Software Engineering Institute | Carnegie Mellon University
Software Engineering Institute | Carnegie Mellon University


Our program uses a data-centric approach to research, develop, and transition the best software engineering, management, and measurement practices. As shown in the diagram below, research and development are aided by the application of methods in government and industry organizations. While anyone who works with organizations gains experience, the SEI also uses these engagements to collect validated, fine-grained data. This unique data is a key component of the SEI's research program, and ultimately benefits government and industry organizations as we use it to evaluate the claims of "best practice" by many different development methodologies.

Some recent research efforts include:

 Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE)
Difficulties with estimating the costs of developing new systems have been well documented, and are compounded by the fact that estimates are now prepared much earlier in the acquisition lifecycle, before there is concrete technical information available on the particular program to be developed. The SEI has developed an innovative synthesis of analytical techniques into a cost estimation method that models and quantifies the uncertainties associated with early lifecycle cost estimation.

Agile Research Forum
The SEI hosted an Agile Research Forum to explore how agile approaches confront the challenges of complexity, exacting regulations, and schedule pressures in the large-scale development found in government and many industry environments. A series of webinars and blog posts based on the forum are available.

The Accelerated Improvement Method (AIM)
AIM is an improvement method being piloted by the SEI that includes

  • a process improvement framework
  • self-directed teaming of TSP
  • measurement and analysis techniques, such as goal-driven measurement, performance benchmarking approaches, and Six Sigma measurement, analysis, and improvement techniques

This integrated solution enables superior implementations for performance improvement. Each component in AIM has proven to help organizations reduce costs and improve quality and schedule predictability.