CodeChecker

CodeChecker is a static analysis infrastructure built on the LLVM/Clang Static Analyzer toolchain, replacing scan-build in a Linux or macOS (OS X) development environment.

CodeChecker is ported to Python3!
No Python2 support is planned. The minimal required Python3 version is 3.6.
Old virtual environments needs to be removed!

💡 Check out our DEMO showing some analysis results of open-source projects!

Main features

Command line C/C++ Analysis

• Executes Clang-Tidy, Clang Static Analyzer with Cross-Translation Unit analysis, Statistical Analysis (when checkers are available), and Cppcheck.
• Creates the JSON compilation database by wiretapping any build process (e.g., CodeChecker log -b "make").
• Automatically analyzes GCC cross-compiled projects: detecting GCC or Clang compiler configuration and forming the corresponding clang analyzer invocations.
• Incremental analysis: Only the changed files and its dependencies need to be reanalyzed.
• False positive suppression with a possibility to add review comments.
• Result visualization in command line or in static HTML.

Web-based report storage

• You can store & visualize thousands of analysis reports of many analyzers like Clang Static Analyzer (C/C++), Clang Tidy (C/C++), Facebook Infer (C/C++, Java), Clang Sanitizers (C/C++), Spotbugs (Java), Pylint (Python), Eslint (Javascript) ...
  For a complete list see Supported Analyzers
• Web application for viewing discovered code defects with a streamlined, easy experience (with PostgreSQL, or SQLite backend).
• Gerrit and GitLab integration Shows analysis results as GitLab or Gerrit reviews.
• Filterable (defect checker name, severity, source paths, ...) and comparable (calculates difference between two analyses of the project, showing which bugs have been fixed and which are newly introduced) result viewing.
• Diff mode: This shows the list of bugs that have been introduced since your last analyzer execution.
• Results can be shared with fellow developers, the comments and review system helps communication of code defects.
• Easily implementable Thrift-based server-client communication used for storing and querying of discovered defects.
• Support for multiple bug visualization frontends, such as the web application, a command-line tool and an Eclipse plugin.

Command line features

CodeChecker command has many subcommands which can be used for example to log and analyze your projects, print the results or start a web server. For full list see the following table or check the help message of this command (CodeChecker --help):

CodeChecker subcommand	Description
analyze	Execute the supported code analyzers for the files recorded in a JSON Compilation Database.
analyzer-version	Print the version of CodeChecker analyzer package that is being used.
analyzers	List supported and available analyzers.
check	Perform analysis on a project and print results to standard output.
checkers	List the checkers available for code analysis.
cmd	View analysis results on a running server from the command line.
fixit	Apply automatic fixes based on the suggestions of the analyzers.
log	Run a build command, collect the executed compilation commands and store them in a JSON file.
parse	Print analysis summary and results in a human-readable format.
server	Start and manage the CodeChecker Web server.
store	Save analysis results to a database.
version	Print the version of CodeChecker package that is being used.
web-version	Print the version of CodeChecker server package that is being used.

CodeChecker cmd subcommand also has many other subcommands which can be used to get data (products, runs, results, statistics) from a running CodeChecker server. For full list see the following table or check the help message of this subcommand (CodeChecker cmd --help):

CodeChecker cmd subcommand	Description
runs	List the available analysis runs.
history	Show run history of multiple runs.
results	List analysis result (finding) summary for a given run.
diff	Compare two analysis runs and show the difference.
sum	Show statistics of checkers.
token	Access subcommands related to configuring personal access tokens managed by a CodeChecker server.
del	Delete analysis runs.
update	Update an analysis run.
suppress	Manage and import suppressions of reports on a CodeChecker server.
products	Access subcommands related to configuring the products managed by a CodeChecker server.
components	Access subcommands related to configuring the source components managed by a CodeChecker server.
login	Authenticate into CodeChecker servers that require privileges.
export	Export comments and review statuses from CodeChecker.
import	Import comments and review statuses into CodeChecker.

Usage flow

• Step 1: CodeChecker log runs the given build command and records the executed compilation steps. These steps are written to an output file (Compilation Database) in a JSON format.
• Step 2: CodeChecker analyze uses the previously created JSON Compilation Database to perform an analysis on the project, outputting analysis results in a machine-readable (plist) format.
• Step 3: In this step, you can do multiple things:
  • Parse and pretty-print the summary and results from analysis result files (CodeChecker parse).
  • Store the results to a running CodeChecker server (CodeChecker store).
  • Compare two analysis results/runs to show the results that differ between the two (CodeChecker cmd diff).
  • etc.

For more information how to use CodeChecker see our user guide.

User documentation

• Getting started (How-To with examples)

C/C++ Analysis

• Analyzer User guide
• Avoiding or suppressing false positives
• Checker and Static Analyzer configuration
• GCC incompatibilities
• Suppressing false positives

Web based report management

• Webserver User Guide
• WEB GUI User Guide
• Command line and WEB UI Feature overview
• Security configuration
  • Configuring Authentication
  • Configuring Authorization
• Deployment
  • Deploy server using docker
• Server Configuration
  • Configuring Server Logging
  • Setting up multiple CodeChecker repositories in one server
• Continuous Integration(CI)
  • Setting up CI gating with Gerrit and Jenkins
• Database Configuration
  • PostgreSQL database backend setup guide
  • CodeChecker server and database schema upgrade guide

Storage of reports from analyzer tools

CodeChecker can be used as a generic tool for visualizing analyzer results.

The following tools are supported:

Language	Analyzer
C/C++	Clang Static Analyzer
	Clang Tidy
	Clang Sanitizers
	Cppcheck
	Facebook Infer
	Coccinelle
	Smatch
	Kernel-Doc
	Sparse
	cpplint
C#	Roslynator.DotNet.Cli
Java	SpotBugs
	Facebook Infer
Python	Pylint
	Pyflakes
JavaScript	ESLint
TypeScript	TSLint
Go	Golint
Markdown	Markdownlint
	Sphinx

For details see supported code analyzers documentation and the Report Converter Tool.

Common Tools

Useful tools that can also be used outside CodeChecker.

• Build Logger (to generate JSON Compilation Database from your builds)
• Plist to HTML converter (to generate HTML files from the given plist files)
• Report Converter Tool (to convert analysis results from other analyzers to the codechecker report directory format))
• Translation Unit Collector (to collect source files of a translation unit or to get source files which depend on the given header files)
• Report Hash generator (to generate unique hash identifiers for reports)

Helper Scripts

• Helper Scripts for daily analysis

Install guide

Install CodeChecker via pip

CodeChecker is available on the pypi and can be installed with the following command:

pip3 install codechecker

Note: this package can be installed on Linux, OSX and Windows systems where pip3 command is available. On OSX, intercept-build must be installed for logging (CodeChecker log). On Windows, logging is not available.

Installing CodeChecker via Snap package manager

CodeChecker is available on the Snap Store and can be installed with the following command:

sudo snap install codechecker --classic

Note: Unfortunately, the snap package supports only lower case command names. For this reason, you need to use codechecker command instead of CodeChecker everywhere. For a full list of available commands in the codechecker snap package, run snap info codechecker.

Linux

For a detailed dependency list, and for instructions on how to install newer Clang and Clang-Tidy versions, please see Requirements. The following commands are used to bootstrap CodeChecker on Ubuntu 20.04 LTS:

# Install mandatory dependencies for a development and analysis environment.
# NOTE: clang or clang-tidy can be any sufficiently fresh version, and need not
#       come from package manager!
#       In case of Cppcheck, the minimal supported version is 1.80.
sudo apt-get install clang clang-tidy cppcheck build-essential curl gcc-multilib \
      git python3-dev python3-venv

# Install nodejs dependency for web. In case of Debian/Ubuntu you can use the
# following commands. For more information see the official docs:
# https://nodejs.org/en/download/package-manager/
curl -sL https://deb.nodesource.com/setup_16.x | sudo -E bash -
sudo apt-get install -y nodejs

# Check out CodeChecker source code.
git clone https://github.com/Ericsson/CodeChecker.git --depth 1 ~/codechecker
cd ~/codechecker

# Create a Python virtualenv and set it as your environment.
# NOTE: if you want to develop CodeChecker, use the `venv_dev` target instead
# of `venv`.
make venv
source $PWD/venv/bin/activate

# [Optional] If you want to use external authentication methods (LDAP / PAM)
# follow the instructions in
# docs/web/authentication.md#external-authentication-methods

# Build and install a CodeChecker package.
make package

# For ease of access, add the build directory to PATH.
export PATH="$PWD/build/CodeChecker/bin:$PATH"

cd ..

Notes:

• By default, make package will build ldlogger shared objects for 32bit and 64bit too. If you would like to build and package 64 bit only shared objects and ldlogger binary you can set BUILD_LOGGER_64_BIT_ONLY environment variable to YES before the package build: BUILD_LOGGER_64_BIT_ONLY=YES make package.
• By default, the make package will build the UI code if it's not built yet or the UI code is changed. If you wouldn't like to build the UI code you can set the BUILD_UI_DIST environment variable to NO before the package build: BUILD_UI_DIST=NO make package.
• Use make standalone_package instead of make package to avoid having to manually activate the environment before running CodeChecker.

Upgrading environment after system or Python upgrade

If you have upgraded your system's Python to a newer version (e.g., from 2.7.6 to 2.7.12 – this is the case when upgrading Ubuntu from 14.04.2 LTS to 16.04.1 LTS), the installed environment will not work out-of-the-box. To fix this issue, run the following command to upgrade your checker_env too:

cd ~/codechecker/venv
python3 -m venv .

Mac OS X

For installation instructions for Mac OS X see Mac OS X Installation Guide documentation.

Docker

To run the CodeChecker server in Docker see the Docker documentation. You can find the CodeChecker web-server container at the Docker Hub.

Visual Studio Code Plugin

You can install and use CodeChecker VSCode extension from the Visual Studio Marketplace or from Open VSX.

Main features:

• Run CodeChecker analysis from the editor and see the results automatically.
• Re-analyze the current file when saved.
• Commands and build tasks for running CodeChecker as part of a build system.
• Browse through the found reports and show the reproduction steps directly in the code.
• Navigate between the reproduction steps.

For more information how to install and use this plugin see the repository of this extension.

Analyze your first project

Setting up the environment in your Terminal

These steps must always be taken in a new command prompt you wish to execute analysis in.

source ~/codechecker/venv/bin/activate

# Path of CodeChecker package
# NOTE: SKIP this line if you want to always specify CodeChecker's full path.
export PATH=~/codechecker/build/CodeChecker/bin:$PATH

# Path of the built LLVM/Clang
# NOTE: SKIP this line if clang is available in your PATH as an installed Linux package.
export PATH=~/<user path>/build/bin:$PATH

Execute analysis

Analyze your project with the check command:

CodeChecker check -b "cd ~/your-project && make clean && make" -o ./results

check will print an overview of the issues found in your project by the analyzers. The reports will be stored in the ./results directory in plist XML format.

Export the reports as static HTML files

You can visualize the results as static HTML by executing

CodeChecker parse -e html ./results -o ./reports_html

An index page will be generated with a list of all repors in ./reports_html/index.html

Optionally store the results in Web server & view the results

If you have hundreds of results, you may want to store them on the web server with a database backend.

Start a CodeChecker web and storage server in another terminal or as a background process. By default, it will listen on localhost:8001.

The SQLite database containing the reports will be placed in your workspace directory (~/.codechecker by default), which can be provided via the -w flag.

CodeChecker server

Store your analysis reports onto the server to be able to use the Web Viewer.

CodeChecker store ./results -n my-project

Open the CodeChecker Web Viewer in your browser, and you should be greeted with a web application showing you the analysis results.

Important limitations with older Clang versions

Clang 3.6 or earlier releases are NOT supported due to CodeChecker relying on features not available in those releases.

If you have Clang 3.7 installed you might see the following warning message:

Hash value wasn't found in the plist file.

• Use Clang >= 3.8 or trunk r251011 — otherwise CodeChecker generates a simple hash based on the filename and the line content. This method is applied for Clang-Tidy results too, because Clang-Tidy does not support bug identifier hash generation currently.

Developer documentations

• Architecture
• Package layout
• Dependencies
• Thrift interface
• Package and integration tests
• Checker documentation mapping file

Conference papers, presentations

• A high-level overview about the infrastructure is available amongst the 2015Euro LLVM Conference presentations.
  Dániel KRUPP, György ORBÁN, Gábor HORVÁTH and Bence BABATI:
  Industrial Experiences with the Clang Static Analysis Toolset