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http://dx.doi.org/10.15207/JKCS.2017.8.11.077

An Predictive Analytics based on Goal-Scenario for Self-adaptive System  

Baek, Su-Jin (Department of Information Communication, Yong-In Songdam College)
Publication Information
Journal of the Korea Convergence Society / v.8, no.11, 2017 , pp. 77-83 More about this Journal
Abstract
For efficient predictive analysis, self-healing research is needed that enables the system to recover autonomously by self-cognition and diagnosing system problems. However, software development does not provide formal contextual information analysis and appropriate presentation structure according to external situation. In this paper, we propose a prediction analysis method based on the change contents by applying the extraction rule to the functions that can act, data, and transaction based on the new Goal-scenario. We also evaluated how well the predictive analysis met through the performance indicators for achieving the requirements goal. Compared with the existing methods, the proposed method has a maximum 32.8% higher matching result through performance measurement, resulting in a 28.9% error rate and a 45.8% reduction in the change code. This shows that it can be processed into a serviceable form through rules, and it shows that performance can be expanded through predictive analysis of changes.
Keywords
Predictive Analytics; Self-Adaptive Software; Goal-Scenario Analysis; Self-Healing; Dynamic Reconfiguration;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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