By Patrick Brézillon, Avelino J. Gonzalez
This quantity explores how context has been and will be utilized in computing to version human behaviors, activities and communications in addition to to control info and data. It addresses context administration and exploitation of context for sharing adventure throughout domains.
The e-book serves as a user-centric consultant for readers wishing to advance context-based purposes, in addition to an highbrow reference at the suggestion of context. It presents a large but deep remedy of context in computing and similar components that count seriously on computing. The insurance is large due to its cross-disciplinary nature yet treats themes at a adequate intensity to allow a reader to enforce context in his/her computational endeavors.
The quantity addresses how context may be built-in in software program and platforms and the way it may be utilized in a computing setting. moreover, using context to symbolize the human measurement, separately in addition to jointly is defined. Contributions additionally contain descriptions of ways context has been represented in formal in addition to non-formal, dependent methods. The final part describes numerous human habit illustration paradigms in accordance with the idea that of context as its imperative representational element.
The intensity and breadth of this content material is sure to supply precious in addition to intellectually enriching info to readers of various backgrounds who've an curiosity in or are intrigued by utilizing context to aid of their illustration of the genuine world.
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Extra resources for Context in Computing: A Cross-Disciplinary Approach for Modeling the Real World
It was considered irrelevant by 64 % of the participants. This result contradicts what was initially expected since the authors believed that recommendations could be more effective if the user already knows the recommended expert; 2 The CSS Design Process: On Supporting Context-Sensitive Systems Development 19 • M1: to model context acquisition, three external and two internal context sources were identified: Lattes Database3 (a curricula database in Brazil); GeoLite City4 (a database that supports the identification of location information according to IP addresses); MSN 5 (an instant messenger application); User Profile (a form filled by users when registering to ICARE); and History Cases (a base with previous recommendation cases); • M2: the interaction interface between ICARE and the identified external context sources, using existent API, were designed.
The proposed method is called Context-Assisted Test Case Reduction (CATCR). In CATCR, the results of previous test cases are used to influence the selection of test cases in the next testing iteration. Using contextual inputs for reducing testing time/effort is the main goal of CATCR. Furthermore, through selecting appropriate cloud sites and automatically evaluating the situation, contextual testing helps the engineers make better timely decisions. To evaluate the proposed context-based method, an experimental assessment is performed using Amazon’s Cloud.
Cloud site weight reflects the assurance level of the model. When the assurance of all models reaches 10 (100 %) and implementation is done, validation stops. Another very important variable is Global Importance (GI). GI is used to define the importance of any test case within the global set of test cases, across all cloud sites. Global Importance = Local VM Importance * CSW. As software is distributed across the cloud (different sites and VMs), the site with the highest importance is used for testing.