Abstract

SADT (Structured Analysis and Design Technique) methodology and its component IDEF0 is widely used for modeling business processes, software systems, as well as technology and production processes. There is a wide range of CASE-tools to implement SADT methodology. SADT-model construction starts with the presentation of a system as a single unit and arcs representing system interfaces with the environment. It is a so called contextual diagram. Then, this block is decomposed into several blocksjoined by arcs interface. These blocks are the original function subfunctions. Each of the sub-functions if necessary can be decomposed further in a similar manner to achieve the desired granularity. The paper offers a new approach to estimating the complexity of SADT models perception based on functioning features of short-term human memory and transferring data process from short-term memory into long-term. The article considers a model perception factor and a formula to calculate it which allows comparing and optimizing SADT models for a given parameter. The paper contains a perception factor analysis for a homogeneous SADT model (a model with the same number of blocks in all the diagrams). It confirms the known empirical principle: the number of diagram blocks should be in the range 3-6. An analysis of heterogeneous 2-level SADT model has shown that to reduce a perception factor, it is necessary to choose a decomposition strategy so that the number of blocks on the charts decreased when a decomposition level increases. The authors propose to use adaptable fuzzy systems for increasing the accuracy of estimating SADT models perception difficulty. Thus, a theoretical estimate of perception factor should be used as a priori information and experimental data as a training set.

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