APICAD: Augmenting API Misuse Detection through Specifications from Code and Documents

Using API should follow its specifications. Otherwise, it can bring security impacts while the functionality is damaged. To detect API misuse, we need to know what its specifications are. In addition to being provided manually, current tools usually mine the majority usage in the existing codebase as specifications, or capture specifications from its relevant texts in human language. However, the former depends on the quality of the codebase itself, while the latter is limited to the irregularity of the text. In this work, we observe that the information carried by code and documents can complement each other. To mitigate the demand for a high-quality codebase and reduce the pressure to capture valid information from texts, we present APICAD to detect API misuse bugs of C/C++ by combining the specifications mined from code and documents. On the one hand, we effectively build the contexts for API invocations and mine specifications from them through a frequency-based method. On the other hand, we acquire the specifications from documents by using lightweight keyword-based and NLP-assisted techniques. Finally, the combined specifications are generated for bug detection. Experiments show that APICAD can handle diverse API usage semantics to deal with different types of API misuse bugs. With the help of APICAD, we report 153 new bugs in Curl, Httpd, OpenSSL and Linux kernel, 145 of which have been confirmed and 126 have applied our patches.