Feed me, Feed me: An Exemplar for Engineering Adaptive Software

Bennaceur, Amel; Mccormick, Ciaran; García Galán, Jesús; Perera, Charith; Smith, Andrew; Zisman, Andrea and Nuseibeh, Bashar (2016). Feed me, Feed me: An Exemplar for Engineering Adaptive Software. In: 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, 16-17 May 2016.

Abstract

The Internet of Things (IoT) promises to deliver improved quality of life for citizens, through pervasive connectivity and quantified monitoring of devices, people, and their environment. As such, the IoT presents a major new opportunity for research in adaptive software engineering. However, there are currently no shared exemplars that can support software engineering researchers to explore and potentially address the challenges of engineering adaptive software for the IoT, and to comparatively evaluate proposed solutions. In this paper, we present Feed me, Feed me, an exemplar that represents an IoT-based ecosystem to support food security at different levels of granularity: individuals, families, cities, and nations.
We describe this exemplar using animated videos which highlight the requirements that have been informally observed to play a critical role in the success or failure of IoT-based software systems. These requirements are: security and privacy, interoperability, adaptation, and personalisation. To elicit a wide spectrum of user reactions, we created these animated videos based on the ContraVision empirical methodology, which specifically supports the elicitation of end-user requirements for controversial or futuristic technologies. Our deployment of ContraVision presented our pilot study subjects with an equal number of utopian and dystopian scenarios, derived from the food security domain, and described them at the different level of granularity.
Our synthesis of the preliminary empirical findings suggests a number of key requirements and software engineering research challenges in this area. We offer these to the research community, together with a rich exemplar and associated scenarios available in both their textual form in the paper, and as a series of animated videos (http://sead1.open.ac.uk/fmfm/).

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About

• Item ORO ID
• 45597
• Item Type
• Conference or Workshop Item
• Project Funding Details

• Funded Project Name	Project ID	Funding Body
  Adaptive Security and Privacy - ASAP	291652	ERC
  Not Set	10/CE/I1855 and 13/RC/2094	SFI
  Privacy Dynamics: Learning from the wisdom of groups (XC-12-062-BN)	EP/K033522/1	EPSRC (Engineering and Physical Sciences Research Council)
  Monetize Me? Privacy and the Quantified Self in the Digital Economy	EP/L021285/1	EPSRC (Engineering and Physical Sciences Research Council)

• Keywords
• Requirements; Internet of Things; mediator synthesis; feature models; collaborative adaptation
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Research Group
• Centre for Research in Computing (CRC)
  eSTEeM
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• Copyright Holders
• © 2016 ACM
• Depositing User
• Amel Bennaceur