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

## Quotient trace
In the description of the [adjoint message](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/adjoint-anchor-causal-chains-history-messages) analysis pattern, we mentioned compressing message sequences having the same message attribute into one message. Considering the trace as a “topological” space and message attribute as an “equivalence” relation, we now introduce the **quotient trace** analysis pattern, so named after the quotient space in topology. By endowing message sequences with the same attribute with some “metric” such as cardinality of [message set](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/flow-interleave-invariant-pattern-set), we can also visually distinguish resulting quotient messages if they have the same attribute but come from different sequences at different times. All this is illustrated in the following diagram:

# Quotient trace
In the description of the [adjoint message](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/adjoint-anchor-causal-chains-history-messages) analysis pattern, we mentioned compressing message sequences having the same message attribute into one message. Considering the trace as a “topological” space and message attribute as an “equivalence” relation, we now introduce the **quotient trace** analysis pattern, so named after the quotient space in topology. By endowing message sequences with the same attribute with some “metric” such as cardinality of [message set](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/flow-interleave-invariant-pattern-set), we can also visually distinguish resulting quotient messages if they have the same attribute but come from different sequences at different times. All this is illustrated in the following diagram:

This lesson introduces the following analysis patterns: quotient trace, singleton trace, sorted trace, and statement density and current.

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

Quotient, Singleton, Sorted, Density, Current

Quotient trace