UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Generalized observational slicing for tree-represented modelling languages

Gold, NE; Binkley, D; Harman, M; Islam, S; Krinke, J; Yoo, S; (2017) Generalized observational slicing for tree-represented modelling languages. In: Bodden, E and Schäfer, W and Van Deursen, A and Zisman, A, (eds.) ESEC/FSE 2017: Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering. (pp. pp. 547-558). Association for Computing Machinery (ACM): New York, NY, USA. Green open access

[img]
Preview
Text
Gold_it(2).pdf - Accepted version

Download (740kB) | Preview

Abstract

Model-driven software engineering raises the abstraction level making complex systems easier to understand than if written in textual code. Nevertheless, large complicated software systems can have large models, motivating the need for slicing techniques that reduce the size of a model. We present a generalization of observation-based slicing that allows the criterion to be defined using a variety of kinds of observable behavior and does not require any complex dependence analysis. We apply our implementation of generalized observational slicing for tree-structured representations to Simulink models. The resulting slice might be the subset of the original model responsible for an observed failure or simply the sub-model semantically related to a classic slicing criterion. Unlike its predecessors, the algorithm is also capable of slicing embedded Stateflow state machines. A study of nine real-world models drawn from four different application domains demonstrates the effectiveness of our approach at dramatically reducing Simulink model sizes for realistic observation scenarios: for 9 out of 20 cases, the resulting model has fewer than 25% of the original model's elements.

Type: Proceedings paper
Title: Generalized observational slicing for tree-represented modelling languages
Event: 2017 11th Joint Meeting on Foundations of Software Engineering (ESEC/FSE 2017)
Location: Paderborn, Germany
Dates: 04 September 2017 - 08 September 2017
ISBN-13: 9781450351058
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3106237.3106304
Publisher version: http://dx.doi.org/10.1145/3106237.3106304
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Slicing, ORBS, Simulink, MATLAB, Observational Slicing
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1561648
Downloads since deposit
97Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item