Pros of pfff

• More comprehensive static analysis toolset with support for multiple languages
• Includes advanced features like type inference and dataflow analysis
• Offers visualization tools for code structure and dependencies

Cons of pfff

• Less actively maintained (last commit in 2019)
• Steeper learning curve due to its complexity
• Limited documentation and community support

Code Comparison

pfff (OCaml):

let parse_program file =
  let ast = Parse_php.parse_program file in
  let ast = Ast_php_simple_build.program ast in
  ast

Comby (Pattern matching):

:[prefix]function :[name](...) {
  :[body]
}

Key Differences

• pfff is a more comprehensive static analysis tool, while Comby focuses on pattern matching and rewriting
• pfff is written in OCaml, whereas Comby uses its own pattern matching language
• Comby is more actively maintained and has better documentation
• pfff offers deeper analysis capabilities, but Comby is easier to use for quick code transformations

Use Cases

• Use pfff for in-depth static analysis and visualization of large codebases
• Choose Comby for quick, language-agnostic code refactoring and pattern matching tasks

Pros of Semgrep

• More extensive language support, covering 30+ languages
• Advanced features like taint analysis and dataflow tracking
• Large rule database with community-contributed rules

Cons of Semgrep

• Steeper learning curve for creating custom rules
• Slower performance on large codebases compared to Comby
• More complex setup and configuration process

Code Comparison

Semgrep rule example:

rules:
  - id: detect-eval
    pattern: eval($X)
    message: "Dangerous use of eval()"
    languages: [python]
    severity: WARNING

Comby pattern example:

eval(:[arg])

Both tools aim to improve code quality and security through pattern matching, but they differ in approach and complexity. Semgrep offers more advanced features and broader language support, making it suitable for complex analysis tasks. Comby, on the other hand, provides a simpler, faster solution for basic pattern matching across multiple languages.

Semgrep's rule-based approach allows for more nuanced and context-aware checks, while Comby's lightweight design enables quick and easy pattern matching without the need for language-specific parsing.

Choose Semgrep for comprehensive, language-aware analysis in large projects, and Comby for rapid, language-agnostic pattern matching and transformation tasks in smaller codebases or specific use cases.

Pros of Tree-sitter

• More robust parsing with full syntax trees
• Supports incremental parsing for better performance
• Wider language support out-of-the-box

Cons of Tree-sitter

• Steeper learning curve for creating and modifying grammars
• Requires more setup and integration effort
• Less flexible for quick, pattern-based searches

Code Comparison

Tree-sitter grammar example:

module {
  rules {
    source_file: $ => repeat($._definition),

    _definition: $ => choice(
      $.function_definition,
      $.variable_declaration
    ),

    function_definition: $ => seq(
      'func',
      $.identifier,
      $.parameter_list,
      $.block
    )
  }
}

Comby pattern example:

func :[name](...) {
  :[body]
}

Tree-sitter provides a more comprehensive parsing solution, generating full syntax trees for supported languages. It offers better performance for large codebases and incremental parsing capabilities. However, it requires more setup and has a steeper learning curve for creating custom grammars.

Comby, on the other hand, focuses on simpler pattern-based matching and rewriting. It's more flexible for quick searches and transformations but may not handle complex language constructs as accurately as Tree-sitter.