Association Mining Based Consistent Service Configuration

Componentized service-oriented software systems always consist of loosely coupled hetero-geneous service components, each of which contains a large number of configuration items configured with high flexibility. Complex dependencies exist between service components, resulting in their interrelated configuration items, so the operations of deploying, updating and migrating components are prone to errors. For configuration items related with each other, changing one configuration item requires to modify other related configuration items. Otherwise, violating constraints perhaps happens, which should cause system failure. Therefore, analyzing associations between configuration items is one key to ensure the reliability of a system. This paper proposes a service configuration approach based on association mining. Our approach crawls configuration files from Internet, narrows the analysis scope to frequently changed configuration items, generates association coefficients for item pairs according to the similarity of items’ name, value and type, determines the set of candidate item pairs with rules, and then outputs a list of ordered configuration item pairs for query. We have deployed two typical open-source software systems to validate our approach for mining configuration associations between configuration items with case studies. Experimental results show that our approach can accurately detect most associations between configuration items.