Accession Number:



Do Software Architecture Patterns Reduce Security Vulnerabilities? xB;Insight from Causal Learning

Descriptive Note:

[Technical Report, Briefing Charts]

Corporate Author:

Carnegie Mellon University Software Engineering Institute

Report Date:


Pagination or Media Count:



Motivation for Causal Learning Controlling costs requires knowing which independent factors actually cause item outcomes, so that we may change items in a predictable manner. Just as correlation may be fooled by spurious association, so can regression. We must move beyond correlation to causation, if we want to make use of cause and effect relationships. We can now evaluate causation without expensive and difficult experiments. Establishing causation with observational data remains a vital need and a key technical challenge, but is becoming more feasible and practical.


Subject Categories:

  • Computer Systems Management and Standards

Distribution Statement:

[A, Approved For Public Release]