Symbolic Repairs for GR(1) Specifications

Maoz, Shahar; Ringert, Jan Oliver; Shalom, Rafi

doi:10.1109/icse.2019.00106

Cited by 30 publications

(51 citation statements)

References 36 publications

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“…Secondly, we propose using the weakness measure as a heuristic to drive the search for refinements towards weaker formulae compared with the common breadth-first approach to this search problem used in [CA17,AMT13,MRS19,LDS11]. We show that, despite the fact that this heuristic-based approach produces fewer solutions in the given time, it can reach weaker solutions that are missed by a basic breadth-first search of the refinement tree.…”

Section: Gr(1) Assumption Refinementmentioning

confidence: 99%

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A Weakness Measure for GR(1) Formulae

2021

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When dealing with unrealizable specifications in reactive synthesis, finding the weakest environment assumptions that ensure realizability is often considered a desirable property. However, little effort has been dedicated to defining or evaluating the notion of weakness of assumptions formally. The question of whether one assumption is weaker than another is commonly interpreted by considering the implication relationship between the two or, equivalently, their language inclusion. This interpretation fails to provide any insight into the weakness of the assumptions when implication (or language inclusion) does not hold. To our knowledge, the only measure that is capable of comparing two formulae in this case is entropy, but even it cannot distinguish the weakness of assumptions expressed as fairness properties. In this paper, we propose a refined measure of weakness based on combining entropy with Hausdorff dimension, a concept that captures the notion of size of the $$\omega $$ ω -language satisfying a linear temporal logic formula. We focus on a special subset of linear temporal logic formulae which is of particular interest in reactive synthesis, called GR(1). We identify the conditions under which this measure is guaranteed to distinguish between weaker and stronger GR(1) formulae, and propose a refined measure to cover cases when two formulae are strictly ordered by implication but have the same entropy and Hausdorff dimension. We prove the consistency between our weakness measure and logical implication, that is, if one formula implies another, the latter is weaker than the former according to our measure. We evaluate our proposed weakness measure in two contexts. The first is in computing GR(1) assumption refinements where our weakness measure is used as a heuristic to drive the refinement search towards weaker solutions. The second is in the context of quantitative model checking where it is used to measure the size of the language of a model violating a linear temporal logic formula.

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Section: Gr(1) Assumption Refinementmentioning

confidence: 99%

“…To the best of our knowledge, assumption refinement is approached in most cases as a breadth-first search over a refinement tree [AMT13,LDS11,CA17,MRS19]. Given an initial, unrealizable specification φ φ E → φ S , a counterstrategy C is computed (see Sect.…”

Section: Ordering Via Weakness and Implicationmentioning

confidence: 99%

A Weakness Measure for GR(1) Formulae

2021

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“…Typical assumptions refinement approaches are based on alternating between counterstrategy computations and assumption generation, thus called counterstrategy-guided [2,8,24,25,29]. The counterstrategy computation is implemented as a well-known algorithm presented in [21].…”

Section: Counterstrategy-guided Assumptions Refinementmentioning

confidence: 99%

“…In its simplest form, assumptions refinement defines a search problem in an intractably large search space. To deal with this, state-of-the-art approaches (e.g., [2,8,24,29]) employ an incremental procedure that makes use of counterstrategies, i.e., examples of environment behaviours that force the violation of a guarantee. In brief, given an unrealizable specification, a counterstrategy is computed in iteration .…”

Section: Introductionmentioning

confidence: 99%

“…Second, incremental approaches are prone to exploring solutions that are lengthy in the number of assumptions added. This increases the computational overhead since counterstrategy computation is linear in the number of assumptions (Theorem 3 of [6]); it has also been argued [29] that larger sets of assumptions may negatively affect readability.…”

Section: Introductionmentioning

confidence: 99%

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Minimal Assumptions Refinement for Realizable Specifications

Cavezza

Alrajeh

György

2020

Proceedings of the 8th International Conference on Formal Methods in Software Engineering

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A challenge that has gathered much attention in recent years is automated synthesis of correct-by-construction software systems from declarative specifications. The specification language is typically a subset of linear temporal logic called generalized reactivity of rank 1, for which there exists an efficient synthesis algorithm. Specifications in this language model the system as the interaction between an environment and a controller, the former satisfying a set of assumptions and the latter a set of guarantees. In order for a solution to exist, a sufficient set of assumptions implying the guarantees must be provided. The assumptions must be as general as possible and small enough to be intelligible by engineers that need to assess their consistency with the true environment where the synthesized controller will operate. The search for such assumptions is generally a refinement approach driven by counterstrategies, characterizations of undesirable environment behaviors that force the violation of the guarantees; assumptions are progressively refined in order to exclude such behaviors. In this work we provide a heuristic to drive this counterstrategy-guided search towards smaller refinements. We define a concept of minimality of refinements with respect to counterstrategies and provide an algorithm that provably finds minimal refinements with little time overhead. We show experimentally that it consistently produces one or more shorter solutions than state of the art for a set of popular case studies. We also demonstrate that in a popular case study (AMBA-AHB protocol) our heuristic finds a close-to-optimal solution that cannot be found by previous fully automated approaches. CCS CONCEPTS • Software and its engineering Formalsoftwareverification; Requirements analysis; • Hardware Buses and high-speed links.

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Capture, Analyze, Diagnose: Realizability Checking Of Requirements in FRET

Katis

Mavridou

Giannakopoulou

et al. 2022

Computer Aided Verification

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Requirements formalization has become increasingly popular in industrial settings as an effort to disambiguate designs and optimize development time and costs for critical system components. Formal requirements elicitation also enables the employment of analysis tools to prove important properties, such as consistency and realizability. In this paper, we present the realizability analysis framework that we developed as part of the Formal Requirements Elicitation Tool (FRET). Our framework prioritizes usability, and employs state-of-the-art analysis algorithms that support infinite theories. We demonstrate the workflow for realizability checking, showcase the diagnosis process that supports visualization of conflicts between requirements and simulation of counterexamples, and discuss results from industrial-level case studies.

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Symbolic Repairs for GR(1) Specifications

Cited by 30 publications

References 36 publications

A Weakness Measure for GR(1) Formulae

A Weakness Measure for GR(1) Formulae

Minimal Assumptions Refinement for Realizable Specifications

Capture, Analyze, Diagnose: Realizability Checking Of Requirements in FRET

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