Requirements-driven social adaptation: Expert survey

Authors: Almaliki, M., Faniyi, F., Bahsoon, R., Phalp, K. and Ali, R.

Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume: 8396 LNCS

Pages: 72-87

eISSN: 1611-3349

ISBN: 9783319058429

ISSN: 0302-9743

DOI: 10.1007/978-3-319-05843-6_6

Abstract:

[Context and motivation] Self-adaptation empowers systems with the capability to meet stakeholders' requirements in a dynamic environment. Such systems autonomously monitor changes and events which drive adaptation decisions at runtime. Social Adaptation is a recent kind of requirements-driven adaptation which enables users to give a runtime feedback on the success and quality of a system's configurations in reaching their requirements. The system analyses users' feedback, infers their collective judgement and then uses it to shape its adaptation decisions. [Question/problem] However, there is still a lack of engineering mechanisms to guarantee a correct conduction of Social Adaptation. [Principal ideas/results] In this paper, we conduct a two-phase Expert Survey to identify core benefits, domain areas and challenges for Social Adaptation. [Contribution] Our findings provide practitioners and researchers in adaptive systems engineering with insights on this emerging role of users, or the crowd, and stimulate future research to solve the open problems in this area. © 2014 Springer International Publishing Switzerland.

Source: Scopus

Requirements-driven Social Adaptation: Expert Survey

Authors: Almaliki, M., Faniyi, F., Bahsoon, R., Phalp, K. and Ali, R.

Conference: The 20th International Working Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 2014)

Dates: 7-10 April 2014

Source: Manual

Preferred by: Keith Phalp and Raian Ali

Requirements-Driven Social Adaptation: Expert Survey.

Authors: Almaliki, M., Faniyi, F., Bahsoon, R., Phalp, K. and Ali, R.

Editors: Salinesi, C. and Weerd, I.V.D.

Journal: REFSQ

Volume: 8396

Pages: 72-87

Publisher: Springer

ISBN: 978-3-319-05842-9

https://doi.org/10.1007/978-3-319-05843-6

Source: DBLP