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:

Note that we also have the significant event pattern, which is more general and also covers messages without a variable part and suspicious log entries.

# Error message
While working on accelerated windows software trace analysis training, we discovered some missing patterns needed for completeness despite their triviality. One of them is called an **error message**. In this pattern, an error is reported either explicitly (“operation failed”) or implicitly as an operation status result such as `0xC00000XX`. Sometimes, a trace message designer specifies that the number value is supplied for information only and should be ignored. Some error messages may contain information that is not relevant to the current software incident, the so-called [false positive errors](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/exception-stack-false-positive-hidden-periodic). Some tracing architectures and tools include a message information category for errors, such as Citrix CDF, where we can filter by error category to get [adjoint thread](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/region-theatre-adjoint-thread-blackout-braid-group). The association of a trace statement with an error category is in the discretion of an engineer writing code. Information category messages may also contain implicit errors such as the last error and return status reports.

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

Error message