analyze-codebase-workflow

Analyze Codebase Workflow

Survey an arbitrary repository to auto-detect data flows, file I/O, and script dependencies, then produce a structured annotation plan for manual refinement.

When to Use

• Onboarding onto an unfamiliar codebase and need to understand data flow
• Starting putior integration in a project that has no PUT annotations yet
• Auditing an existing project's data pipeline before documentation
• Preparing an annotation plan before running annotate-source-files

Inputs

• Required: Path to the repository or source directory to analyze
• Optional: Specific subdirectories to focus on (default: entire repo)
• Optional: Languages to include or exclude (default: all detected)
• Optional: Detection scope: inputs only, outputs only, or both (default: both + dependencies)

Procedure

Step 1: Survey Repository Structure

Identify source files and their languages to understand what putior can analyze.

library(putior)

# List all supported languages and their extensions
list_supported_languages()
list_supported_languages(detection_only = TRUE)  # Only languages with auto-detection

# Get supported extensions
exts <- get_supported_extensions()

Use file listing to understand repo composition:

# Count files by extension in the target directory
find /path/to/repo -type f | sed 's/.*\.//' | sort | uniq -c | sort -rn | head -20

Got: A list of file extensions present in the repo, with counts. Map these against get_supported_extensions() to know coverage.

If fail: If the repo has no files matching supported extensions, putior cannot auto-detect workflows. Consider whether the language is supported but files use non-standard extensions.

Step 2: Check Language Detection Coverage

For each detected language, verify auto-detection pattern availability.

# Check which languages have auto-detection patterns (18 languages, 902 patterns)
detection_langs <- list_supported_languages(detection_only = TRUE)
cat("Languages with auto-detection:\n")
print(detection_langs)

# Get pattern counts for specific languages found in the repo
for (lang in c("r", "python", "javascript", "sql", "dockerfile", "makefile")) {
  patterns <- get_detection_patterns(lang)
  cat(sprintf("%s: %d input, %d output, %d dependency patterns\n",
    lang,
    length(patterns$input),
    length(patterns$output),
    length(patterns$dependency)
  ))
}