Browse free open source Source Code Analysis tools and projects below. Use the toggles on the left to filter open source Source Code Analysis tools by OS, license, language, programming language, and project status.
A source code analyzer
The web-based visual programming editor
Versatile typeface for code, from code
Continuous inspection
Static source code analysis tool for C and C++ code
The .NET Compiler Platform
Integrates Checkstye into the Eclipse IDE
Visual Studio extension for syntax highlighting assembly
Side-by-side diff viewer, editor and merge preparer
Loads environment variables automatically
It's not just a linter that annoys you!
Code security review tool for C/C++, C#, VB, PHP, Java, PL/SQL, COBOL.
A web based file manager, web IDE / browser based code editor
Code editor that connects you to your creation with instant feedback
Reformats Java source code to comply with Google Java Style
Node.js express.js MongoDB JWT REST API - Basic Project Skeleton
Tokenize PHP files and detects violations of coding standards
An extensible multilanguage static code analyzer
Automated mass refactoring of source code
A static analysis tool for shell scripts
Docker image that provides static analysis tools for PHP
Open source source code analysis software is a type of software that is developed and released to the public for free, meaning anyone has access to it. It’s typically used by developers and software engineers as a tool to evaluate how their code performs. The primary purpose of open source source code analysis software is to improve the quality, security, and maintainability of the source code.
Open source source code analysis tools can be divided into two categories: Static Analysis (SAST) tools and Dynamic Analysis (DAST) tools. Both SAST and DAST are automated processes that scan through the entire project or application files to look for vulnerabilities or weaknesses in the code base.
Static Analysis Tools are designed to analyze an individual’s written code at compile time, meaning before any actual execution takes place. They do this by looking for issues such as potential coding errors, dead/unreachable codes, or misuse of APIs or libraries. This type of tool tends to have a much shorter runtime because it only needs to analyze each file once; however, it can still be quite complex depending on how many libraries or APIs your project uses. Some popular SAST open source options include: pylint-jsHint, Cppchecker & ESLint Fortify.
Dynamic Analysis Tools were created with run-time concerns in mind; they focus on analyzing executed programs rather than just compiled ones. These tools act like a black box testing framework; simulating user interactions with your app during runtime so that any unintended behaviors can be detected before deployment occurs for real users in production environments. Common DAST open source options include OWASP ZAP & Arachni among others.
Overall open source code analysis tools are extremely helpful when it comes developing high quality apps without introducing new security flaws due their thoroughness while reviewing applications or projects which often go overlooked during development cycles due time constraints or other factors beyond our control. Nevertheless, it’s important to note that these types of tools should be used in conjunction with manual code reviews and other security measures like penetration testing or bug bounties for maximum effect.
Open source source code analysis software typically has no upfront cost, as it is available for free with the source code distributed openly. However, there may be associated costs such as licensing and maintenance fees to consider when using open source software. Furthermore, depending upon the type of analysis that is being done, additional hardware or software requirements might incur additional costs. It can also take significant time and effort to integrate open source analysis tools into existing development process and ensure proper security standards are met throughout its usage. If a business requires comprehensive support then there will likely be an associated cost for assistance from either the community of developers or from professional service providers who specialize in developing services around open source software. Overall, the cost of using open source software can vary greatly depending upon how involved one chooses to be in deploying and maintaining their own customized solution.
Open source source code analysis software can generally be integrated with any type of applications or software that use codes. This includes programming languages such as Java, Python, JavaScript and HTML5, as well as backend systems such as Linux or Windows. Furthermore, it is also possible to integrate open source source code analysis software with development tools like GitHub and Jenkins. Additionally, some open source source code analysis tools have specific integrations with web application frameworks such as AngularJS and ReactJS. Finally, integration with cloud-based services such as Amazon AWS and Microsoft Azure is possible through various plugins available in the market today.
Getting started with open source source code analysis software is relatively straightforward. First, users should identify the type of project they want to analyze and what their goals are for the analysis. Once these considerations have been addressed, users should select an appropriate open source tool that meets their requirements.
The next step is to download and install the application onto a computer or server. This usually involves downloading the binary file in a supported package format (e.g., Debian), running it through an application installer, and following any other installation instructions that may be provided. After installing the tool and ensuring it has been configured correctly, users can begin analyzing code. Depending on the complexity of their project and which language they’re working with (e.g., Java or C++), they may need to learn more about how to use specific features of their chosen tool in order to conduct effective analyses of their codebase(s).
Source code analysis tools generally provide some type of graphical user interface (GUI) so that users don’t have to interact with command-line utilities when running queries against their codebase(s). A GUI typically makes it easier for users to navigate through different parts of an application and quickly find areas where potential issues exist, such as security flaws or logic errors in algorithm implementations; without having to manually comb through hundreds or even thousands of lines of code themselves.
Finally, users may want to review the results generated by their chosen open source source code analysis tool before making any changes based on those results. The GUI will often provide detailed information regarding each discovered issue that can be used by developers as a starting point for correcting any problems uncovered during the analysis process. With this knowledge in place, developers can now apply fixes as necessary in order to improve the overall quality and security posture of theirs applications going forward.