Intelligent Software Service Configuration Technology Based on Association Mining

Abstract Association relationship and types between software service configuration parameters determine that the items must meet corresponding rules constraints in parameter value setting order. However, distribution of services architecture based on loose coupling heterogeneous components make association more concealed. The correlation are crucial to ensure system configuration. When deploying, migrating, updating systems, violating will lead errors, resulting failures. To minimize loss caused by can be mined avoid potential incorrect settings. This paper proposes an intelligent technology mining analyzing items. sample data file is extracted from open source code base, parsed obtain item name value. Then mine rule each pair name, value, type. According constraints, error detection, cascade update recommendation performed. Finally, proposed method tested evaluated six typical software, experimental results prove accuracy effectiveness this paper.