presence of uncertainty

Lyons

Arkin

Nirmal

et al. 2013

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-Certain robot missions need to perform predictably in a physical environment that may only be poorly characterized in advance. We have previously developed an approach to establishing performance guarantees for behaviorbased controllers in a process-algebra framework. We extend that work here to include random variables, and we show how our prior results can be used to generate a Dynamic Bayesian Network for the coupled system of program and environment model. Verification is reduced to a filtering problem for this network. Finally, we present validation results that demonstrate the effectiveness of the verification of a multiple waypoint robot mission using this approach.

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Section: Prior Workmentioning

confidence: 99%

Getting it right the first time: Robot mission guarantees in the presence of uncertainty

Lyons

Arkin

Nirmal

et al. 2013

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems

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“…Model checking [1] is useful for this purpose. Recently software model checking [2] is actively studied, and program verification [3] is receiving a lot of attention. B.Schlich have developed model checking [mc]square [10], [11] of assembly programs for microcontrollers.…”

Section: Introductionmentioning

confidence: 99%

Model Checking of Embedded Assembly Program Based on Simulation

Yamane

Konoshita

Kato

2017

IEICE Trans. Inf. & Syst.

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SUMMARY Embedded systems have been widely used. In addition, embedded systems have been gradually complicated. It is important to ensure the safety for embedded software by software model checking. We have developed a verification system for verifying embedded assembly programs. It generates exact Kripke structure by exhaustively and dynamically simulating assembly programs, and simultaneously verify it by model checking. In addition, we have introduced undefined values to reduce the number of states in order to avoid the state space explosion.

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“…Verification of robot software is related to general purpose software verification in its objective of taking a program as input and automatically determining whether that program achieves a desired objective or not [1]. It differs in that a robot program continually interacts with its uncertain and dynamic environment, which has to be included in the verification problem.…”

Section: Introductionmentioning

confidence: 99%

“…It differs in that a robot program continually interacts with its uncertain and dynamic environment, which has to be included in the verification problem. However, following general purpose software verification [1], many robot software verification papers do not include any model of the environment in which the mission is carried out and verify properties such as absence of deadlock or run-time errors [2] [3]. Such an approach might verify that a robot never issues a collision velocity, but not that a robot might roll or be mistakenly pushed into an obstacle.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Verification of Multi-robot Missions in Uncertain Environments

Lyons

Arkin

Jiang

et al. 2015

2015 IEEE 27th International Conference on Tools With Artificial Intelligence (ICTAI)

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Abstract-The effective use of autonomous robot teams in highly-critical missions depends on being able to establish performance guarantees. However, establishing a guarantee for the behavior of an autonomous robot operating in an uncertain environment with obstacles is a challenging problem. This paper addresses the challenges involved in building a software tool for verifying the behavior of a multi-robot waypoint mission that includes uncertain environment geometry as well as uncertainty in robot motion. One contribution of this paper is an approach to the problem of a-priori specification of uncertain environments for robot program verification. A second contribution is a novel method to extend the Bayesian Network formulation to reason about random variables with different subpopulations, introduced to address the challenge of representing the effects of multiple sensory histories when verifying a robot mission. The third contribution is experimental validation results presented to show the effectiveness of this approach on a two-robot, bounding overwatch mission.

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Software model checking

Abstract: We survey recent progress in software model checking.

Cited by 306 publications

References 156 publications

Getting it right the first time: Robot mission guarantees in the presence of uncertainty

Getting it right the first time: Robot mission guarantees in the presence of uncertainty

Model Checking of Embedded Assembly Program Based on Simulation

Probabilistic Verification of Multi-robot Missions in Uncertain Environments

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