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Stavros Tripakis

Publications and source records attributed to Stavros Tripakis.

35 records · Page 2Linked to original sources
arXiv2021

Counterexample Classification

In model checking, when a given model fails to satisfy the desired specification, a typical model checker provides a counterexample that illustrates how the violation occurs. In general, there exist many diverse counterexamples that exhibit distinct violating behaviors, which the user may wish to examine before deciding how to repair the model. Unfortunately, obtaining this information is challenging in existing model checkers since (1) the number of counterexamples may be too large to enumerate one by one, and (2) many of these counterexamples are redundant, in that they describe the same type of violating behavior. In this paper, we propose a technique called counterexample classification. The goal of classification is to partition the space of all counterexamples into a finite set of counterexample classes, each of which describes a distinct type of violating behavior for the given specification. These classes are then presented as a summary of possible violating behaviors in the system, freeing the user from manually having to inspect or analyze numerous counterexamples to extract the same information. We have implemented a prototype of our technique on top of an existing formal modeling and verification tool, the Alloy Analyzer, and evaluated the effectiveness of the technique on case studies involving the well-known Needham-Schroeder protocol with promising results.

cs.SE↗
arXiv2021

Decentralized Observation of Discrete-Event Systems: At Least One Can Tell

We introduce a new decentralized observation condition which we call "at least one can tell" (OCT) and which attempts to capture the idea that for any possible behavior that a system can generate, at least one decentralized observation agent can tell whether that behavior was "good" or "bad", for given formal specifications of "good" and "bad". We provide several equivalent formulations of the OCT condition, and we relate it to (and show that it is different from) previously introduced joint observability. In fact, contrary to joint observability which is undecidable, we show that the OCT condition is decidable. We also show that when the condition holds, finite-state decentralized observers exist.

cs.FL↗
arXiv2020

Metrics and methods for robustness evaluation of neural networks with generative models

Recent studies have shown that modern deep neural network classifiers are easy to fool, assuming that an adversary is able to slightly modify their inputs. Many papers have proposed adversarial attacks, defenses and methods to measure robustness to such adversarial perturbations. However, most commonly considered adversarial examples are based on $\ell_p$-bounded perturbations in the input space of the neural network, which are unlikely to arise naturally. Recently, especially in computer vision, researchers discovered "natural" or "semantic" perturbations, such as rotations, changes of brightness, or more high-level changes, but these perturbations have not yet been systematically utilized to measure the performance of classifiers. In this paper, we propose several metrics to measure robustness of classifiers to natural adversarial examples, and methods to evaluate them. These metrics, called latent space performance metrics, are based on the ability of generative models to capture probability distributions, and are defined in their latent spaces. On three image classification case studies, we evaluate the proposed metrics for several classifiers, including ones trained in conventional and robust ways. We find that the latent counterparts of adversarial robustness are associated with the accuracy of the classifier rather than its conventional adversarial robustness, but the latter is still reflected on the properties of found latent perturbations. In addition, our novel method of finding latent adversarial perturbations demonstrates that these perturbations are often perceptually small.

cs.LG↗
arXiv2018

Automated Synthesis of Secure Platform Mappings

System development often involves decisions about how a high-level design is to be implemented using primitives from a low-level platform. Certain decisions, however, may introduce undesirable behavior into the resulting implementation, possibly leading to a violation of a desired property that has already been established at the design level. In this paper, we introduce the problem of synthesizing a property-preserving platform mapping: A set of implementation decisions ensuring that a desired property is preserved from a high-level design into a low-level platform implementation. We provide a formalization of the synthesis problem and propose a technique for synthesizing a mapping based on symbolic constraint search. We describe our prototype implementation, and a real-world case study demonstrating the application of our technique to synthesizing secure mappings for the popular web authorization protocols OAuth 1.0 and 2.0.

cs.SE↗
arXiv2018

Mechanically Proving Determinacy of Hierarchical Block Diagram Translations

Hierarchical block diagrams (HBDs) are at the heart of embedded system design tools, including Simulink. Numerous translations exist from HBDs into languages with formal semantics, amenable to formal verification. However, none of these translations has been proven correct, to our knowledge. We present in this paper the first mechanically proven HBD translation algorithm. The algorithm translates HBDs into an algebra of terms with three basic composition operations (serial, parallel, and feedback). In order to capture various translation strategies resulting in different terms achieving different tradeoffs, the algorithm is nondeterministic. Despite this, we prove its semantic determinacy: for every input HBD, all possible terms that can be generated by the algorithm are semantically equivalent. We apply this result to show how three Simulink translation strategies introduced previously can be formalized as determinizations of the algorithm, and derive that these strategies yield semantically equivalent results (a question left open in previous work). All results are formalized and proved in the Isabelle theorem-prover.

cs.LO↗
arXiv2018

The Refinement Calculus of Reactive Systems

The Refinement Calculus of Reactive Systems (RCRS) is a compositional formal framework for modeling and reasoning about reactive systems. RCRS provides a language which allows to describe atomic components as symbolic transition systems or QLTL formulas, and composite components formed using three primitive composition operators: serial, parallel, and feedback. The semantics of the language is given in terms of monotonic property transformers, an extension to reactive systems of monotonic predicate transformers, which have been used to give compositional semantics to sequential programs. RCRS allows to specify both safety and liveness properties. It also allows to model input-output systems which are both non-deterministic and non-input-receptive (i.e., which may reject some inputs at some points in time), and can thus be seen as a behavioral type system. RCRS provides a set of techniques for symbolic computer-aided reasoning, including compositional static analysis and verification. RCRS comes with a publicly available implementation which includes a complete formalization of the RCRS theory in the Isabelle proof assistant.

cs.LO↗
arXiv2017

Type Inference of Simulink Hierarchical Block Diagrams in Isabelle

Simulink is a de-facto industrial standard for the design of embedded systems. In previous work, we developed a compositional analysis framework for Simulink models in Isabelle -- the Refinement Calculus of Reactive Systems (RCRS), which allows checking compatibility and substitutability of components. However, standard type checking was not considered in that work. In this paper we present a method for the type inference of hierarchical block diagrams using the Isabelle theorem prover. A Simulink diagram is translated into an (RCRS) Isabelle theory. Then the Isabelle's powerful type inference mechanism is used to infer the types of the diagram based on the types of the basic blocks. One of the aims is to handle formally as many diagrams as possible. In particular, we want to be able to handle even those diagrams that may have typing ambiguities, provided that they are accepted by Simulink. This method is implemented in our toolset that translates Simulink diagrams into Isabelle theories and simplifies them. We evaluate our technique on several case studies, most notably, an automotive fuel control system benchmark provided by Toyota.

cs.SE↗
arXiv2016

Runtime enforcement of reactive systems using synchronous enforcers

Synchronous programming is a paradigm of choice for the design of safety-critical reactive systems. Runtime enforcement is a technique to ensure that the output of a black-box system satisfies some desired properties. This paper deals with the problem of runtime enforcement in the context of synchronous programs. We propose a framework where an enforcer monitors both the inputs and the outputs of a synchronous program and (minimally) edits erroneous inputs/outputs in order to guarantee that a given property holds. We define enforceability conditions, develop an online enforcement algorithm, and prove its correctness. We also report on an implementation of the algorithm on top of the KIELER framework for the SCCharts synchronous language. Experimental results show that enforcement has minimal execution time overhead, which decreases proportionally with larger benchmarks.

cs.FL↗
arXiv2016

What's Decidable about Syntax-Guided Synthesis?

Syntax-guided synthesis (SyGuS) is a recently proposed framework for program synthesis problems. The SyGuS problem is to find an expression or program generated by a given grammar that meets a correctness specification. Correctness specifications are given as formulas in suitable logical theories, typically amongst those studied in satisfiability modulo theories (SMT). In this work, we analyze the decidability of the SyGuS problem for different classes of grammars and correctness specifications. We prove that the SyGuS problem is undecidable for the theory of equality with uninterpreted functions (EUF).We identify a fragment of EUF, which we call regular-EUF, for which the SyGuS problem is decidable. We prove that this restricted problem is EXPTIME-complete and that the sets of solution expressions are precisely the regular tree languages. For theories that admit a unique, finite domain, we give a general algorithm to solve the SyGuS problem on tree grammars. Finite-domain theories include the bit-vector theory without concatenation. We prove SyGuS undecidable for a very simple bit-vector theory with concatenation, both for context-free grammars and for tree grammars. Finally, we give some additional results for linear arithmetic and bit-vector arithmetic along with a discussion of the implication of these results.

cs.LO↗
arXiv2016

Learning Moore Machines from Input-Output Traces

The problem of learning automata from example traces (but no equivalence or membership queries) is fundamental in automata learning theory and practice. In this paper we study this problem for finite state machines with inputs and outputs, and in particular for Moore machines. We develop three algorithms for solving this problem: (1) the PTAP algorithm, which transforms a set of input-output traces into an incomplete Moore machine and then completes the machine with self-loops; (2) the PRPNI algorithm, which uses the well-known RPNI algorithm for automata learning to learn a product of automata encoding a Moore machine; and (3) the MooreMI algorithm, which directly learns a Moore machine using PTAP extended with state merging. We prove that MooreMI has the fundamental identification in the limit property. We also compare the algorithms experimentally in terms of the size of the learned machine and several notions of accuracy, introduced in this paper. Finally, we compare with OSTIA, an algorithm that learns a more general class of transducers, and find that OSTIA generally does not learn a Moore machine, even when fed with a characteristic sample.

cs.FL↗
arXiv2016

Towards Compositional Feedback in Non-Deterministic and Non-Input-Receptive Systems

Feedback is an essential composition operator in many classes of reactive and other systems. This paper studies feedback in the context of compositional theories with refinement. Such theories allow to reason about systems on a component-by-component basis, and to characterize substitutability as a refinement relation. Although compositional theories of feedback do exist, they are limited either to deterministic systems (functions) or input-receptive systems (total relations). In this work we propose a compositional theory of feedback which applies to non-deterministic and non-input-receptive systems (e.g., partial relations). To achieve this, we use the semantic frameworks of predicate and property transformers, and relations with fail and unknown values. We show how to define instantaneous feedback for stateless systems and feedback with unit delay for stateful systems. Both operations preserve the refinement relation, and both can be applied to non-deterministic and non-input-receptive systems.

cs.SE↗
arXiv2015

Translating Hierarchical Block Diagrams into Composite Predicate Transformers

Simulink is the de facto industrial standard for designing embedded control systems. When dealing with the formal verification of Simulink models, we face the problem of translating the graphical language of Simulink, namely, hierarchical block diagrams (HBDs), into a formalism suitable for verification. In this paper, we study the translation of HBDs into the compositional refinement calculus framework for reactive systems. Specifically, we consider as target language an algebra of atomic predicate transformers to capture basic Simulink blocks (both stateless and stateful), composed in series, in parallel, and in feedback. For a given HBD, there are many possible ways to translate it into a term in this algebra, with different tradeoffs. We explore these tradeoffs, and present three translation algorithms. We report on a prototype implementation of these algorithms in a tool that translates Simulink models into algebra terms implemented in the Isabelle theorem prover. We test our tool on several case studies including a benchmark Simulink model by Toyota. We compare the three translation algorithms, with respect to size and readability of generated terms, simplifiability of the corresponding formulas, and other metrics.

cs.SE↗
arXiv2015

Automatic Completion of Distributed Protocols with Symmetry

A distributed protocol is typically modeled as a set of communicating processes, where each process is described as an extended state machine along with fairness assumptions, and its correctness is specified using safety and liveness requirements. Designing correct distributed protocols is a challenging task. Aimed at simplifying this task, we allow the designer to leave some of the guards and updates to state variables in the description of extended state machines as unknown functions. The protocol completion problem then is to find interpretations for these unknown functions while guaranteeing correctness. In many distributed protocols, process behaviors are naturally symmetric, and thus, synthesized expressions are further required to obey symmetry constraints. Our counterexample-guided synthesis algorithm consists of repeatedly invoking two phases. In the first phase, candidates for unknown expressions are generated using the SMT solver Z3. This phase requires carefully orchestrating constraints to enforce the desired symmetry in read/write accesses. In the second phase, the resulting completed protocol is checked for correctness using a custom-built model checker that handles fairness assumptions, safety and liveness requirements, and exploits symmetry. When model checking fails, our tool examines a set of counterexamples to safety/liveness properties to generate constraints on unknown functions that must be satisfied by subsequent completions. For evaluation, we show that our prototype is able to automatically discover interesting missing details in distributed protocols for mutual exclusion, self stabilization, and cache coherence.

cs.FL↗
arXiv2014

Refinement Calculus of Reactive Systems

Refinement calculus is a powerful and expressive tool for reasoning about sequential programs in a compositional manner. In this paper we present an extension of refinement calculus for reactive systems. Refinement calculus is based on monotonic predicate transformers, which transform sets of post-states into sets of pre-states. To model reactive systems, we introduce monotonic property transformers, which transform sets of output traces into sets of input traces. We show how to model in this semantics refinement, sequential composition, demonic choice, and other semantic operations on reactive systems. We use primarily higher order logic to express our results, but we also show how property transformers can be defined using other formalisms more amenable to automation, such as linear temporal logic (suitable for specifications) and symbolic transition systems (suitable for implementations). Finally, we show how this framework generalizes previous work on relational interfaces so as to be able to express systems with infinite behaviors and liveness properties.

cs.SE↗
arXiv2014

Synthesizing Finite-state Protocols from Scenarios and Requirements

Scenarios, or Message Sequence Charts, offer an intuitive way of describing the desired behaviors of a distributed protocol. In this paper we propose a new way of specifying finite-state protocols using scenarios: we show that it is possible to automatically derive a distributed implementation from a set of scenarios augmented with a set of safety and liveness requirements, provided the given scenarios adequately \emph{cover} all the states of the desired implementation. We first derive incomplete state machines from the given scenarios, and then synthesis corresponds to completing the transition relation of individual processes so that the global product meets the specified requirements. This completion problem, in general, has the same complexity, PSPACE, as the verification problem, but unlike the verification problem, is NP-complete for a constant number of processes. We present two algorithms for solving the completion problem, one based on a heuristic search in the space of possible completions and one based on OBDD-based symbolic fixpoint computation. We evaluate the proposed methodology for protocol specification and the effectiveness of the synthesis algorithms using the classical alternating-bit protocol.

cs.FL↗
arXiv2010

Fault Diagnosis with Dynamic Observers

In this paper, we review some recent results about the use of dynamic observers for fault diagnosis of discrete event systems. Fault diagnosis consists in synthesizing a diagnoser that observes a given plant and identifies faults in the plant as soon as possible after their occurrence. Existing literature on this problem has considered the case of fixed static observers, where the set of observable events is fixed and does not change during execution of the system. In this paper, we consider dynamic observers: an observer can "switch" sensors on or off, thus dynamically changing the set of events it wishes to observe. It is known that checking diagnosability (i.e., whether a given observer is capable of identifying faults) can be solved in polynomial time for static observers, and we show that the same is true for dynamic ones. We also solve the problem of dynamic observers' synthesis and prove that a most permissive observer can be computed in doubly exponential time, using a game-theoretic approach. We further investigate optimization problems for dynamic observers and define a notion of cost of an observer.

cs.FL↗