There are hundreds of debugger commands, such as commands from WinDbg, GDB, LLDB, and other debuggers. A typical diagnostic analysis pattern, for example, a memory dump analysis pattern, may involve many commands (Debugged! Magazine, March 2009). In November 2008 we proposed abstract debugging commands for common diagnostic, forensic, and debugging tasks. After the introduction of pattern-oriented diagnostic thinking we propose another analysis pattern abstraction level of Elementary Analysis Patterns that groups either real or abstract debugging commands and allows chaining analysis activities to uniformly describe diagnostic analysis patterns:
Some Elementary Analysis Patterns may correspond to a single WinDbg command, and some may group several debugger commands. The exact names will be incrementally added and incrementally refined over the course of catalog building process.
Some Elementary Analysis Patterns may be reused across different analysis pattern catalogs, for example, Setting Symbolic Information is also applicable to trace and log analysis, for example, Windows ETW traces (see No Trace Metafile analysis pattern) and Fiber Bundle analysis pattern where symbols are needed for associated stack traces or Adjoint Space where symbols are needed for associated memory snapshots.
Such analysis patterns are different from Elementary Software Diagnostics Patterns since the latter are about observed behavioral signs, but the former are about the analysis process.
Let’s look at one example. We observe increasing memory Counter Values for one Windows server process and look at its memory snapshots. The process doesn’t use .NET so we use process heap Memory Leak analysis pattern which can be split into the following sequentially applied Elementary Analysis Patterns that group appropriate WinDbg commands:
In the case of missing user mode stack trace database or before asking for it, we can also use the following Elementary Analysis Patterns for symbolic hints such as Module Hint analysis pattern, ASCII, and UNICODE data:
All these provide a better description of analysis patterns. The same approach can be applied to trace and log analysis including network trace analysis, memory forensics, reversing and malware analysis.