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

# Basic facts
A typical trace is a detailed narrative accompanied by a problem description that lists essential facts. For this reason, the first task of any trace analysis is to check the presence of **basic facts** in the trace. If they are not visible or if they do not correspond, the trace was probably not recorded when the problem occurred or was taken from a different computer or under other conditions.

Here is an example. The user `test01` cannot connect to a published application in a terminal services environment. We look at the trace and find this statement:

We can be sure that this trace was taken for the user `test01`, especially when we expect this or similar trace statements. If we do not see this trace statement, we may suppose that the trace was taken at the wrong time, such as when the problem had already occurred.

We suggest the following taxonomy of basic facts:

* **Functional facts:** The user expected a dialog to enter data.
* **Non-functional facts:** CPU consumption was at 100%.
* **Identification facts:** These include the application name, PID, username.

# Hidden facts
The previous patterns, such as basic facts and vocabulary index, address the mapping of a problem description to software execution artifacts such as traces and logs. An indirect facts analysis pattern addresses the problem of incomplete problem descriptions. However, we need another pattern for completeness that addresses the mapping from a log to troubleshooting and debugging recommendations.

We call facts that are uncovered by trace and log analysis **hidden facts**. Of course, there can be many such hidden facts, and usually they are discovered after narrowing down analysis to particular [threads of activity](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/ruptured-strand-thread-time-delta-timeout-weave), [adjoint threads](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/region-theatre-adjoint-thread-blackout-braid-group), [message context](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/annotations-change-context-cover-directory), [message set](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/flow-interleave-invariant-pattern-set), or [data flow](https://www.educative.io/courses/guide-learning-software-trace-log-analysis-patterns/backtrace-counter-association-flow-interval) patterns. The need for this pattern arose during the pattern-oriented analysis of the trace case study from Malcolm McCaffery. It is illustrated in the following diagram:

This lesson introduces the following analysis patterns: basic facts, hidden facts, indirect facts, trace constants, and vocabulary index.

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

Basic, Hidden, Indirect Facts, Constants, Vocabulary

Basic facts

Hidden facts