SBIR-STTR Award

Efficient static analysis tools for detecting bugs and improving developer productivity
Award last edited on: 3/13/2009

Sponsored Program
SBIR
Awarding Agency
NSF
Total Award Amount
$1,174,000
Award Phase
2
Solicitation Topic Code
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Principal Investigator
Spiros Xanthos

Company Information

Pattern Insight Inc (AKA: CleanMake Inc)

465 Fairchild Drive Suite 209
Mountain View, CA 94043
   (866) 582-2655
   N/A
   www.patterninsight.com
Location: Single
Congr. District: 18
County: Santa Clara

Phase I

Contract Number: ----------
Start Date: ----    Completed: ----
Phase I year
2007
Phase I Amount
$150,000
This Small Business Innovation Research project investigates and explores the feasibility of commercializing bug detection tools to improve the quality and productivity of a variety of software developed by various industry segments. The tools are based on state-of-art data-mining tools under development at the University of Illinois. The proposed project will improve the accuracy, usability and robustness of the tools in order to make them more user-friendly and reliable. The tools, once commercialized, can benefit a large market of IT departments in different business segments (IT, finance, government, entertainment, insurance, etc) to improve their software quality and productivity and reduce the software development cost via automatic bug detection. In contrast to traditional manual efforts that usually takes a programmer 1-2 weeks to detect a bug, the proposed tools can easily identify hundreds of bugs in millions lines of code automatically in 1-2 hours. In addition to detecting software bugs, the proposed tools could also be used to detect copyright infringment and plagiarism from open source or other software

Phase II

Contract Number: ----------
Start Date: ----    Completed: ----
Phase II year
2008
Phase II Amount
$1,024,000
This SBIR Phase II project develops software products to improve software quality and developer productivity. Computers are used everywhere in our lives with most applications requiring high reliability, availability, and security. Despite efforts to improve quality, bugs are still too common and costly. To address these problems the team has conducted research in static-analysis and bug detection - taking a pattern-based approach - applying data-mining to software code analysis. The Phase II effort will focus on integration of the tools into the software development lifecycle providing customers an optimal way to benefit from the tools. The team will also develop needed functionality (Branch Quality Management, Patch-Mining) and code search - all new, unique, broader and important usages of technology identified by customers from Phase I. The tools, once commercialized, can benefit a large percentage of IT departments in different business segments (IT, finance, government, entertainment, insurance, etc) to improve their software quality and productivity and reduce the software development cost via automatic bug detection. In contrast to traditional manual effort that usually takes a programmer 1-2 weeks to detect a bug, the proposed tools can easily identify hundreds of bugs in millions lines of code automatically in 1-2 hours. Once a bug is detected (either from these tools, or any other tools, the tools can be used to ensure that the bug-fix is applied throughout the code. In addition to detecting software bugs, the proposed tools can also be used to detect illegal software plagiarism from open source or other software