678 research outputs found
Typing Context-Dependent Behavioural Variation
Context Oriented Programming (COP) concerns the ability of programs to adapt
to changes in their running environment. A number of programming languages
endowed with COP constructs and features have been developed. However, some
foundational issues remain unclear. This paper proposes adopting static
analysis techniques to reason on and predict how programs adapt their
behaviour. We introduce a core functional language, ContextML, equipped with
COP primitives for manipulating contexts and for programming behavioural
variations. In particular, we specify the dispatching mechanism, used to select
the program fragments to be executed in the current active context. Besides the
dynamic semantics we present an annotated type system. It guarantees that the
well-typed programs adapt to any context, i.e. the dispatching mechanism always
succeeds at run-time.Comment: In Proceedings PLACES 2012, arXiv:1302.579
Event-driven Adaptation in COP
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
A Context-Oriented Extension of F#
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 the implementation of ML_CoDa as an extension of F#.Comment: In Proceedings FOCLASA 2015, arXiv:1512.0694
Enhanced Operational Semantics in Systems Biology
We are faced with a great challenge: the cross-fertilization between the fields of formal methods for concurrency, in the computer science domain, and systems biology in the biological realm
Tracing where IoT data are collected and aggregated
The Internet of Things (IoT) offers the infrastructure of the information society. It hosts smart objects that automatically collect and exchange data of various kinds, directly gathered from sensors or generated by aggregations. Suitable coordination primitives and analysis mechanisms are in order to design and reason about IoT systems, and to intercept the implied technological shifts. We address these issues from a foundational point of view. To study them, we define IoT-LySa, a process calculus endowed with a static analysis that tracks the provenance and the manipulation of IoT data, and how they flow in the system. The results of the analysis can be used by a designer to check the behaviour of smart objects, in particular to verify non-functional properties, among which security
A Process Calculus for Molecular Interaction Maps
We present the MIM calculus, a modeling formalism with a strong biological
basis, which provides biologically-meaningful operators for representing the
interaction capabilities of molecular species. The operators of the calculus
are inspired by the reaction symbols used in Molecular Interaction Maps (MIMs),
a diagrammatic notation used by biologists. Models of the calculus can be
easily derived from MIM diagrams, for which an unambiguous and executable
interpretation is thus obtained. We give a formal definition of the syntax and
semantics of the MIM calculus, and we study properties of the formalism. A case
study is also presented to show the use of the calculus for modeling
biomolecular networks.Comment: 15 pages; 8 figures; To be published on EPTCS, proceedings of MeCBIC
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