Title: Context-driven composition for mobile applications: a metamodelling approach

Authors: Afrah Djeddar; Hakim Bendjenna; Abdelkrim Amirat; Philippe Roose; Lawrence Chung

Addresses: Laboratory of Mathematics, Informatics and Systems (LAMIS), Department of Mathematics and Computer Science, University of Larbi Tebessi, Tebessa, 12002, Algeria ' Laboratory of Mathematics, Informatics and Systems (LAMIS), Department of Mathematics and Computer Science, University of Larbi Tebessi, Tebessa, 12002, Algeria ' Laboratory of Informatics and Mathematics (LIM), Department of Mathematics and Computer Science, University of Souk Ahras, Souk Ahras, 41000, Algeria ' LIUPPA Laboratory, Department of IUT de Bayonne, University of Pau et de pays de l'adour, 64000, France ' Department of Computer Science, University of Texas at Dallas, USA

Abstract: Nowadays, the numbers of mobile applications (apps) is undeniably explosive. This phenomenon is likely to encourage the user to expect more or less the same app to be available on just about any kind of platforms, even when there are differences in the apps that run on such platforms. In order to better fulfil user's expectations, understanding such differences - or heterogeneities - then becomes critical, as does resolving them, but is quite challenging. In this paper, we propose a technique for developing mobile device apps, through composition of existing homogeneous or heterogeneous software entities that are context-aware. As a key novelty, this technique uses a metamodelling approach in understanding and representing the differences, as well as commonalities, between reused software entities. In order to see the applicability and the effectiveness of this technique, a tool has been implemented to date, together with an application to a shop review app.

Keywords: composition; mobile app; reusing software entities; heterogeneity; context-aware; metamodelling.

DOI: 10.1504/IJES.2017.088036

International Journal of Embedded Systems, 2017 Vol.9 No.6, pp.505 - 522

Received: 17 Aug 2015
Accepted: 13 Jan 2016

Published online: 20 Nov 2017 *

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