Interpolation-Based GR(1) Assumptions Refinement

Cavezza, Davide G.; Alrajeh, Dalal

doi:10.1007/978-3-662-54577-5_16

Cited by 20 publications

(51 citation statements)

References 42 publications

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“…In particular we prove the consistency of this enhanced weakness measure with implication for increasingly complex classes of GR(1) conjunctions. • We demonstrate the applicability of our weakness measure to the problem of GR(1) assumptions refinement [AMT15,CA17] as a way to find weaker refinements. The problem of assumptions refinement usually requires the ranking of several GR(1) formulae.…”

Section: Introductionmentioning

confidence: 93%

“…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%

“…To circumvent this problem, we impose a limit of 8 fairness conditions accepted in any refinement; our approach does not expand further a node of the tree containing more than 8 fairness conditions. This choice is driven by the preliminary observation of the solutions of BFS reported in [CA17]. This approach found one solution with 7 fairness conditions: our choice is such that this solution is not excluded a priori from the search.…”

Section: Gr(1) Assumption Refinementmentioning

confidence: 99%

“…Hence providing formal and rigorous support for ensuring their highest quality is of key importance [Kup12]. One crucial quality metric for specifications, which this paper focuses on, is that of weakness in the context of reactive synthesis [ADG16,AMT15,CA17,DBSU15].…”

Section: Introductionmentioning

confidence: 99%

“…Recent techniques, such as [AMT13,AMT15,CA17,LDS11], deal with the incompleteness of assumptions by providing algorithms for computing missing assumptions that are necessary to ensure the realizability of a given specification. Their aim is to find the "weakest" assumptions refinements amongst possible alternatives.…”

Section: Introductionmentioning

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: Introductionmentioning

confidence: 93%

Section: Gr(1) Assumption Refinementmentioning

confidence: 99%

Section: Gr(1) Assumption Refinementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Weakness Measure for GR(1) Formulae

2021

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GR(1)*: GR(1) Specifications Extended with Existential Guarantees

Amram

Maoz

Pistiner

2019

Lecture Notes in Computer Science

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ACoRe: Automated Goal-Conflict Resolution

Carvalho

Degiovanni

Brizzio

et al. 2023

Lecture Notes in Computer Science

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System goals are the statements that, in the context of software requirements specification, capture how the software should behave. Many times, the understanding of stakeholders on what the system should do, as captured in the goals, can lead to different problems, from clearly contradicting goals, to more subtle situations in which the satisfaction of some goals inhibits the satisfaction of others. These latter issues, called goal divergences, are the subject of goal conflict analysis, which consists of identifying, assessing, and resolving divergences, as part of a more general activity known as goal refinement.While there exist techniques that, when requirements are expressed formally, can automatically identify and assess goal conflicts, there is currently no automated approach to support engineers in resolving identified divergences. In this paper, we present ACoRe, the first approach that automatically proposes potential resolutions to goal conflicts, in requirements specifications formally captured using linear-time temporal logic. ACoRe systematically explores syntactic modifications of the conflicting specifications, aiming at obtaining resolutions that disable previously identified conflicts, while preserving specification consistency. ACoRe integrates modern multi-objective search algorithms (in particular, NSGA-III, WBGA, and AMOSA) to produce resolutions that maintain coherence with the original conflicting specification, by searching for specifications that are either syntactically or semantically similar to the original specification.We assess ACoRe on 25 requirements specifications taken from the literature. We show that ACoRe can successfully produce various conflict resolutions for each of the analyzed case studies, including resolutions that resemble specification repairs manually provided as part of conflict analyses.

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Interpolation-Based GR(1) Assumptions Refinement

Cited by 20 publications

References 42 publications

A Weakness Measure for GR(1) Formulae

A Weakness Measure for GR(1) Formulae

GR(1)*: GR(1) Specifications Extended with Existential Guarantees

ACoRe: Automated Goal-Conflict Resolution

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