Bridging the application and DBMS divide using static analysis and dynamic profiling

Relational database management systems (RDBMSs) today serve as the backend for many real-world data intensive applications. Database developers use data access APIs such as ADO.NET to execute SQL queries and access data. While modern program analysis and code profilers are extensively used during the software development life cycle, there is a significant gap in these technologies for database applications because these tools have little or no understanding of data access APIs or the DBMS. We have developed tools that: (a) Enhance traditional static analysis of programs by leveraging understanding of database APIs to help developers identify security, correctness and performance problems in the application. This enables such problems to be detected early in the application lifecycle. (b) Extend the existing DBMS and application profiling infrastructure to enable correlation of application events with DBMS events. This allows profiling across application, data access and DBMS layers. We demonstrate how our tools enable a rich class of analysis, tuning and profiling tasks that are otherwise not possible today.