Accession Number:

AD1084074

Title:

Causal Search in Observational Data Workshop

Descriptive Note:

Conference Paper

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA PITTSBURGH United States

Personal Author(s):

• Konrad,Mike
• Stoddard,Bob

Report Date:

2018-09-10

Pagination or Media Count:

49.0

Abstract:

Purpose of Workshop - The SEI is leading a three-year research project that seeks to Apply modern advances in causal learning search and estimation Go beyond traditional correlation and regression analyses and accurately identify the causal relations among software process factors and product outcomes. With this workshop, we intend to Enlighten the practical measurement community Encourage joint collaboration in the early adoption of causal learning to improve the quality of systems engineering and software engineering research.

Descriptors:

• software development
• costs
• models
• algorithms
• correlation
• GAUSSIAN DISTRIBUTIONS
• systems engineering
• statistics
• software engineering
• machine learning
• deep learning

Subject Categories:

• Computer Programming and Software

Distribution Statement:

APPROVED FOR PUBLIC RELEASE