SEI Year in Review FY 2011
May 2012 • Annual Report
The SEI Year in Review describes the accomplishments of the SEI during fiscal year 2011 (October 1, 2010, through September 30, 2011).
Software Engineering Institute
2011 was a record year for the SEI—a year of significant growth in our impact, in our influence, and in our initiative. This report in many ways reflects the hard work and innovative thought of the SEI's staff. The following are among the many accomplishments highlighted in this year's edition of the SEI Year in Review:
- In 2011, the SEI focused its investigation of Agile methods to develop guidance for DoD program managers, and plans to develop a companion contingency model in 2012. (See page 8.)
- SEI researchers collaborated with the Office of the Under Secretary of Defense (USD) for Acquisition, Technology, and Logistics (AT&L), Acquisition Visibility (AV). The team set out to evaluate statistical methods for improving on existing, manual methods of anomaly detection. (See page 25.)
- The Accelerated Improvement Method (AIM) streamlines CMMI adoption through a tailored version of the Team Software Process and Six Sigma measurement strategies. Helping organizations like Urban Science implement AIM is one way the SEI is increasing our focus on performance results.(See page 12.)
- The past year saw continued research by the SEI into the challenge of monitoring large networks for malicious activity. The SEI's approaches rely on techniques to summarize communications between hosts on the network. The Network Situational Awareness team in the SEI's CERT® Program has developed approaches to automate the analysis of the huge volumes of data generated in this process. (See page 14.)
The report also presents information about the SEI, its staff members, and its organization, including publications, demographics, and technology-transition activities. To obtain a printed copy of the SEI Annual Report, contact SEI Customer Relations. Even using summary techniques, monitoring large networks operated by the U.S. government and commercial enterprises generates huge volumes of data that security analysts cannot possibly analyze unassisted.