CRSExtractor: Automated configuration option read sites extraction towards IoT cloud infrastructure

There are a large number of solutions for big data processing in the Internet of Things (IoT) environments, among which the IoT cloud infrastructure is one of the most mature solutions. Typically, modern IoT cloud infrastructures have different kinds of configuration options. The diversity of configurations leads to frequent software configuration errors. Generally, troubleshooting configuration errors relies on finding the mapping relationship between configuration options in the documents (e.g., official manuals) and their read sites in the source code. Most current works still manually extract configuration read sites. Automated methods are not always interchangeable and they incur considerable time overheads and low extraction rates. In this paper, we propose CRSExtractor, an automatic technique for extracting configuration read sites based on intra-procedural analysis. Using our technique, configuration option read sites can be automatically identified and built into maps with configuration options. Evaluations on several core software systems of IoT cloud platforms, such as Hadoop and Cassandra, show that our approach performs well, with an accuracy rate of over 90% and efficiency nearly 20 times faster than previous works.