Skip to main content

Next-generation codebase analysis toolkit.

Project description

ScubaTrace

Next-Generation Codebase Analysis Toolkit.


Install

pip install scubatrace

Features

  • Multi-Language Support (C, C++, Java, Python, JavaScript, Go)
  • No Need To Compile
  • Statement-Based AST Abstraction
  • Code Call Graph
  • Code Control Flow Graph
  • Code Data/Control Dependency Graph
  • References Inference
  • CPG Based Multi-Granularity Slicing
Tool Type Capabilities Requires Compilation (Instruction) Supported Languages Limitations
ScubaTrace Lib CG/CFG/DataFlow/Slicing ✅ No Multiple Languages
Soot CLI/Lib (Java) CG/CFG/DataFlow ❌ Yes Java (Bytecode) Cannot directly analyze the source code
LLVM CLI/Lib (C) CG/CFG/DataFlow ❌ Yes C/C++ (IR) Cannot directly analyze the source code
pycallgraph CLI CG ✅ No Python Does not provide a library, requires parsing the tool output
pycg CLI CG ✅ No Python Precision is low, requires parsing the tool output, no longer maintained
Jelly CLI CG ✅ No JavaScript Incomplete call graph (CG), the generated output requires further processing
Infer OCaml CG/CFG/DataFlow ❌ Yes Multiple Languages 1. High cost of adaptation
CodeQL QL CG/CFG/DataFlow ❌ Required for compiled languages
✅ Not required for interpreted languages
Multiple Languages 1. Compiled languages require compilation
2. Requires learning QL and using it for analysis
3. Lower performance, slow for large-scale projects
Joern CLI/Scala CG/CFG/DataFlow ✅ No Multiple Languages 1. The generated CG and other results cannot be directly used, require further processing
2. Generated CG graphs are prone to errors in resolving output failures
3. Lower performance, slow for large-scale projects

Usage

Project-Level Analysis

Load a project (codebase)

proj = scubatrace.CProject("path/to/your/codebase")

Call Graph

# Get the call graph of the project
callgraph = proj.callgraph
# Export call graph to a dot file
proj.export_callgraph("callgraph.dot")

Code Search

stat = proj.search_function("relative/path/to/your/file.c", start_line=20)

File-Level Analysis

Load a file from a project

file = proj.files["relative/path/to/your/file.c"]

Function-Level Analysis

Load a function from a file

the_first_func = file.functions[0]
func_in_tenth_line = file.function_by_line(10)

Call Relationships

callers = func.callers
callfrom, callto, callsite_line, callsite_column = (
    callers[0].src,
    callers[0].dst,
    callers[0].line,
    callers[0].column,
)
callees = func.callees
callfrom, callto, callsite_line, callsite_column = (
    callees[0].src,
    callees[0].dst,
    callees[0].line,
    callees[0].column,
)

Function Control Flow Graph

# Export the control flow graph to a dot file
func.export_cfg_dot("cfg.dot")

Function Data Dependency Graph

# Export the data dependency graph to a dot file
func.export_cfg_dot("ddg.dot", with_ddg=True)

Function Control Dependency Graph

# Export the control dependency graph to a dot file
func.export_cfg_dot("cdg.dot", with_cdg=True)

Function Code Walk

statements_you_interest = list(
    func.walk_backward(
        filter=lambda x: x.is_jump_statement,
        stop_by=lambda x: x.is_jump_statement,
        depth=-1,
        base="control",
    )
)
statements_you_interest = list(
    func.walk_forward(
        filter=lambda x: x.is_jump_statement,
        stop_by=lambda x: x.is_jump_statement,
        depth=-1,
        base="control",
    )
)

Multi-Granularity Slicing

# Slicing by lines
lines_you_interest = [4, 5, 19]
slice_statements = func.slice_by_lines(
    lines=lines_you_interest,
    control_depth=3,
    data_dependent_depth=5,
    control_dependent_depth=2,
)

# Slicing by statements
statements_you_interest = func.statements[0:3]
slice_statements = func.slice_by_statements(
    statements=statements_you_interest,
    control_depth=3,
    data_dependent_depth=5,
    control_dependent_depth=2,
)

Statement-Level Analysis

Load a statement from a function

the_first_stmt = the_first_func.statements[0]
stmt_in_second_line = the_first_func.statement_by_line(2)
stmt_by_type = func.statements_by_type('tree-sitter Queries', recursive=True)

Statement Controls

pre_controls: list[Statement] = stat.pre_controls
post_controls: list[Statement] = stat.post_controls

Statement Data Dependencies

pre_data_dependents: dict[Identifier, list[Statement]] = stat.pre_data_dependents
post_data_dependents: dict[Identifier, list[Statement]] = stat.post_data_dependents

Statement Control Dependencies

pre_control_dependents: list[Statement] = stat.pre_control_dependents
post_control_dependents: list[Statement] = stat.post_control_dependents

AST Node

You can also get the AST node from a file, function, or statement.

file_ast = file.node
func_ast = func.node
stmt_ast = stat.node

ScubaTrace Landscape

ScubaTrace Landscape

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scubatrace-0.6.5.tar.gz (36.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

scubatrace-0.6.5-py3-none-any.whl (38.4 kB view details)

Uploaded Python 3

File details

Details for the file scubatrace-0.6.5.tar.gz.

File metadata

  • Download URL: scubatrace-0.6.5.tar.gz
  • Upload date:
  • Size: 36.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.9

File hashes

Hashes for scubatrace-0.6.5.tar.gz
Algorithm Hash digest
SHA256 ed48c932897a87a8f9c88983dde8f95ef64b208d9196ecfd3ee64d0fec854ffe
MD5 00dfede0d6337761d60764068da64589
BLAKE2b-256 da5f26a36c0d9c3b0f45a7fe7819c58507ea3482af993caf5ee0c4dcdf5df665

See more details on using hashes here.

File details

Details for the file scubatrace-0.6.5-py3-none-any.whl.

File metadata

  • Download URL: scubatrace-0.6.5-py3-none-any.whl
  • Upload date:
  • Size: 38.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.9

File hashes

Hashes for scubatrace-0.6.5-py3-none-any.whl
Algorithm Hash digest
SHA256 6ec9615b6d98ea4c2edf94bbc459116c985e07c418de94452f3fc63cf78da440
MD5 b42d34ed570603cb2cde9bd1300d49bd
BLAKE2b-256 8cd9f02d45acd0920c08fd1b394c927e99f14f64feed84efc123174dfbd84488

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page