Structuring and composition mechanisms to address scalability issues in task models

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Abstract

Along tasks analysis and modeling history it has been demonstrated by experience that task modeling activities become cumbersome when performed on large, real-life systems. However, one of the main goals of task models is to provide designers with a structured and complete description of the users tasks especially when these user tasks are numerous and/or complex. Several authors proposed to handle that problem by providing tools aiming at supporting both construction and understanding (usually via simulation) of models. One of the most popular examples is CTTE environment which is dedicated to the engineering of CTT task models. The paper shows how to extend notations for task description with two kinds of mechanisms: composition and refinement/abstraction. Refinement/abstraction mechanisms make it possible to decompose a task model into several models and to interconnect them. Composition mechanisms make it possible to define communication means between task models. The paper proposes a precise definition of these mechanisms, their integration into a notation for describing task models and demonstrates that altogether, these two structuring mechanisms support the effective exploitation of task models for large scale application. The use of the mechanisms is presented on a real-life case study from the space domain describing operators' tasks to monitor a satellite and manage failures. © 2011 IFIP International Federation for Information Processing.

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APA

Martinie, C., Palanque, P., & Winckler, M. (2011). Structuring and composition mechanisms to address scalability issues in task models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6948 LNCS, pp. 589–609). https://doi.org/10.1007/978-3-642-23765-2_40

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