A Two-Component Language for Adaptation: Design, Semantics and Program Analysis

Degano, Pierpaolo; Ferrari, Gian Luigi; Galletta, Letterio

doi:10.1109/tse.2015.2496941

Cited by 11 publications

(27 citation statements)

References 75 publications

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“…Our semantics supports recovery in these cases. A non trivial effort is needed to extend the static analysis of [7] that guarantees adaptations to be always successful. We plan to carry on this check at run-time, when a behavioural variation is about to run.…”

Section: Resultsmentioning

confidence: 99%

“…Abstractly, it could be considered as a heterogeneous collection of data coming from different sources and having different representations. In [7] we adopted a declarative approach to deal with the context: it is a knowledge base implemented as a Datalog program, following a well-studied approach [10,9]. Hence, programmers can concentrate on what information the context has to include, leaving to the runtime support how this information is actually collected and managed.…”

Section: An Examplementioning

confidence: 99%

“…In this section we introduce our formal model by extending the semantics of ML CoDa presented in [7]. As discussed above, the context "virtualises" smart objects by providing them with a common interface and a communication infrastructure through which they can interact.…”

Section: The Languagementioning

confidence: 99%

“…Syntax The syntax of the Datalog component is standard so here we assume it given [5]. The syntax of the functional part is the following where we denote with F and G Datalog facts and goals, respectively: It is an extension of the one presented in [7]: values are constants, functions (here written in the standard λ -notation and in the example declared via the keyword fun), behavioural variations and facts; expressions include standard ML constructs (let, if, etc. ), context-dependent binding (dlet), context updates and behavioural variation application and concatenation.…”

Section: The Languagementioning

confidence: 99%

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Event-driven Adaptation in COP

Degano

Ferrari

Galletta

2016

Electron. Proc. Theor. Comput. Sci.

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Context-Oriented Programming languages provide us with primitive constructs to adapt program behaviour depending on the evolution of their operational environment, namely the context. In previous work we proposed ML_CoDa, a context-oriented language with two-components: a declarative constituent for programming the context and a functional one for computing. This paper describes an extension of ML_CoDa to deal with adaptation to unpredictable context changes notified by asynchronous events.Comment: In Proceedings PLACES 2016, arXiv:1606.0540

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Section: Resultsmentioning

confidence: 99%

Section: An Examplementioning

confidence: 99%

Section: The Languagementioning

confidence: 99%

Section: The Languagementioning

confidence: 99%

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Event-driven Adaptation in COP

Degano

Ferrari

Galletta

2016

Electron. Proc. Theor. Comput. Sci.

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“…Subjective-C [23], an extension of Objective-C with COP, adopts imperative context activation with imperative context relationship description, which supports various kinds of declarations of dependency between layers, such as implication, requirement, and exclusion. Context Petri Nets [11,12] is a context-oriented extension of Petri Nets, and helps formalization of description of context dependencies in Subjective-C. M L CoDa [19,20] provides two kinds of components; one for declarative description of context dependencies and the other for functional computation. It also provides a type and effect system and a loading-time verification mechanism that detects failures in adaptation.…”

Section: Related Workmentioning

confidence: 99%

A type system for first-class layers with inheritance, subtyping, and swapping

Inoue

Igarashi

2019

Science of Computer Programming

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Context-Oriented Programming (COP) is a programming paradigm to encourage modularization of context-dependent software. Key features of COP are layers-modules to describe context-dependent behavioral variations of a software system-and their dynamic activation, which can modify the behavior of multiple objects that have already been instantiated. Typechecking programs written in a COP language is difficult because the activation of a layer can even change objects' interfaces. Inoue et al. have informally discussed how to make JCop, an extension of Java for COP by Appeltauer et al., type-safe.In this article, we formalize a small COP language called ContextFJ <: with its operational semantics and type system and show its type soundness. The language models main features of the type-safe version of JCop, including dynamically activated first-class layers, inheritance of layer definitions, layer subtyping, and layer swapping.

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Security Metrics at Work on the Things in IoT Systems

Bodei

Degano

Ferrari

et al. 2020

From Lambda Calculus to Cybersecurity Through Program Analysis

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The Internet of Things (IoT) is deeply changing our society. Daily we use smart devices that automatically collect, aggregate and exchange data about our lives. These data are often pivotal when they are used e.g. to train learning algorithms, to control cyber-physical systems, and to guide administrators to take crucial decisions. As a consequence, security attacks on devices can cause severe damages on IoT systems that take care of essential services, such as delivering power, water, transport, and so on. The difficulty of preventing intrusions or attacks is magnified by the big amount of devices and components IoT systems are composed of. Therefore, it is crucial to identify the most critical components in a network of devices and to understand their level of vulnerability, so as to detect where it is better to intervene for improving security. In this paper, we start from the modelling language IoT-LySa and from the results of Control Flow Analysis that statically predict the manipulation of data and their possible trajectories. On this basis, we aim at deriving possible graphs of how data move and which are their dependencies. These graphs can be analysed, by exploiting some security metrics -among which those introduced by Barrere, Hankin et al. -offering system administrators different estimates of the security level of their systems. Partially supported by Università di Pisa PRA_2018_66 DECLWARE: Metodologie dichiarative per la progettazione e il deployment di applicazioni and by MIUR project PRIN 2017FTXR7S IT MATTERS (Methods and Tools for Trustworthy Smart Systems). := (x c ch I check I ≥ cr I thI ). alarmI c al I , 1CR, ring .h ACR = µh.(1CR, {Ring}).τ.h

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A Two-Component Language for Adaptation: Design, Semantics and Program Analysis

Cited by 11 publications

References 75 publications

Event-driven Adaptation in COP

Event-driven Adaptation in COP

A type system for first-class layers with inheritance, subtyping, and swapping

Security Metrics at Work on the Things in IoT Systems

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