eprintid: 3061
rev_number: 10
eprint_status: archive
userid: 69
dir: disk0/00/00/30/61
datestamp: 2016-02-12 11:52:51
lastmod: 2016-02-12 12:08:13
status_changed: 2016-02-12 11:52:57
type: article
metadata_visibility: show
creators_name: Bruni, Roberto
creators_name: Corradini, Andrea
creators_name: Gadducci, Fabio
creators_name: Lafuente, Alberto Lluch
creators_name: Vandin, Andrea
creators_id: 
creators_id: 
creators_id: 
creators_id: 
creators_id: andrea.vandin@imtlucca.it
title: Modelling and analyzing adaptive self-assembly strategies with Maude
ispublished: pub
subjects: QA75
subjects: T1
divisions: CSA
full_text_status: none
keywords: Adaptation; Maude; Reflective Russian Dolls; Statistical model checking; PVeStA
note: Selected Papers from the Ninth International Workshop on Rewriting Logic and its Applications (WRLA 2012)
abstract: Building adaptive systems with predictable emergent behavior is a difficult task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures to programming paradigms and analysis techniques. Our white-box conceptual approach to adaptive systems based on the notion of control data promotes a clear distinction between the application and the adaptation logic. In this paper we propose a concrete instance of our approach based on (i) a neat identification of control data; (ii) a hierarchical architecture that provides the basic structure to separate the adaptation and application logics; (iii) computational reflection as the main mechanism to realize the adaptation logic; (iv) probabilistic rule-based specifications and quantitative verification techniques to specify and analyze the adaptation logic. We show that our solution can be naturally realized in Maude, a Rewriting Logic based framework, and illustrate our approach by specifying, validating and analyzing a prominent example of adaptive systems: robot swarms equipped with self-assembly strategies.
date: 2015
date_type: published
publication: Science of Computer Programming
volume: 99
publisher: Elsevier
pagerange: 75 - 94
id_number: 10.1016/j.scico.2013.11.043
refereed: TRUE
issn: 0167-6423
official_url: http://www.sciencedirect.com/science/article/pii/S0167642313003389
projects: QUANTICOL
citation:   Bruni, Roberto and Corradini, Andrea and Gadducci, Fabio and Lafuente, Alberto Lluch and Vandin, Andrea  Modelling and analyzing adaptive self-assembly strategies with Maude.  Science of Computer Programming, 99.  75 - 94.  ISSN 0167-6423      (2015)