deep-analysis

To identify what a function does during reverse engineering in Ghidra, use a depth-first investigation loop that gathers decompilation context, makes targeted rename and retype improvements, and verifies findings with address-level evidence.

The best way to detect crypto or C2 indicators in a binary is to perform focused malware analysis that gathers cross-reference context, analyzes behavior, and documents claims with address and snippet evidence.

To fix confusing decompilation types for better readability, apply iterative type correction by reading context, making small database improvements like retyping and structuring, and verifying clarity through re-reading the output.

Yes, you can track reverse engineering evidence and TODOs directly in Ghidra by using bookmarks for findings and follow-up threads, ensuring all behavioral claims are backed by address-level snippets.

Yes, this focused binary analysis approach works for single-function or single-topic tasks, applying an iterative loop to improve the Ghidra database while answering specific behavior questions.

You should use an evidence-based approach for decompilation analysis because it prevents getting stuck on unclear questions by forcing depth-first investigation that continually verifies improvements increased clarity.