CSMiner: An Automated Tool for Analyzing Changes in Configuration Settings across Multiple Versions of Large Scale Cloud Software

摘要

As software evolves, the number of configuration settings and their usage scenario often change as well, causing system misconfiguration and performance degradation. However, no tool exists today that can aid system administrators/developers answering questions such as "What are the new configuration settings in this new version?", or "Where and How is setting X used in the new version?". As manually investigating answers to these questions is almost impossible due to the number of settings and size of the software, this paper investigates the design of an automated tool (CSMiner) leveraging static program analysis techniques that helps users to understand how and where a particular setting is used in a program and how settings have evolved across different versions of a software system. CSMiner was applied on four different open source software packages, namely, Apache Cassandra, ElasticSearch, Apache Hadoop, and Apache HBase, and CSMiner identified 109 (out of 109), 109 (out of 113), 811 (out of 847), and 160 (out of 167) settings for these software packages respectively. In each case, CSMiner successfully identified the changes in configuration settings across multiple versions with high accuracy.