This document summarizes research on analyzing Windows event logs to identify the root causes of defects in software. It discusses using machine learning algorithms and pattern recognition techniques on event log data to detect defect root causes. Specifically, it proposes developing an efficient algorithm based on pattern recognition to accurately detect defect root causes. The algorithm would analyze past event logs and defect resolution methods to improve prediction capability and accuracy over traditional approaches. It also reviews literature on using clustering, classification, and other machine learning methods on event logs to identify patterns and anomalies.