2011
DOI: 10.1007/978-3-642-21530-8_21
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End-User Requirements for Wisdom-Aware EUD

Abstract: Abstract. This paper presents requirements elicitation study for a EUD tool for composing service-based applications. WIRE aims at enabling EUD by harvesting and recommending community composition knowledge (the wisdom), thus facilitating knowledge transfer from developers to end-users. The idea was evaluated with 10 contextual interviews to accountants, eliciting a rich set of information, which can lead to requirements for Wisdom-Aware EUD.

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Cited by 14 publications
(12 citation statements)
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“…Asking the users to define a dataflow or control-flow logic, even assuming they would be able to understand these technical concepts, is not realistic [Angeli et al 2011]. Some studies about users' expectations and the usability of mashup composition environments [Namoun et al 2010a] highlighted fundamental issues concerning the conceptual understanding of service composition.…”
Section: Ui-centric Composition Of Mashupsmentioning
confidence: 99%
“…Asking the users to define a dataflow or control-flow logic, even assuming they would be able to understand these technical concepts, is not realistic [Angeli et al 2011]. Some studies about users' expectations and the usability of mashup composition environments [Namoun et al 2010a] highlighted fundamental issues concerning the conceptual understanding of service composition.…”
Section: Ui-centric Composition Of Mashupsmentioning
confidence: 99%
“…Furthermore, the live environment enables widgets to communicate with each other, providing added value to the otherwise static set of widgets [7]. This is fundamentally different from current practice, in which composition is typically based on explicit composition models [3]. Instead of manipulating abstract modeling constructs (which are relatively intuitive to experts, but may not have any meaning to end users) representing software artifacts, the live environment allows end users to directly manipulate the software artifacts (the widgets).…”
Section: The Live Environmentmentioning
confidence: 97%
“…Understanding this logic is neither trivial nor intuitive. Motivated by a user study on how end users imagine assistance during mashup development [3], we assist the modeler in each step of his development task by means of interactive, contextual recommendations of composition knowledge. The knowledge is re-usable composition patterns, i.e., frequently occurred composition fragments of previous successful mashup models.…”
Section: Problem and Motivationmentioning
confidence: 99%