Muse leverages a broad range of analyzers that can be tailored to your code-base. Below is a list of the analyzers we’ve incorporated and made available within the Muse platform. And if you don’t see your favorite analyzer or language on the list, fill out the form at the bottom to make a suggestion.
Languages: Java, C, C++
Error Patterns: https://fbinfer.com/docs/all-issue-types
Infer was developed at Facebook and uses advanced compositional analysis techniques to provide deep insight into code behavior while keeping analysis times low. Infer checks Java for null pointer exceptions, resource leaks, performance issues, command injection and other information flow vulnerabilities, annotation consistency, and concurrency errors such as race conditions and deadlocks. Infer checks C/C++/ObjectiveC code for null pointer dereferences, memory leaks, coding convention violations, and API misuse errors.
Error Patterns: https://errorprone.info/bugpatterns
Developed by Google, this Java bug detection tool looks for language-specific error patterns and API mis-use errors. It is implemented as a compiler extension, and so has access to type information, class hierarchies, and dependency data. This gives it deeper insight into the code than most linters and allows it to detect more bugs while maintaining a low false positive rate. ErrorProne can also be extended with custom rules.
Error Patterns: https://find-sec-bugs.github.io/bugs.htm
This tool provides static analysis for security audits of Java web applications and Android applications targeting many of the OWASP Top Ten.
Languages: Java, C, C++
Error Patterns: https://fbinfer.com/docs/checker-quandary#list-of-issue-types
Quandary is an extension of Infer that detects flows of values between sources and sinks that don’t
pass through a “sanitizer”. It has a small list of built-in sources and sinks, but also provides a
means for defining custom sources and sinks via an
.inferconfig file included in the same
directory as the build files (see an example
Quandary can be used to detect cross-site scripting, shell/sql injection, untrusted data use, and
logging of private data.
Error Patterns: https://eslint.org/docs/rules
Lightweight static analysis for many languages. Find and block bug variants with rules that look like source code.
Staticcheck is a state of the art linter for the Go programming language that finds bugs and performance issues, offers simplifications, and enforces style rules.
golangci-lint aggregates and runs 31 Golang linters to catch a broad range of common Go errors.
Error Patterns: https://pyre-check.org/docs/error-types.html
Pyre is a fast, scalable type checker for large Python 3 codebases, designed to help improve code quality and development speed by flagging type errors, following the typing standards introduced in PEP484 and PEP526. Pyre also includes the Pysa information flow analysis tool which can be configured to detect and warn on flows between functions labeled as sources and sinks.
Bandit is a security linter from PyCQA designed to find common security issues in Python code. To do this Bandit processes each file, builds an AST from it, and runs appropriate plugins against the AST nodes.
RuboCop is a Ruby code style checker (linter) and formatter based on the community-driven Ruby Style Guide.
Detekt a static code analysis tool for the Kotlin programming language. It operates on the abstract syntax tree provided by the Kotlin compiler.
Languages: Infrastructure Code (Terraform, Cloudformation, K8S)
Checkov is a static code analysis tool for infrastructure-as-code. It scans cloud infrastructure managed in Terraform, Cloudformation, Kubernetes, Arm templates or Serverless Framework and detects misconfigurations.
Languages: Bash, Shell
Error Patterns: https://github.com/koalaman/shellcheck/wiki/Checks
ShellCheck is a code analyzer for your shell scripts.
Cobra is a structural source code analyzer. Fast and easy to configure, Cobra is an ideal choice for enforcing API rules without needing compilation.
HLint is a tool for analysing Haskell projects and outputting discovered short-comings in a helpful way with possible solutions for detected problems. HLint is searching for not only performance or error-prone code pieces, but it also can help with establishing and applying best-practices from the whole Haskell ecosystem.
Markdownlint - MDL (Disabled by Default)
MDL is a tool to check markdown files and flag style issues.
PMD (Disabled by Default)
Error Patterns: https://pmd.github.io/pmd-6.23.0/pmd_rules_java.html
The tool finds common programming flaws like unused variables, empty catch blocks, unnecessary object creation, and so forth.
PMD is not enabled by default. To add, copy this line into your Muse configuration file.
customTools = [ "https://docs.muse.dev/scripts/pmd.sh rulesets/java/quickstart.xml" ]
Click here to learn how to create a Muse configuration file.
Don’t see your favorite analyzer here, or looking for additional language support? Fill out the form below to give us a suggestion…we’re a new start-up and welcome ideas for how to make Muse work for you!