A Quality Model for Mashups

Cappiello, Cinzia; Daniel, Florian; Koschmider, Agnes; Matera, Maristella; Picozzi, Matteo

doi:10.1007/978-3-642-22233-7_10

Cited by 18 publications

(23 citation statements)

References 17 publications

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“…Research on Web Engineering has proposed several quality models addressing Web applications. However, as also proved by a study that we conducted on a large collection of mashups from the programmableWeb.com repository [3], the application of traditional and generic models not always captures the real value of Web mashups. Although the majority of such applications are characterized by a simple one-page structure, specific concerns, related to the component-based development and to the dynamics that characterize the mashup ecosystem, require specific attention.…”

Section: Introductionmentioning

confidence: 94%

“…Mashup applications generally consist of a single page, with a simplistic presentation layer, usually deriving from the combination of the layout of each individual component, and an application logic mainly deriving from the operations exposed by the involved components [3]. The additional integration logic has a limited complexity.…”

Section: Quality Issues In Mashup Developmentmentioning

confidence: 99%

“…In this context, the quality and the role of the constituent components become relevant ingredients for quality assessment [4], [5], [3]; the added value introduced by the integration logic is however also relevant. We thus propose evaluation techniques taking into account these features, and show how they can be integrated into the mashup life cycle to enable a quality-aware mashup development process.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Quality-Aware Mashup Composition: Issues, Techniques and Tools

Cappiello¹,

Matera²,

Picozzi³

et al. 2012

2012 Eighth International Conference on the Quality of Information and Communications Technology

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Abstract-Web mashups are a new generation of applications based on the composition of ready-to-use, heterogeneous components. In different contexts, ranging from the consumer Web to Enterprise systems, the potential of this new technology is to make users evolve from passive receivers of applications to actors actively involved in the creation of their artifacts, thus accommodating the inherent variability of the users' needs. Current advances in mashup technologies are good candidates to satisfy this requirement. However, some issues are still largely unexplored. In particular, quality issues specific for this class of applications, and the way they can guide the users in the identification of adequate components and composition patterns, are neglected. This paper discusses quality dimensions that can capture the intrinsic quality of mashup components, as well as the components' capacity to maximize the quality and the userperceived value of the overall composition. It also proposes an assisted composition process in which quality becomes the driver for recommending to the users how to complete mashups, based on the integration of quality assessment and recommendation techniques within a tool for mashup development.

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Section: Introductionmentioning

confidence: 94%

Section: Quality Issues In Mashup Developmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Quality-Aware Mashup Composition: Issues, Techniques and Tools

Cappiello¹,

Matera²,

Picozzi³

et al. 2012

2012 Eighth International Conference on the Quality of Information and Communications Technology

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“…The proposed taxonomy features a holistic view on the problem of quality control in crowdsourcing and aims to highlight the key aspects and options one has to face when developing quality control mechanisms. The taxonomy is based on our own experience Cappiello et al 2011;Kritikos et al 2013;Batini et al 2009] as well as on an extensive literature review of related areas, discussions with colleagues, experimentation with systems and prototypes, which allowed us to identify common building blocks for the different variations in quality control mechanisms. Accordingly, we propose a taxonomy with three categories that may, in turn, be split into sub-categories: -A quality model for crowdsourcing that captures which quality dimensions and attributes have been identified so far in the literature.…”

Section: Taxonomymentioning

confidence: 99%

Quality Control in Crowdsourcing

et al. 2018

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Crowdsourcing enables one to leverage on the intelligence and wisdom of potentially large groups of individuals toward solving problems. Common problems approached with crowdsourcing are labeling images, translating or transcribing text, providing opinions or ideas, and similar -all tasks that computers are not good at or where they may even fail altogether. The introduction of humans into computations and/or everyday work, however, also poses critical, novel challenges in terms of quality control, as the crowd is typically composed of people with unknown and very diverse abilities, skills, interests, personal objectives and technological resources. This survey studies quality in the context of crowdsourcing along several dimensions, so as to define and characterize it and to understand the current state of the art. Specifically, this survey derives a quality model for crowdsourcing tasks, identifies the methods and techniques that can be used to assess the attributes of the model, and the actions and strategies that help prevent and mitigate quality problems. An analysis of how these features are supported by the state of the art further identifies open issues and informs an outlook on hot future research directions.

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“…Our assumption here is that patterns proven successful in the past (e.g., assessed by experts) or that have been used repeatedly (e.g., verified via minimum support threshold values) are also of good quality. Yet, explicit quality models as, for instance, in Chen et al [2013] and Cappiello et al [2009Cappiello et al [ , 2011 could be used to analytically ascertain quality and to rerank patterns. -Trust in patterns.…”

Section: Performance and Limitationsmentioning

confidence: 99%

Recommendation and Weaving of Reusable Mashup Model Patterns for Assisted Development

Chowdhury

Daniel

Casati

2014

ACM Trans. Internet Technol.

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With this article, we give an answer to one of the open problems of mashup development that users may face when operating a model-driven mashup tool, namely the lack of modeling expertise. Although commonly considered simple applications, mashups can also be complex software artifacts depending on the number and types of Web resources (the components) they integrate. Mashup tools have undoubtedly simplified mashup development, yet the problem is still generally nontrivial and requires intimate knowledge of the components provided by the mashup tool, its underlying mashup paradigm, and of how to apply such to the integration of the components. This knowledge is generally neither intuitive nor standardized across different mashup tools and the consequent lack of modeling expertise affects both skilled programmers and end-user programmers alike.In this article, we show how to effectively assist the users of mashup tools with contextual, interactive recommendations of composition knowledge in the form of reusable mashup model patterns. We design and study three different recommendation algorithms and describe a pattern weaving approach for the one-click reuse of composition knowledge. We report on the implementation of three pattern recommender plugins for different mashup tools and demonstrate via user studies that recommending and weaving contextual mashup model patterns significantly reduces development times in all three cases.

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A Quality Model for Mashups

Cited by 18 publications

References 17 publications

Quality-Aware Mashup Composition: Issues, Techniques and Tools

Quality-Aware Mashup Composition: Issues, Techniques and Tools

Quality Control in Crowdsourcing

Recommendation and Weaving of Reusable Mashup Model Patterns for Assisted Development

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