Gain insights into diagnostic techniques and anomaly detection with over 200 trace and log analysis patterns, applicable across various software environments, operating systems, and platforms.

General trace and log analysis patterns allow the application of uniform diagnostics and anomaly detection across diverse software environments. It includes troubleshooting, debugging, describing, and explaining problems and incidents on various operating systems and platforms. It is also helpful in recording network traces, malware, general data, narratives, and text and image analysis (space-like narratology). This course, organized as a pattern language dictionary and cross-referenced with classification, explains and teaches more than 200 traces and log analysis patterns.

A Guide to Learning Software Trace and Log Analysis Patterns

## Abnormal value
While preparing a presentation on malware narratives, we found one essential pattern missing from the current log analysis pattern catalog. Most of the time, we see some abnormal or unexpected value in a software trace or log, such as a network address outside the expected range, which triggers a further investigation. The message structure may have the same [message invariant](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/flow-interleave-invariant-pattern-set), but the variable part may contain such values as depicted graphically below:

# Abnormal value
While preparing a presentation on malware narratives, we found one essential pattern missing from the current log analysis pattern catalog. Most of the time, we see some abnormal or unexpected value in a software trace or log, such as a network address outside the expected range, which triggers a further investigation. The message structure may have the same [message invariant](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/flow-interleave-invariant-pattern-set), but the variable part may contain such values as depicted graphically below:

This lesson introduces the following analysis patterns: abnormal value, error message, error distribution, error powerset, and error thread.

Getting Started

Activity

Block and Data

Error and Large Scale

Message 1

Message 2

Trace as a Whole

Trace Set

Vocabulary, Memory, Code and Text

Conclusion

Index

Value, Message, Distribution, Powerset, Thread

Abnormal value