Mining and Understanding Software Enclaves (MUSE)
Abstract
The Mining and Understanding Software Enclaves (MUSE) program developed program analyses and frameworks for improving the resilience and reliability of complex software applications at scale. MUSE applied machine learning algorithms to large software corpora to repair defects and vulnerabilities in existing software, and to create new software programs that conform to desired behaviors and specifications. Specific technical challenges included generation and analysis of persistent semantic artifacts, identification and repair of defects, and inference and synthesis of specifications. MUSE research improves the security of intelligence-related applications and enhances computational capabilities in areas such as automated code maintenance and revision management, low-level systems implementation, graph processing, entity extraction, link analysis, high-dimensional data analysis, data/event correlation, and visualization.
Document Details
- Document Type
- Accomplishment
- Publication Date
- Oct 01, 2020
- Source ID
- 767f0f18355a819dad0f4f132952969c