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A Hierarchical Categorization Approach for Configuration Management Modules
Configuration management tools, CMTs for short, are a set of indispensable software for DevOps (Development and Operations). CMTs automate system deployment and configuration through CMT modules, which are reusable, shareable units of configuration code. Therefore, thousands of CMT modules have been...
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Main Authors: | , , , , , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
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Summary: | Configuration management tools, CMTs for short, are a set of indispensable software for DevOps (Development and Operations). CMTs automate system deployment and configuration through CMT modules, which are reusable, shareable units of configuration code. Therefore, thousands of CMT modules have been developed for various systems, and are still growing fast. Although CMT repositories usually provide keyword-and tag-based search, a large number of search results could prevent users from finding desired CMT modules. CMT modules could be managed in a hierarchical categorization, which can limit the search scope in specified categories, and thus help to improve search performance. Unfortunately, there is no hierarchical categorization in all CMT repositories. In this paper, we propose a hierarchical categorization approach for CMT modules. Our approach first extracts frequently-used module tags as categories, and constructs the category hierarchy by mining the hierarchical relations among tags. We leverage online module profiles (names, descriptions and tags) as source information to do categorization. It trains a set of classifiers by taking TF-IDF (term frequency-inverse document frequency) of module profiles as features. Finally, our evaluation on more than 11,000 CMT modules shows that our approach could obtain 90 fine-grained and multi-layered categories, and does categorization for CMT modules with high precision (0.81), recall (0.88) and F-Measure (0.85). |
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ISSN: | 0730-3157 |
DOI: | 10.1109/COMPSAC.2017.17 |