SBIR Phase I: Software Analysis Tools for Field Specialization of Database Management Systems

Dataware Ventures Llc, Tucson AZ

Investigators

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a set of software tools that can demonstrate the feasibility of a patent-pending technology for dramatically boosting the performance of a wide range of software systems, on very large and complex commercial-scale database management systems (DBMS). The accelerating growth in data-driven approaches to business decision-making, together with the rapidly growing volume of data being used, makes the speed of data processing an important consideration in today's business world; interviews with industry CIOs indicate that DBMS performance is a significant pain point for businesses. The commercialization of the technology developed in this project will greatly improve data processing capacity and thereby permit faster and better business decision-making. Given the central role played by DBMSs in enterprise IT systems, this can be expected to have a significant positive impact on businesses large and small. This Small Business Innovation Research (SBIR) Phase I project will demonstrate the feasibility of applying field specialization technology to large commercial database management systems (DBMSs), with the objective of significantly improving the performance of these systems, by developing a highly precise and scalable software analysis tool to identify field specialization opportunities in commercial DBMS software. The primary challenges to be addressed are those of scale and complexity (commercial code bases run to many tens of millions of lines of source code in size, and contain significant amounts of legacy code as well as more complex data structures and source language constructs). The project will address these challenges by developing an automated software tool that is both (a) highly precise in its analysis of DBMS software properties, and (b) highly scalable in its ability to process large software systems.