Interactive Visualization of Saturation Attempts in Vampire

Gleiss, Bernhard; Kovács, Laura; Schnedlitz, Lena

doi:10.1007/978-3-030-34968-4_28

Cited by 7 publications

(5 citation statements)

References 14 publications

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“…Additionally, heron gives a series of first-order problems in the widely adopted TPTP format [33] which describe the inductiveness checks of the proven property. This allows a user to leverage the advanced tool support for first-order theorem proving [6,24,32] to verify the proof and, simultaneously, better understand the analyzed system.…”

Section: Resultsmentioning

confidence: 99%

Abduction of trap invariants in parameterized systems

Esparza,

Raskin,

Welzel

2021

Preprint

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In a previous paper we have presented a CEGAR approach for the verification of parameterized systems with an arbitrary number of processes organized in an array or a ring [18]. The technique is based on the iterative computation of parameterized invariants, i.e., infinite families of invariants for the infinitely many instances of the system. Safety properties are proved by checking that every global configuration of the system satisfying all parameterized invariants also satisfies the property; we have shown that this check can be reduced to the satisfiability problem for Monadic Second Order on words, which is decidable.A strong limitation of the approach is that processes can only have a fixed number of variables with a fixed finite range. In particular, they cannot use variables with range [0, N − 1], where N is the number of processes, which appear in many standard distributed algorithms. In this paper, we extend our technique to this case. While conducting the check whether a safety property is inductive assuming a computed set of invariants becomes undecidable, we show how to reduce it to checking satisfiability of a first-order formula. We report on experiments showing that automatic first-order theorem provers can still perform this check for a collection of non-trivial examples. Additionally, we can give small sets of readable invariants for these checks.

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Section: Resultsmentioning

confidence: 99%

Abduction of trap invariants in parameterized systems

Esparza,

Raskin,

Welzel

2021

Preprint

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show abstract

“…Most prominently, this includes work within the area of explainable artificial intelligence (XAI) [40,79,82], but can also be extended to related fields such as formal methods [32]. For example, proof attempts have been visualized by SATVIS [34] and an improved version of the Z3 Axiom Profiler [74]. They visually represent attempts from the VAMPEXCIRE theorem prover and Z3 SMT solver, respectively, in order to support users and developers of the tools in understanding the results.…”

Section: Visualization and Explication Of Formal Methodsmentioning

confidence: 99%

Visual Analysis of Hyperproperties for Understanding Model Checking Results

Horak¹,

Coenen²,

Niklas³

et al. 2021

Preprint

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“…Perhác and Zuzana Bilanová have then developed an interactive tool for visualization of the structural operational semantics of a simple imperative programming language. SMGA partially shares the motivation of the first study [9]. This is because the main purpose of SMGA is to help human users conjecture lemmas needed for interactive theorem proving through graphical animations of state machines concerned.…”

Section: Related Workmentioning

confidence: 95%

“…We introduce two recent studies on an integration of formal methods and visualization. One [9] is a study on visualization of what is done inside by Vampire [11], an automated first-order logic theorem prover, and the other is a study on visualization of the structural operational semantics of a simple imperative programming language [17]. Although automated theorem provers are attractive because they may automatically prove theorems, they cannot truly fully automatically prove all possible theorems.…”

Section: Related Workmentioning

confidence: 99%

Graphical Animations of the Lim-Jeong-Park-Lee Autonomous Vehicle Intersection Control Protocol

Buia¹,

Myinta²,

Trana³

et al. 2022

JVLC

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SMGA is a tool that mainly supports humans in visually perceiving the characteristics/properties of systems/protocols. Those characteristics could be used as lemmas to formally verify that the systems/protocols enjoy desired properties. The core task of the tool is to design a state picture that helps humans comprehend the systems/protocols better and then conjecture the characteristics. To demonstrate that SMGA can be applied to a wider class of systems/applications, we have graphically animated the Lim-Jeong-Park-Lee autonomous vehicle intersection control protocol with SMGA. The state machine formalizing the protocol uses composite data. We have revised SMGA so as to handle composite data. We design a flexible state picture for the protocol so that it is possible to deal with different initial states when the number of vehicles is less than or equal to a given number. In the conference version of the present paper, the visual representations of vehicles (or vehicle statuses) on each lane did not preserve the actual order of the vehicles on the lane. We have also revised SMGA so that it is possible to make a state picture design that preserves such an order. In the conference version, any information on conflict and concurrent lanes for each lane was not displayed. We have revised the state picture design so that such information can be visualized. Some characteristics are guessed by observing graphical animations based on the state picture design, and the characteristics are confirmed with model checking. The paper also summarizes several lessons learned as tips on how to design a state picture with composite data.

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Interactive Visualization of Saturation Attempts in Vampire

Cited by 7 publications

References 14 publications

Abduction of trap invariants in parameterized systems

Abduction of trap invariants in parameterized systems

Visual Analysis of Hyperproperties for Understanding Model Checking Results

Graphical Animations of the Lim-Jeong-Park-Lee Autonomous Vehicle Intersection Control Protocol

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