Web mashups available online today are very often characterized by a poor quality. Several researchers justify this aspect by considering the situational, short-living nature of these applications. We instead believe such a low quality is also due to the lack of suitable quality models. This paper presents a quality model that tries to capture the nature of Web mashups by focusing on their component-based nature and the added value that they are required to introduce with respect to their single constituents. A finite set of indicators and attributes was first determined by reviewing the literature. An analysis of data collected from domain experts revealed a relevance of performance variables at different levels of granularity. An empirical study was then carried out to assess which dimensions are the most relevant with respect to the mashup quality as perceived by users.

Identifying relevant dimensions for the quality of web mashups: An empirical study

CAPPIELLO, CINZIA;MATERA, MARISTELLA
2016

Abstract

Web mashups available online today are very often characterized by a poor quality. Several researchers justify this aspect by considering the situational, short-living nature of these applications. We instead believe such a low quality is also due to the lack of suitable quality models. This paper presents a quality model that tries to capture the nature of Web mashups by focusing on their component-based nature and the added value that they are required to introduce with respect to their single constituents. A finite set of indicators and attributes was first determined by reviewing the literature. An analysis of data collected from domain experts revealed a relevance of performance variables at different levels of granularity. An empirical study was then carried out to assess which dimensions are the most relevant with respect to the mashup quality as perceived by users.
Proceedings of the 18th International Conference on Human-Computer Interaction, HCI International 2016; Toronto; Canada; 17 July 2016 through 22 July 2016
9783319395098
9783319395098
Empirical study; Model validation; Quality evaluation; Relevance identification; Web mashups; Computer Science (all); Theoretical Computer Science
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/998295
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