FQL: An Extensible Feature Query Language and Toolkit on Searching Software Characteristics for HPC Applications
This work addresses the need for automated feature extraction in HPC applications, though it appears incremental as it builds on existing static analysis concepts.
The authors tackled the problem of extracting software features from large-scale scientific computing code by designing FQL, a feature query language, and an accompanying toolkit for static code analysis, demonstrating its application on several HPC codes with extensibility to general software queries.
The amount of large-scale scientific computing software is dramatically increasing. In this work, we designed a new language, named feature query language (FQL), to collect and extract software features from a quick static code analysis. We designed and implemented an FQL toolkit to automatically detect and present the software features using an extensible query repository. Several large-scale, high performance computing (HPC) scientific codes have been used in the paper to demonstrate the HPC-related feature extraction and information collection. Although we emphasized the HPC features in the study, the toolkit can be easily extended to answer general software feature questions, such as coding pattern and hardware dependency.