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An Approach to Locating Delayed Activities in Software Processes

An Approach to Locating Delayed Activities in Software Processes
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摘要 Activity is now playing a vital role in software processes. To ensure the high-level efficiency of software processes, a key point is to locate those activities that own bigger resource occupation probabilities with respect to average execution time, called delayed activities, and then improve them. To this end, we firstly propose an approach to locating delayed activities in software processes. Furthermore, we present a case study, which exhibits the high-level efficiency of the approach, to concretely illustrate this new solution. Some beneficial analysis and reasonable modification are developed in the end. Activity is now playing a vital role in software processes. To ensure the high-level efficiency of software processes, a key point is to locate those activities that own bigger resource occupation probabilities with respect to average execution time, called delayed activities, and then improve them. To this end, we firstly propose an approach to locating delayed activities in software processes. Furthermore, we present a case study, which exhibits the high-level efficiency of the approach, to concretely illustrate this new solution. Some beneficial analysis and reasonable modification are developed in the end.
出处 《International Journal of Automation and computing》 EI CSCD 2018年第1期115-124,共10页 国际自动化与计算杂志(英文版)
基金 supported by National Natural Science Foundation of China(No.61462091) High-tech Industrial Development Program of Yunnan Province(No.1956,in 2012) New Academic Researcher Award for Doctoral Candidates of Yunnan Province of China(No.ynu201414) Natural Science Youth Foundation of Yunnan Province of China(No.2014FD006) the Postgraduates Science Foundation of Yunnan University(No.ynuy201424)
关键词 Locating of the delayed activities software process stochastic Petri-nets Markov random fields metrics. Locating of the delayed activities, software process, stochastic Petri-nets, Markov random fields, metrics.
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