The Julia programming language is widely considered a powerful and versatile tool for modern technical computing. Combining the high-level syntax and dynamism of languages like Python with the performance capabilities of languages such as C and Fortran, Julia is the go-to choice for a diverse range of computational tasks. Julia’s popularity and appeal lie in the elegant syntax, exceptional speed, and scalability that make it suitable for building computationally intensive tasks or everyday programming needs.
JuliaHub is the platform that works with the Julia language to empower developers and enterprises using the Julia programming language to build complex systems, proprietary packages, and scientific applications. The platform offers a comprehensive suite of tools and services built specifically for the complex use cases of technical computing. Right from package management and version control to code analysis and deployment, JuliaHub becomes a one-stop shop for everything you need to build, test and deploy Julia code with ease including tools that help enforce coding standards for the Julia language.
Static Code Analysis
With the rising adoption, ensuring code quality and security becomes crucial. This is where Static Code Analysis (SCA) plays a vital role in the Julia development process. Let's explore what SCA is and how it benefits Julia developers.
Static Code Analysis (SCA) is an integral component of software development and testing that helps analyze source code. It helps identify errors, style violations, vulnerabilities, and deviations from coding standards before the code is in production. Typically, static code analysis is performed with purpose-built tools called static code analyzers that parse through the codebase following its logic and structure.
As opposed to dynamic analysis, which involves running code to detect issues at runtime, static analysis is performed during the development phase. This allows developers to catch errors early in the development process, and shift left.
Early error detection is not only significantly cheaper but also less disruptive. One big advantage of executing static code checks is to find security flaws and vulnerabilities in the code that could be exploited by attackers. For organizations in heavily regulated domains, static code analysis ensures that your code adheres to industry-specific norms for regulatory governance and compliance. This whitepaper outlines the best practices to minimize risks and maintain a secure Julia codebase.
Semgrep lets developers create custom code patterns to scan for specific issues. For example, Semgrep can be used to identify common security vulnerabilities such as SQL injection or cross-site scripting (XSS) attacks by scanning for patterns indicative of these issues in the codebase. Using instant feedback and insights, developers can fix security issues early, ensuring the security and reliability of their code in production. In the next section, we’ll present a video that shows how this works.
Julia Code Scanning with Semgrep
To learn more about Julia code scanning with Semgrep, watch this video.
What we are building next
The current implementation of our code scanning tools provides you text output of the results based on the Julia packages you asked it to scan. Next quarter, we hope to take this information and provide it within the JuliaHub web interface itself. We’re hoping to provide scan results next to each package in JuliaHub and indicate the severity of weakness found in package code. Further, we plan on helping teams develop a way to upload and scan their entire project for weaknesses and vulnerabilities by integrating Semgrep more fully into our registries and project tools. Finally, we also aim to build a more robust reporting tool that can be fully customized and sent to your DevSecOps and Compliance team via email and within the JuliaHub UI.
If you would like to learn more about JuliaHub, explore our code analysis tools and let us help you keep your Julia code safe, contact us today. You can learn even more about how Semgrep works by reading our blog here and then signing up for a free version of JuliaHub.
