A Context-Oriented Extension of F#

Lecture Notes in Computer Science

Ferrari

et al. 2017

Self Cite

Contextual information plays an increasingly crucial role in concurrent applications in the times of mobility and pervasiveness of computing. Context-Oriented Programming languages explicitly treat this kind of information. They provide primitive constructs to adapt the behaviour of a program, depending on the evolution of its operational environment, which is affected by other programs hosted therein independently and unpredictably. We discuss these issues and the challenges they pose, reporting on our recent work on ML CoDa, a language specifically designed for adaptation and equipped with a clear formal semantics and analysis tools. We will show how applications and context interactions can be better specified, analysed and controlled, with the help of some experiments done with a preliminary implementation of ML CoDa. © Springer International Publishing AG 2017

Section: The Execution Model Of MLmentioning

confidence: 99%

Section: The Execution Model Of MLmentioning

confidence: 99%

Experimenting with a Context-Aware Language

Bodei

Lecture Notes in Computer Science

Ferrari

et al. 2017

Self Cite

“…We are currently experimenting on our language, in particular on the usage of the static analysis on more realistic examples. We are using a prototypical implementation of ML CoDa that extends F# [15] and that is available together with some case studies. 2 To do that, we exploit the well-established metaprogramming mechanisms of F#, so to both minimise the learning cost for users and to avoid the need of any modification to the compiler and to the underlying .NET runtime.…”

Section: Future Workmentioning

confidence: 99%

“…Our prototype[15] does not fully integrate the F# type system with ours; presently we only have an early implementation of our analyses.…”

mentioning

confidence: 99%

Context-aware security: Linguistic mechanisms and static analysis

Bodei

Galletta

et al. 2016

JCS

Self Cite

Adaptive systems improve their efficiency by modifying their behaviour to respond to changes in their operational\ud environment. Also, security must adapt to these changes and policy enforcement becomes dependent on the dynamic contexts.\ud We study these issues within MLCoDa, (the core of) an adaptive declarative language proposed recently. A main characteristic\ud of MLCoDa is to have two components: a logical one for handling the context and a functional one for computing. We extend\ud this language with security policies that are expressed in logical terms. They are of two different kinds: context and application\ud policies. The first, unknown a priori to an application, protect the context from unwanted changes. The others protect the\ud applications from malicious actions of the context, can be nested and can be activated and deactivated according to their scope.\ud An execution step can only occur if all the policies in force hold, under the control of an execution monitor. Beneficial to this is\ud a type and effect system, which safely approximates the behaviour of an application, and a further static analysis, based on the\ud computed effect. The last analysis can only be carried on at load time, when the execution context is known, and it enables us to\ud efficiently enforce the security policies on the code execution, by instrumenting applications. The monitor is thus implemented\ud within MLCoDa, and it is only activated on those policies that may be infringed, and switched off otherwise

“…Its higher-order facilities are essential to exchange the bundle of functionalities required to manage adaptivity. ML CoDa is equipped with a formal semantics which drove a prototypical implementation in F# [4]. Moreover, ML CoDa offers a further support through a static analysis that guarantees programs to always be able to adapt in every context [7].…”

Section: Introductionmentioning

confidence: 99%

Event-driven Adaptation in COP

Electron. Proc. Theor. Comput. Sci.

Ferrari

Galletta

2016

Self Cite

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