Title :
A software engineering approach to assessing complexity in network supervision tasks
Author :
Murray, John ; Liu, Yili
Author_Institution :
Dept. of Ind. & Oper. Eng., Michigan Univ., Ann Arbor, MI, USA
Abstract :
Studies of work environments associated with supervisory monitoring of a large-scale networked system suggest that a person´s working efficiency is influenced by the `complexity´ of the networked system itself. A quantitative understanding of network complexity therefore holds considerable potential for research and industrial application. However, previous attempts to apply numeric metrics to assess this area have encountered various shortcomings. A new measure of complexity is investigated, which is based upon a popular software complexity metric. A series of experiments designed to evaluate and test the metric is described
Keywords :
human factors; large-scale systems; software engineering; user interfaces; human factors; large-scale networked system; network complexity assessment; network supervision tasks; software complexity metric; software engineering; user interface; Application software; Data communication; Humans; Intelligent networks; Large-scale systems; Monitoring; Software engineering; Software measurement; Supervisory control; Testing;
Conference_Titel :
Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2129-4
DOI :
10.1109/ICSMC.1994.399806
