Sketch-based program synthesis allows users to guide the synthesizer by writing partial programs (sketches). Traditionally, the specifications of these sketches are safety properties expressed either as assertions or semantic equivalences. These specifications, however, lack expressiveness when the user wants to establish how the execution of the desired program evolves over time. This is especially important when synthesizing reactive programs, where the whole specification is about how the computation evolves over time. We explore an alternative method letting the user specify desired program executions as linear temporal logic (LTL) formulae. We define a method for transforming sketches with LTL assertions into sketches with only standard assertions. Specifically, for terminating programs, our method transforms and implements, within the sketch, the LTL formulae as runtime monitors. For non-terminating programs, our procedure defines and implements, into the sketch, fairness conditions (analyzing when an acceptance state of the Büchi automata equivalent to these LTL formulae occurs infinitely often). We prove the correctness of both constructions. Evaluation of our implementation in Sketch shows that our method enables the system to synthesize non-terminating programs, such as a round-robin arbiter for a variable number of devices and a lift controller for a variable number of floors. For terminating programs, our approach improves the synthesizer performance by restricting the search of program candidates without modifying the sketches structures.

Abstract We introduce pattern models, a dynamic epistemic logic for analyzing distributed systems. First, we present a version of pattern models where the full-information protocol, widely studied in distributed computability, is static in the product definition of pattern models. Next, we parametrize such a logic so as to add the capability to model dynamics of arbitrary deterministic protocols. We thus give a systematic construction of pattern models for a large variety of distributed-computing models called dynamic-network models. Using pattern models, the epistemic dynamics of a proper subclass of dynamic-network models called oblivious can be described using a static pattern model, hence using constant space. For this case, we present a sufficient unsolvability condition for the consensus task that can be easily verified analyzing the structure of the initial epistemic model and the pattern model for a given oblivious dynamic-network model.

Runtime verification is a lightweight method for monitoring the formal specification of a system during its execution. It has recently been shown that a given state predicate can be monitored consistently by a set of crash-prone asynchronous distributed monitors observing the system, only if each monitor can emit verdicts taken from a large enough finite set. We revisit this impossibility result in the concrete context of linear-time logic ( ltl ) semantics for runtime verification, that is, when the correctness of the system is specified by an ltl formula on its execution traces. First, we show that monitors synthesized based on the 4-valued semantics of ltl ( rv-ltl ) may result in inconsistent distributed monitoring, even for some simple ltl formulas. More generally, given any ltl formula φ, we relate the number of different verdicts required by the monitors for consistently monitoring φ, with a specific structural characteristic of φ called its alternation number . Specifically, we show that, for every k ≥ 0 , there is an ltl formula φ with alternation number k that cannot be verified at runtime by distributed monitors emitting verdicts from a set of cardinality smaller than k + 1. On the positive side, we define a family of logics, called distributed ltl (abbreviated as dltl ), parameterized by k ≥ 0, which refines rv-ltl by incorporating 2k + 4 truth values. Our main contribution is to show that, for every k ≥ 0, every ltl formula φ with alternation number k can be consistently monitored by distributed monitors, each running an automaton based on a (2 ⌈ k /2 ⌉ +4)-valued logic taken from the dltl family.

We introduce and describe an algorithmic transformation from the formalism of arrangements of logic-labelled finite-state machines (LLFSMs) into NuSMV modules (and its implementation as a model-to-model ATL transformation from an Ecore meta-model to the NuSMV language). Our transformation benefits from using modules and integers of NuSMV to improve the efficiency in the construction and verification of the model. Moreover, we can handle predicates about time. Thus, we enable verification of LLFSMs in the time domain. Our transformation is a considerable improvement in efficiency. Compared with earlier transformation algorithms developed by us, the one presented here produces concise NuSMV files (in an example, 130,295 lines were reduced to 418). We thus show that it is possible to automatically translate arrangements of LLFSMs to concise models that can be efficiently and formally verified.

Biochemical reaction networks are one of the most widely used formalisms in systems biology to describe the molecular mechanisms of high-level cell processes. However, modellers also reason with influence diagrams to represent the positive and negative influences between molecular species and may find an influence network useful in the process of building a reaction network. In this paper, we introduce a formalism of influence networks with forces, and equip it with a hierarchy of Boolean, Petri net, stochastic and differential semantics, similarly to reaction networks with rates. We show that the expressive power of influence networks is the same as that of reaction networks under the differential semantics, but weaker under the discrete semantics. Furthermore, the hierarchy of semantics leads us to consider a (positive) Boolean semantics that cannot test the absence of a species, that we compare with the (negative) Boolean semantics with test for absence of a species in gene regulatory networks à la Thomas. We study the monotonicity properties of the positive semantics and derive from them an algorithm to compute attractors in both the positive and negative Boolean semantics. We illustrate our results on models of the literature about the p53/Mdm2 DNA damage repair system, the circadian clock, and the influence of MAPK signaling on cell-fate decision in urinary bladder cancer.

BACKGROUND: There are recent experimental reports on the cross-regulation between molecules involved in the control of the cell cycle and the differentiation of the vulval precursor cells (VPCs) of Caenorhabditis elegans. Such discoveries provide novel clues on how the molecular mechanisms involved in the cell cycle and cell differentiation processes are coordinated during vulval development. Dynamic computational models are helpful to understand the integrated regulatory mechanisms affecting these cellular processes. RESULTS: Here we propose a simplified model of the regulatory network that includes sufficient molecules involved in the control of both the cell cycle and cell differentiation in the C. elegans vulva to recover their dynamic behavior. We first infer both the topology and the update rules of the cell cycle module from an expected time series. Next, we use a symbolic algorithmic approach to find which interactions must be included in the regulatory network. Finally, we use a continuous-time version of the update rules for the cell cycle module to validate the cyclic behavior of the network, as well as to rule out the presence of potential artifacts due to the synchronous updating of the discrete model. We analyze the dynamical behavior of the model for the wild type and several mutants, finding that most of the results are consistent with published experimental results. CONCLUSIONS: Our model shows that the regulation of Notch signaling by the cell cycle preserves the potential of the VPCs and the three vulval fates to differentiate and de-differentiate, allowing them to remain completely responsive to the concentration of LIN-3 and lateral signal in the extracellular microenvironment.

We present a nondeterministic, recursive algorithm for updating a Kripke model so as to satisfy a given formula of computation-tree logic (CTL). Recursive algorithms for model update face two dual difficulties: (1) Removing transitions from a Kripke model to satisfy a universal subformula may dissatisfy some existential subformulas. Conversely, (2) adding transitions to satisfy an existential subformula may dissatisfy some universal subformulas. To overcome these difficulties, we employ protections of the form 〈 E , A , L 〉 , recording information about the satisfaction of subformulas previously treated by the algorithm. Intuitively, (1) E is the set of transitions that we cannot remove without compromising the satisfaction of previously treated subformulas. Conversely, (2) A is the set of transitions that we can add . Hence, update proceeds without diminishing E and without augmenting A . Finally, (3) L is a set of literals protecting the model labels. We illustrate our algorithm through several examples: Emerson and Clarke's mutual-exclusion problem, Clarke et. al.'s microwave-oven example, synchronous counters, and randomly generated models and formulas. In addition, we compare our method with other update approaches for either CTL or fragments of CTL. Lastly, we provide proofs of soundness and completeness and a complexity analysis.

The extended mind hypothesis has stimulated much interest in cognitive science. However, its core claim, i.e. that the process of cognition can extend beyond the brain via the body and into the environment, has been heavily criticized. A prominent critique of this claim holds that when some part of the world is coupled to a cognitive system this does not necessarily entail that the part is also constitutive of that cognitive system. This critique is known as the “coupling-constitution fallacy”. In this paper we respond to this reductionist challenge by using an evolutionary robotics approach to create a minimal model of two acoustically coupled agents. We demonstrate how the interaction process as a whole has properties that cannot be reduced to the contributions of the isolated agents. We also show that the neural dynamics of the coupled agents has formal properties that are inherently impossible for those neural networks in isolation. By keeping the complexity of the model to an absolute minimum, we are able to illustrate how the coupling-constitution fallacy is in fact based on an inadequate understanding of the constitutive role of nonlinear interactions in dynamical systems theory.

We propose vectors of finite-state machines whose transitions are labeled by formulas of a common-sense logic as the modeling tool for embedded systems software. We have previously shown that this methodology is very efficient in producing succinct and clear models (e.g., in contrast to plain finite-state machines, Petri nets, or Behavior Trees). We show that we can capture requirements precisely and that we can simulate and validate the models. We can, therefore, directly apply Model-Driven Engineering and deploy the models into software for diverse platforms with full tractability of requirements. Moreover, the sequential semantics of our vector of finite-state machines enables model-checking, formally establishing the correctness of the model. Finally, our approach facilitates systematic Failure Modes and Effects Analysis (FMEA) for diverse target platforms. We demonstrate the effectiveness of our methodology with several examples widely discussed in the software engineering literature and compare this with other approaches, showing that we can prove more properties, and that some claims about verification in such approaches have been exaggerated or are incomplete.

BACKGROUND: In Thomas' formalism for modeling gene regulatory networks (GRNs), branching time, where a state can have more than one possible future, plays a prominent role. By representing a certain degree of unpredictability, branching time can model several important phenomena, such as (a) asynchrony, (b) incompletely specified behavior, and (c) interaction with the environment. Introducing more than one possible future for a state, however, creates a difficulty for ordinary simulators, because infinitely many paths may appear, limiting ordinary simulators to statistical conclusions. Model checkers for branching time, by contrast, are able to prove properties in the presence of infinitely many paths. RESULTS: We have developed Antelope ("Analysis of Networks through TEmporal-LOgic sPEcifications", http://turing.iimas.unam.mx:8080/AntelopeWEB/), a model checker for analyzing and constructing Boolean GRNs. Currently, software systems for Boolean GRNs use branching time almost exclusively for asynchrony. Antelope, by contrast, also uses branching time for incompletely specified behavior and environment interaction. We show the usefulness of modeling these two phenomena in the development of a Boolean GRN of the Arabidopsis thaliana root stem cell niche.There are two obstacles to a direct approach when applying model checking to Boolean GRN analysis. First, ordinary model checkers normally only verify whether or not a given set of model states has a given property. In comparison, a model checker for Boolean GRNs is preferable if it reports the set of states having a desired property. Second, for efficiency, the expressiveness of many model checkers is limited, resulting in the inability to express some interesting properties of Boolean GRNs.Antelope tries to overcome these two drawbacks: Apart from reporting the set of all states having a given property, our model checker can express, at the expense of efficiency, some properties that ordinary model checkers (e.g., NuSMV) cannot. This additional expressiveness is achieved by employing a logic extending the standard Computation-Tree Logic (CTL) with hybrid-logic operators. CONCLUSIONS: We illustrate the advantages of Antelope when (a) modeling incomplete networks and environment interaction, (b) exhibiting the set of all states having a given property, and (c) representing Boolean GRN properties with hybrid CTL.

Many metainterpreters found in the logic programming literature are nondeterministic in the sense that the selection of program clauses is not determined. Examples are the familiar ‘demo’ and ‘vanilla’ metainterpreters. For some applications this nondeterminism is convenient. In some cases, however, a deterministic metainterpreter, having an explicit selection of clauses, is needed. Such cases include (1) conversion of OR parallelism into AND parallelism for ‘committed-choice’ processors, (2) logic-based, imperative-language implementation of search strategies, and (3) simulation of bounded-resource reasoning. Deterministic metainterpreters are difficult to write because the programmer must be concerned about the set of unifiers of the children of a node in the derivation tree. We argue that it is both possible and advantageous to write these metainterpreters by reasoning in terms of object programs converted into a syntactically restricted form that we call ‘chain’ form, where we can forget about unification, except for unit clauses. We give two transformations converting logic programs into chain form, one for ‘moded’ programs (implicit in two existing exhaustive-traversal methods for committed-choice execution), and one for arbitrary definite programs. As illustrations of our approach we show examples of the three applications mentioned above.

Program transformation advocates the development of programs by applying a sequence of meaning-preserving rules to a specification, thereby obtaining an implementation. The cost of program development and maintenance decreases if previous, similar derivations can be reused conveniently Through the string-matching problem, we study the reuse of complete parts of the derivation of an algorithm, in the deriv ation of another, "similar" algorithm. In particular, we first derive the search stage of a variant of the Boyer--Moore algorithm, and then reuse some "dev elopments" in a derivation of the search stage of the Knuth-Morris-Pratt algorithm. Several advantages result from employing logic programming. First, we get the semantic benefit of having a logical basis. Second, we can easily exploit nondeterminism. Third, we link both deriv ations by observing that repetitive "deterministic" unfolding (i.e. sequences of unfolding steps that halt when more than one clause would be inferred) is closely related to the preprocessing stage of both algorithms.

MOTIVATION: One of the most common methodologies to identify cis-regulatory sites in regulatory regions in the DNA is that of weight matrices, as testified by several articles in this issue. An alternative to strengthen the computational predictions in regulatory regions is to develop methods that incorporate more biological properties present in such DNA regions. The grammatical implementation presented in this paper provides a concrete example in this direction. RESULTS: On the basis of the analysis of an exhaustive collection of regulatory regions in Escherichia coli, a grammatical model for the regulatory regions of sigma 70 promoters has been developed. The terminal symbols of the grammar represent individual sites for the binding of activator and repressor proteins, and include the precise position of sites in relation to transcription initiation. Combining these symbols, the grammar generates a large number of different sentences, each of which can be searched for matching against a collection of regulatory regions by means of weight matrices specific for each set of sites for individual proteins. On the basis of this grammatical model, a Prolog syntactic recognizer is presented here. Specific subgrammars for ArgR, LexA and TyrR were implemented. When parsing a collection of 128 sigma 70 promoter regions, the syntactic recognizer produces a much lower number of false-positive sites than the standard search using weight matrices.