By Lin Liu, Mikio Aoyama (eds.)
This publication constitutes the lawsuits of the second one Asia Pacific necessities Engineering Symposium, APRES 2015, held in Wuhan, China, in October 2015.
The nine complete papers provided including three device demos papers and one brief paper, have been rigorously reviewed and chosen from 18 submissions. The papers take care of numerous elements of necessities engineering within the mammoth info period, similar to computerized standards research, necessities acquisition through crowdsourcing, requirement procedures and necessities, standards engineering tools.requirements engineering within the gigantic info period, similar to automatic requisites research, necessities acquisition through crowdsourcing, requirement approaches and requisites, necessities engineering tools.
Read Online or Download Requirements Engineering in the Big Data Era: Second Asia Pacific Symposium, APRES 2015, Wuhan, China, October 18–20, 2015, Proceedings PDF
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Extra resources for Requirements Engineering in the Big Data Era: Second Asia Pacific Symposium, APRES 2015, Wuhan, China, October 18–20, 2015, Proceedings
Finally, an evaluation of our method is provided by a case study at the end of the paper. Keywords: Adaptive User Interface (AUI) · Model-Based User Interface (MBUI) · Requirements Engineering (RE) · Self-Adaptive System (SAS) · User Interface (UI) 1 Introduction Due to the widespread popularity of mobile devices, demands of end users to be provided with personalized and customized services have been tremendously raised these days. For achieving such a personalization of services, a system should fulfill dynamic requirements varying in different contexts at runtime.
Timed data contain information about time concerning the point at which actions happen or how long actions would take through. 1, it is just an example! The same in the rest of paper). DataSRT contains a domain representing the duration of one action. } Where we take stop as an instant action, meaning the ﬁnishing of the action stop, the same as run . We can proof that such timed language L is a timed regular expression so we generate a timed automata shown as Fig. 5, we translate the ‘duration’ to a clock ‘x’ in timed automata.
Table 4 contains the requirements specification of this step. Detailed types of sensors or rules for adaptation are not specified in this step. That is because those parts have high possibility to change. Detailed rules that have high chances of change are specified in the next step, the Final Requirements for AUI. In this layer, related quality attributes are revisited and modified. The specification of Final Requirements for AUI is represented in Table 4. These contain adaptation rules and situation recognition rules which can be modified often due to the demands of stakeholders.