Notion Of Refinement Research Articles

Fair Asynchronous Session Subtyping

Session types are widely used as abstractions of asynchronous message passing systems. Refinement for such abstractions is crucial as it allows improvements of a given component without compromising its compatibility with the rest of the system. In the context of session types, the most general notion of refinement is asynchronous session subtyping, which allows message emissions to be anticipated w.r.t. a bounded amount of message consumptions. In this paper we investigate the possibility to anticipate emissions w.r.t. an unbounded amount of consumptions: to this aim we propose to consider fair compliance over asynchronous session types and fair refinement as the relation that preserves it. This allows us to propose a novel variant of session subtyping that leverages the notion of controllability from service contract theory and that is a sound characterisation of fair refinement. In addition, we show that both fair refinement and our novel subtyping are undecidable. We also present a sound algorithm which deals with examples that feature potentially unbounded buffering. Finally, we present an implementation of our algorithm and an empirical evaluation of it on synthetic benchmarks.

Coherent modal transition systems refinement

Modal Transition Systems (MTS) are a well-known formalism that extend Labelled Transition Systems (LTS) with the possibility of specifying necessary and permitted behaviour. Coherent MTS (CMTS) have been introduced to model Software Product Lines (SPL) based on a correspondence between the necessary and permitted modalities of MTS transitions and their associated actions, and the core and optional features of SPL. In this paper, we address open problems of the coherent fragment of MTS and introduce the notions of refinement and thorough refinement of CMTS. Most notably, we prove that refinement and thorough refinement coincide for CMTS, while it is known that this is not the case for MTS. We also define (thorough) equivalence and strong bisimilarity of both MTS and CMTS. We show their relations and, in particular, we prove that also strong bisimilarity and equivalence coincide for CMTS, whereas they do not for MTS. Finally, we extend our investigation to CMTS equipped with Constraints (MTSC), originally introduced to express alternative behaviour, and we prove that novel notions of refinement and strong thorough refinement coincide for MTSC, and so do their extensions to strong (thorough) equivalence and strong bisimilarity.

Composition of Behavioural Assume–Guarantee Contracts

The growing complexity of modern engineering systems necessitates a method for design and analysis that is inherently modular. Methods based on using contracts for system design have successfully tackled this issue for a variety of system classes, but mostly in the context of discrete software systems. Motivated by this, we present assume-guarantee contracts for continuous linear dynamical systems with inputs and outputs. Such contracts serve as system specifications through two aspects. The assumptions specify the dynamic behaviour of the environment of the system, which provides inputs for it, while the guarantees specify the desired dynamic behaviour of the output of the system when interconnected with a relevant environment. This is formalized by utilizing the behavioural approach to system theory. We define and characterize notions of contract implementation and contract refinement, where the latter is used to compare contracts. We also define and characterize two notions of contract composition that allow one to reason about two types of system interconnections: series and feedback. The properties of refinement and composition allow contracts to be used for modular design and analysis.

Exact and Soft Successive Refinement of the Information Bottleneck.

The information bottleneck (IB) framework formalises the essential requirement for efficient information processing systems to achieve an optimal balance between the complexity of their representation and the amount of information extracted about relevant features. However, since the representation complexity affordable by real-world systems may vary in time, the processing cost of updating the representations should also be taken into account. A crucial question is thus the extent to which adaptive systems can leverage the information content of already existing IB-optimal representations for producing new ones, which target the same relevant features but at a different granularity. We investigate the information-theoretic optimal limits of this process by studying and extending, within the IB framework, the notion of successive refinement, which describes the ideal situation where no information needs to be discarded for adapting an IB-optimal representation's granularity. Thanks in particular to a new geometric characterisation, we analytically derive the successive refinability of some specific IB problems (for binary variables, for jointly Gaussian variables, and for the relevancy variable being a deterministic function of the source variable), and provide a linear-programming-based tool to numerically investigate, in the discrete case, the successive refinement of the IB. We then soften this notion into a quantification of the loss of information optimality induced by several-stage processing through an existing measure of unique information. Simple numerical experiments suggest that this quantity is typically low, though not entirely negligible. These results could have important implications for (i) the structure and efficiency of incremental learning in biological and artificial agents, (ii) the comparison of IB-optimal observation channels in statistical decision problems, and (iii) the IB theory of deep neural networks.

Belief contraction and erasure in fragments of propositional logic

Abstract Recently, belief change within the framework of fragments of propositional logic has gained attention. In the context of revision, it has been proposed to refine existing operators so that they operate within propositional fragments and that the result of revision remains in the fragment under consideration. Later, this notion of refinement was generalized to belief change operators. Whereas refinement allowed one to define concrete rational operators adapted to propositional fragments in the context of revision and update, it has to be specified for contraction and erasure. We propose a specific notion of refinement for contraction and erasure operators, called reasonable refinement. This allows us to provide refined contraction and erasure operators that satisfy the basic postulates. We study the logical properties of reasonable refinement of two model-based contraction operators and two model-based erasure operators. Our approach is not limited to the Horn fragment but applicable to many fragments of propositional logic, like Krom and affine fragments.

Formal verification and validation of run-to-completion style state charts using Event-B

State chart notations with ‘run to completion’ semantics are popular with engineers for designing controllers that react to environment events with a sequence of state transitions but lack formal refinement and rigorous verification methods. State chart models are typically used to design complex control systems that respond to environmental triggers with a sequential process. The model is usually constructed at a concrete level and verified and validated using animation techniques relying on human judgement. Event-B, on the other hand, is based on refinement from an initial abstraction and is designed to make formal verification by automatic theorem provers feasible. ion and formal verification provide greater assurance that critical (e.g. safety or security) properties are not violated by the control system. In this paper, we introduce a notion of refinement into a ‘run to completion’ state chart modelling notation and leverage Event-B’s tool support for theorem proving. We describe the difficulties in translating ‘run to completion’ semantics into Event-B refinements and suggest a solution. We illustrate our approach and show how models can be validated at different refinement levels using our scenario checker animation tools. We show how critical invariant properties can be verified by proof despite the reactive nature of the system and how behavioural aspects of the system can be verified by testing the expected reactions using a temporal logic, model checking approach. To verify liveness, we outline a proof that the run to completion is deadlock-free and converges to complete the run.

A relational theory of effects and coeffects

Graded modal types systems and coeffects are becoming a standard formalism to deal with context-dependent, usage-sensitive computations, especially when combined with computational effects. From a semantic perspective, effectful and coeffectful languages have been studied mostly by means of denotational semantics and almost nothing has been done from the point of view of relational reasoning. This gap in the literature is quite surprising, since many cornerstone results — such asnon-interference,metric preservation, andproof irrelevance— on concrete coeffects are inherently relational. In this paper, we fill this gap by developing a general theory and calculus of program relations for higher-order languages with combined effects and coeffects. The relational calculus builds upon the novel notion of acorelator(orcomonadic lax extension) to handle coeffects relationally. Inside such a calculus, we define three notions of effectful and coeffectful program refinements:contextual approximation,logical preorder, andapplicative similarity. These are the first operationally-based notions of program refinement (and, consequently, equivalence) for languages with combined effects and coeffects appearing in the literature. We show that the axiomatics of a corelator (together with the one of a relator) is precisely what is needed to prove all the aforementioned program refinements to be precongruences, this way obtaining compositional relational techniques for reasoning about combined effects and coeffects.

Model Theory in a Paraconsistent Environment

AbstractThe purpose of this thesis is to develop a paraconsistent Model Theory. The basis for such a theory was launched by Walter Carnielli, Marcelo Esteban Coniglio, Rodrigo Podiack, and Tarcísio Rodrigues in the article ‘On the Way to a Wider Model Theory: Completeness Theorems for First-Order Logics of Formal Inconsistency’ [The Review of Symbolic Logic, vol. 7 (2014)].Naturally, a complete theory cannot be fully developed in a single work. Indeed, the goal of this work is to show that a paraconsistent Model Theory is a sound and worthy possibility. The pursuit of this goal is divided in three tasks: The first one is to give the theory a philosophical meaning. The second one is to transpose as many results from the classical theory to the new one as possible. The third one is to show an application of the theory to practical science.The response to the first task is a Paraconsistent Reasoning System. The start point is that paraconsistency is an epistemological concept. The pursuit of a deeper understanding of the phenomenon of paraconsistency from this point of view leads to a reasoning system based on the Logics of Formal Inconsistency. Models are regarded as states of knowledge and the concept of isomorphism is reformulated so as to give raise to a new concept that preserves a portion of the whole knowledge of each state. Based on this, a notion of refinement is created which may occur from inside or from outside the state.In order to respond to the second task, two important classical results, namely the Omitting Types Theorem and Craig’s Interpolation Theorem are shown to hold in the new system and it is also shown that, if classical results in general are to hold in a paraconsistent system, then such a system should be in essence how it was developed here.Finally, the response to the third task is a proposal of what a Paraconsistent Logic Programming may be. For that, the basis for a paraconsistent PROLOG is settled in the light of the ideas developed so far.Abstract prepared by Bruno Costa Coscarelli.E-mail: brunocostacoscarelli@gmail.comURL: http://repositorio.unicamp.br/jspui/handle/REPOSIP/331697

VulDeeLocator: A Deep Learning-Based Fine-Grained Vulnerability Detector

Automatically detecting software vulnerabilities is an important problem that has attracted much attention from the academic research community. However, existing vulnerability detectors still cannot achieve the vulnerability detection capability and the locating precision that would warrant their adoption for real-world use. In this paper, we present a vulnerability detector that can simultaneously achieve a high detection capability and a high locating precision, dubbed Vulnerability Deep learning-based Locator (VulDeeLocator). In the course of designing VulDeeLocator, we encounter difficulties including how to accommodate semantic relations between the definitions of types as well as macros and their uses across files, how to accommodate accurate control flows and variable define-use relations, and how to achieve high locating precision. We solve these difficulties by using two innovative ideas: (i) leveraging intermediate code to accommodate extra semantic information, and (ii) using the notion of granularity refinement to pin down locations of vulnerabilities. When applied to 200 files randomly selected from three real-world software products, VulDeeLocator detects 18 confirmed vulnerabilities (i.e., true-positives). Among them, 16 vulnerabilities correspond to known vulnerabilities; the other two are not reported in the National Vulnerability Database (NVD) but have been "silently" patched by the vendor of Libav when releasing newer versions.

Verified secure compilation for mixed-sensitivity concurrent programs

Abstract Proving only over source code that programs do not leak sensitive data leaves a gap between reasoning and reality that can only be filled by accounting for the behaviour of the compiler. Furthermore, software does not always have the luxury of limiting itself to single-threaded computation with resources statically dedicated to each user to ensure the confidentiality of their data. This results in mixed-sensitivity concurrent programs, which might reuse memory shared between their threads to hold data of different sensitivity levels at different times; for such programs, a compiler must preserve the value-dependent coordination of such mixed-sensitivity reuse despite the impact of concurrency. Here we demonstrate, using Isabelle/HOL, that it is feasible to verify that a compiler preserves noninterference, the strictest kind of confidentiality property, for mixed-sensitivity concurrent programs. First, we present notions of refinement that preserve a concurrent value-dependent notion of noninterference that we have designed to support such programs. As proving noninterference-preserving refinement can be considerably more complex than the standard refinements typically used to verify semantics-preserving compilation, our notions include a decomposition principle that separates the semantics preservation from security preservation concerns. Second, we demonstrate that these refinement notions are applicable to verified secure compilation, by exercising them on a single-pass compiler for mixed-sensitivity concurrent programs that synchronise using mutex locks, from a generic imperative language to a generic RISC-style assembly language. Finally, we execute our compiler on a non-trivial mixed-sensitivity concurrent program modelling a real-world use case, thus preserving its source-level noninterference properties down to an assembly-level model automatically. All results are formalised and proved in the Isabelle/HOL interactive proof assistant. Our work paves the way for more fully featured compilers to offer verified secure compilation support to developers of multithreaded software that must handle data of multiple sensitivity levels.

Curating the Caribbean: unsettling the boundaries of art and artefact

ABSTRACT In this paper, we consider the material and visual implications of coloniality – the darker side of modernity, and structure of management that underpins and supports modernity’s rhetoric of promises – within the circum-Caribbean through a reflection on curating the exhibition Decolonising Refinement: Contemporary Pursuits in the Art of Edouard Duval-Carrié. By juxtaposing the recent work of Haitian-born American painter and sculptor Edouard Duval-Carrié (1954b) and a selection of historical artefacts from the Southeastern US we bring to light the recursive patterns of colonialism and exploitation in which the Gulf region has been culturally, economically, and politically entangled. Our collaborative exhibition deconstructs the notion of refinement both in the aesthetic sense and also as processes by which a resource becomes a product. For Duval-Carrié, the Caribbean is not merely a case study for these broader global dynamics, but rather the crucible from which the modern, industrial age emerges. We thus approach this exhibition as an experiment in decolonising the museum – itself a tool of coloniality – by creating dynamic visual and material relationships in the gallery that deny the viewer the convenient binaries of past/present, art/artefact, and US/Caribbean, and thus forge new possibilities for a kind of decolonial museality that reflects upon its own medial limitations.

Refining Indeterministic Choice: Imprecise Probabilities and Strategic Thinking

Often, uncertainty is present in processes that are part of our routines. Having tools to understand the consequences of unpredictability is convenient. We introduce a general framework to deal with uncertainty in the realm of distribution sets that are descriptions of imprecise probabilities. We propose several non-biased refinement strategies to obtain sensible forecasts about results of uncertain processes. Initially, uncertainty on a system is modeled as the non-deterministic choice of its possible behaviors. Our refinement hypothesis translates non-determinism into imprecise probabilistic choices. Imprecise probabilities allow us to propose a notion of uncertainty refinement in terms of set inclusions. Later on, unpredictability is tackled through a strategic approach using uncertainty profiles and angel/daemon games ([Formula: see text]-games). Here, imprecise probabilities form the set of mixed strategies and Nash equilibria corresponds to natural uncertainty refinements. We use this approach to study the performance of Web applications — in terms of response times — under stress conditions.

Generalized abstraction-refinement for game-based CTL lifted model checking

System families (Software Product Lines) are becoming omnipresent in application areas ranging from embedded system domains to system-level software and communication protocols. Software Product Line methods and architectures allow effective building many custom variants of a software system in these domains. In many of the applications, their rigorous verification and quality assurance are of paramount importance. Lifted model checking for system families is capable of verifying all their variants simultaneously in a single run by exploiting the similarities between the variants. The computational cost of lifted model checking still greatly depends on the number of variants (the size of configuration space), which is often huge. Variability abstractions have successfully addressed this configuration space explosion problem, giving rise to smaller abstract variability models with fewer abstract configurations. Abstract variability models are given as modal transition systems, which contain may (over-approximating) and must (under-approximating) transitions. Thus, they preserve both universal and existential CTL properties.In this work, we bring two main contributions. First, we define a novel game-based approach for variability-specific abstraction and refinement for lifted model checking of the full CTL, interpreted over 3-valued semantics. We propose a direct algorithm for solving a 3-valued (abstract) lifted model checking game. In case the result of model checking an abstract variability model is indefinite, we suggest a new notion of refinement, which eliminates indefinite results. This provides an iterative incremental variability-specific abstraction and refinement framework, where refinement is applied only where indefinite results exist and definite results from previous iterations are reused. Second, we propose a new generalized definition of abstract variability models, given as so-called generalized modal transition systems, by introducing the notion of (must) hyper-transitions. This results in more precise abstract models in which more CTL formulae can be proved or disproved. We integrate the newly defined generalized abstract variability models in the existing abstraction-refinement framework for game-based lifted model checking of CTL. Finally, we evaluate the practicality of this approach on several system families.

Object similarity measures and Pawlak’s indiscernibility on decision tables

In this paper we investigate the mathematical foundations of the notion of similarity between objects in relation to the granulations on a decision table D. First of all, we compare the endogenous granulation induced by Pawlak’s indiscernibility with the exogenous granulation induced by a similarity measure ζ defined on pairs of objects and assuming values in the unit interval. To this aim, the starting point of our analysis is the introduction of the notion of refinement of the granulation induced by an attribute subset A through the object similarity measure ζ. More in detail, we say that ζrefines the granulation induced by A if ζ assumes value 1 on a pair of objects if and only if they are A-indiscernible. Next, starting from two given families ρ and ν of numerical maps defined on pairs of admissible values of D, we determine a broad class of potential similarity measures on the objects of D refining, sometimes under some specific additional hypotheses, the A-granulation on the object set of D. With regard to a such class of similarity measures, we establish several mathematical properties. Finally, we focus our attention to the analysis of specific pairs of numerical maps ρ and ν that have been classically studied in literature and, for each of them, we exhibit the main properties with respect to the aforementioned refinement of granulation.

Inputs and Outputs in CSP

This article addresses refinement and testing based on CSP models, when we distinguish input and output events. In a testing experiment, the tester (or the environment) controls the inputs, and the system under test controls the outputs. The standard models and refinement relations of CSP, however, do not differentiate inputs and outputs and are not, therefore, entirely suitable for testing. Here, we consider an alphabet of events partitioned into inputs and outputs, and we present a novel refusal-testing model for CSP with a notion of input-output refusal-traces refinement. We compare that with the ioco relation often used in testing, and we find that it is more widely applicable and stronger. This means that mistakes found using traditional ioco testing do indicate mistakes in the development. Finally, we provide a CSP testing theory that takes into account inputs and outputs. With our theory, it becomes feasible to develop techniques and tools for automatic generation of realistic and sound tests from CSP models. Our work reconciles the normally disparate areas of refinement and (formal) testing by identifying how ioco testing can be used to inform refinement-based results and vice-versa.

A formal, scalable approach to semantic interoperability

Abstract Scientific progress is increasingly dependent upon the acquisition, processing, and analysis of large volumes of data. The validity of results and the safety of applications rely upon an adequate understanding of the real-world semantics of this data: its intended interpretation, and the context in which it is acquired and processed. This presents a challenge: interpretations vary, context is infinite, and either may change over time. This paper addresses that challenge. It introduces a language for the description of real-world semantics that allows for multiple, evolving interpretations, together with a high degree of automation in the capture and creation of contextual metadata. The language itself has a mathematical semantics, and supports a notion of semantic interoperability closely related to existing, formal notions of refinement. The language represents a scalable approach in three respects: it is compositional, in terms of composing real-world semantics piece by piece; it allows for multiple perspectives, allowing the parallel development of different interpretations; and it supports automatic transformations to and from implementation languages. The practical application of the approach is illustrated with examples from large-scale medical research.

Specification and inference of trace refinement relations

The modern software engineering process is evolutionary, with commits/patches begetting new versions of code, progressing steadily toward improved systems. In recent years, program analysis and verification tools have exploited version-based reasoning, where new code can be seen in terms of how it has changed from the previous version. When considering program versions, refinement seems a natural fit and, in recent decades, researchers have weakened classical notions of concrete refinement and program equivalence to capture similarities as well as differences between programs. For example, Benton, Yang and others have worked on state-based refinement relations . In this paper, we explore a form of weak refinement based on trace relations rather than state relations. The idea begins by partitioning traces of a program C 1 into trace classes, each identified via a restriction r 1 . For each class, we specify similar behavior in the other program C 2 via a separate restriction r 2 on C 2 . Still, these two trace classes may not yet be equivalent so we further permit a weakening via a binary relation A on traces, that allows one to, for instance disregard unimportant events, relate analogous atomic events, etc. We address several challenges that arise. First, we explore one way to specify trace refinement relations by instantiating the framework to Kleene Algebra with Tests (KAT) due to Kozen. We use KAT intersection for restriction, KAT hypotheses for A , KAT inclusion for refinement, and have proved compositionality. Next, we present an algorithm for automatically synthesizing refinement relations, based on a mixture of semantic program abstraction, KAT inclusion, a custom edit-distance algorithm on counterexamples, and case-analysis on nondeterministic branching. We have proved our algorithm to be sound. Finally, we implemented our algorithm as a tool called Knotical, on top of Interproc and Symkat. We demonstrate promising first steps in synthesizing trace refinement relations across a hand-crafted collection of 37 benchmarks that include changing fragments of array programs, models of systems code, and examples inspired by the thttpd and Merecat web servers.

Automated Reuse of Model Transformations through Typing Requirements Models

Model transformations are key elements of model-driven engineering, where they are used to automate the manipulation of models. However, they are typed with respect to concrete source and target meta-models, making their reuse for other (even similar) meta-models challenging. To improve this situation, we propose capturing the typing requirements for reusing a transformation with other meta-models by the notion of a typing requirements model (TRM). A TRM describes the prerequisites that a model transformation imposes on the source and target meta-models to obtain a correct typing. The key observation is that any meta-model pair that satisfies the TRM is a valid reuse context for the transformation at hand. A TRM is made of two domain requirement models (DRMs) describing the requirements for the source and target meta-models, and a compatibility model expressing dependencies between them. We define a notion of refinement between DRMs and see meta-models as a special case of DRM. We provide a catalogue of valid refinements and describe how to automatically extract a TRM from an ATL transformation. The approach is supported by our tool TOTEM. We report on two experiments—based on transformations developed by third parties and meta-model mutation techniques—validating the correctness and completeness of our TRM extraction procedure and confirming the power of TRMs to encode variability and support flexible reuse.

Blending under deconstruction

The cognitive-linguistic theory of conceptual blending was introduced by Fauconnier and Turner in the late 90s to provide a descriptive model and foundational approach for the (almost uniquely) human ability to invent new concepts. Whilst blending is often described as ‘fluid’ and ‘effortless’ when ascribed to humans, it becomes a highly complex, multi-paradigm problem in Artificial Intelligence. This paper aims at presenting a coherent computational narrative, focusing on how one may derive a formal reconstruction of conceptual blending from a deconstruction of the human ability of concept invention into some of its core components. It thus focuses on presenting the key facets that a computational framework for concept invention should possess. A central theme in our narrative is the notion of refinement, understood as ways of specialising or generalising concepts, an idea that can be seen as providing conceptual uniformity to a number of theoretical constructs as well as implementation efforts underlying computational versions of conceptual blending. Particular elements underlying our reconstruction effort include ontologies and ontology-based reasoning, image schema theory, spatio-temporal reasoning, abstract specification, social choice theory, and axiom pinpointing. We overview and analyse adopted solutions and then focus on open perspectives that address two core problems in computational approaches to conceptual blending: searching for the shared semantic structure between concepts—the so-called generic space in conceptual blending—and concept evaluation, i.e., to determine the value of newly found blends.

Partially safe evolution of software product lines

Software Product Lines allow the automatic generation of related products built with reusable artefacts. In this context, developers may need to perform changes and check whether products are affected. A strategy to perform such analysis is verifying behaviour preservation through the use of formal theories. The product line refinement notion requires behaviour preservation for all existing products. Nevertheless, in evolution scenarios like bug fixes, some products intentionally have their behaviour changed. To support developers in these and other unsafe scenarios, we define a theory of partial product line refinement that helps to precisely understand which products are affected by a change. This provides a kind of impact analysis that could, for example, reduce test effort, since only affected products need to be tested. We provide properties such as compositionality, which deals with changes to a specific product line element, and general properties to support developers when safe and partially safe scenarios are combined. We also define a set of transformation templates, which are classified according to their compatibility to specific types of product lines. To evaluate our work, we analyse two product lines: Linux and Soletta, to discover if our templates could be helpful in evolving these systems.