Automatic Hardware Synthesis from Specifications: A Case Study

Bloem, Roderick; Galler, Stefan; Jobstmann, Barbara; Piterman, Nir; Pnueli, Amir; Weiglhofer, Martin

doi:10.1109/date.2007.364456

Cited by 84 publications

(105 citation statements)

References 9 publications

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“…In [3], games with GR(1) conditions are introduced. GR(1) games allow for polynomial-time solutions and have been widely applied in practice [4], [26], [40]. By extending 2-player GR(1) games with a stochastic component introducing 2 1 /2-player GR(1) games, our approach expands the applicability of 2-player GR(1) games in domains such as robotics and autonomous systems where stochastic models are a more natural modeling approach.…”

Section: Algorithmmentioning

confidence: 99%

“…GR(1) games have been applied in numerous settings such as hardware design [4], high-level strategies for selfadaptive systems [15], [5], robot-controller planning [11], [21], [24], [25], [40] and user programming [26], [27]. In addition, many tools for solving GR(1) games have been developed [22], [38], [2], [16] showing that there is real interest in the application of games with GR(1) winning conditions.…”

Section: Introductionmentioning

confidence: 99%

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2½-player generalized reactivity (1) games

Rodrı́guez

Braberman

D’Ippolito

et al. 2016

2016 IEEE 55th Conference on Decision and Control (CDC)

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Abstract-We introduce a new class of 2 1 /2-player games, the 2 1 /2-player GR(1) games, that allows for solving problems of stochastic nature by adding a probabilistic component to simple 2-player GR(1) games. Further, we present an efficient approach for solving qualitative 2 1 /2-player GR(1) games with polynomial-time complexity. Our approach is based on a reduction from 2 1 /2-player GR(1) games to 2-player GR(1) games that allows for solving the game and constructing, from a sure winning strategy for player 2 (resp. 3) in a 2-player GR (1) game, an almost-sure (resp. positively) winning strategy for its corresponding 2 1 /2-player GR(1) game. Key to the effectiveness of the proposed approach is the fact that the reduction generates a 2-player game that is linearly larger than the original 2 1 /2-player game, more precisely, it is linear with respect to the number of probabilistic states in the 2 1 /2-player GR(1) game.

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Section: Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

2½-player generalized reactivity (1) games

Rodrı́guez

Braberman

D’Ippolito

et al. 2016

2016 IEEE 55th Conference on Decision and Control (CDC)

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“…First formulated by Church in 1962 [5], it has been used to synthesize designs in a variety of applications, such as digital circuits [3] and embedded software [22]. In this section, we give an overview on synthesizing reactive modules from a specification given in Linear Temporal Logic (LTL) [17].…”

Section: Synthesis From Temporal Logicmentioning

confidence: 99%

Synthesis for Human-in-the-Loop Control Systems

Sadigh

Sastry

et al. 2014

Lecture Notes in Computer Science

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Abstract-Several control systems in safety-critical applications involve the interaction of an autonomous controller with one or more human operators. Examples include pilots interacting with an autopilot system in an aircraft, and a driver interacting with automated driver-assistance features in an automobile. The correctness of such systems depends not only on the autonomous controller, but also on the actions of the human controller. In this paper, we present a formalism for human-inthe-loop control systems. Particularly, we focus on the problem of synthesizing a semi-autonomous controller from high-level temporal specifications that expect occasional human intervention for correct operation. We present an algorithm for this problem, and demonstrate its operation on problems related to driver assistance in automobiles.

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“…Our specifications for this protocol are taken from the example files provided with RATSY [7]. For details of this protocol, we refer the readers to [6]. There are four environment signals.…”

Section: A Amba Ahb Bus Protocolmentioning

confidence: 99%

Mining assumptions for synthesis

Dworkin

Seshia

2011

Ninth ACM/IEEE International Conference on Formal Methods and Models for Codesign (MEMPCODE2011)

123

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Abstract-Automatic synthesis of a reactive system from its formal specification is appealing but often difficult due to the tedium of writing auxiliary specifications, especially on the environment. In several instances, specifications are found unrealizable as a result of insufficient environmental assumptions. We present an approach to this problem for synthesis from LTL based on specification mining. For a satisfiable but unrealizable specification, a counter-strategy can be computed from the synthesis game as a witness to unrealizability. Our algorithm mines environment assumptions from this counter-strategy as well as user scenarios if they are provided. We argue that our approach is a natural way to discover the designer's intent. We demonstrate the effectiveness of our approach on examples from the domains of digital circuits and robotic controllers.

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Automatic Hardware Synthesis from Specifications: A Case Study

Cited by 84 publications

References 9 publications

2½-player generalized reactivity (1) games

2½-player generalized reactivity (1) games

Synthesis for Human-in-the-Loop Control Systems

Mining assumptions for synthesis

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