Docker, Inc.® announced Docker Hardened Images (DHI), a curated catalog of security-hardened, enterprise-grade container images designed to meet today’s toughest software supply chain challenges.
Delivering clean and safe software is no longer an option for developers or the organizations they work for. Customers have little patience for buggy, error-prone apps and software that's rife with critical vulnerabilities. These sort of quality and security issues can seriously hurt a company's brand reputation and negatively impact revenues.
Security has become a particular concern for developers. The majority of software security vulnerabilities are the result of coding errors, not malicious attacks. According to a recent analysis(link is external) of over 500 Github security advisories from 2019-2020, 83% of advisories were caused by coding mistakes, while only 17% "were related to explicitly malicious behavior such as backdoor attempts."
Because of these factors, developers and development teams are continuously looking for ways to achieve cleaner and safer code. As a result, static analysis tools have begun to grow rapidly in popularity.
On a basic level, code linting software analyzes source code to flag issues during the development process and helps developers find and fix typos, programming errors, syntax, and bugs.
But is it enough?
No. That's why Developers are turning to modern day linters.
Modern day linters are becoming a must-have commodity in every developer's toolbox because of their advanced capabilities. Good linting tools not only perform basic checks, but are also capable of running static analysis to detect security vulnerabilities, memory leaks, code compliance, and more, right in the development environment. With developers taking more ownership of security, these features are critical.
Support for a Shift Left Approach
Bugs in production apps can wreak major havoc, exposing sensitive user data and jeopardizing a company's revenue and reputation. Detecting and fixing these bugs in pre-production is critical to avoiding these issues. It's also much easier and cheaper to correct coding errors during pre-production than it is once an app is in production. Aside from reducing the risk of end-user impact and protecting your brand's reputation, detecting issues earlier in the software pipeline can also reduce development costs and avoid delayed projects.
Developers can achieve this by adopting a shift left approach to software development — testing code, finding errors and fixing them as early as possible, often dynamically as you code (i.e. in your IDE using a "Clean as you Code" approach). These advanced linting tools ultimately support this shift left approach, allowing developers to detect issues earlier in the development cycle. Shifting left not only allows developers to deliver clean and safe code, but also improves the overall maintainability and reliability of their codebase. Moreover, these checks can be built into a team's development toolchain — so that bugs and security vulnerabilities can be prevented before an app is deployed to production.
Beyond Identifying Errors: Helping Developers Grow
Good linting tools need to do more than just identify syntax, style, bugs, or security issues — they must provide helpful cues on what the issues are, why they are harmful, and how they should be fixed. When a linter flags that a developer has made an error, it should offer context explaining the reasoning behind the rule that was broken, information on why it should be followed, provide helpful examples, and a rundown of what can go wrong if the rule isn't followed. Developers shouldn't change code simply because a linter told them to. They should change it because they've learned to do better.
With these insights, developers can learn from their mistakes, uncover new best practices to avoid those mistakes, master new programming languages faster, and code safer and better apps in the long run. This not only improves software quality, but boosts the efficiency of an organization's entire development team. As a result, organizations can reduce technical debt and spend more developer resources building new features rather than fixing flawed code.
For developers to learn from their mistakes, instant feedback is essential. Linting tools should flag any errors or quality issues while developers are writing code, providing more of an intuitive spell-checking or grammar checking experience. This real-time feedback makes it easier for developers to recognize mistakes and remember how to prevent them in the future.
This approach also supports better code ownership. When issues are raised as a developer adds new code, it's clear that person is responsible for fixing it. This avoids the confusion common in traditional testing methods, when errors aren't flagged until long after code is written and development teams have to manually review the codebase to determine what the appropriate next step is.
Conclusion
Modern code linters play a pivotal role in the development process, enabling developers to improve code quality and security, and should serve as more than just another testing or error monitoring tool. By Offering robust real-time insights, including detailed context for every issue flagged, clear guidance on fixing those issues and best practices for avoiding them, programmers get better at their job in the long term and enterprises will reap major benefits from improved developer skills and efficiency.
Industry News
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JFrog announced the integration of its foundational DevSecOps tools with the NVIDIA Enterprise AI Factory validated design.
GitLab announced the launch of GitLab 18, including AI capabilities natively integrated into the platform and major new innovations across core DevOps, and security and compliance workflows that are available now, with further enhancements planned throughout the year.
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CIQ announced the tech preview launch of Rocky Linux from CIQ for AI (RLC-AI), an operating system engineered and optimized for artificial intelligence workloads.
The Linux Foundation, the nonprofit organization enabling mass innovation through open source, announced the launch of the Cybersecurity Skills Framework, a global reference guide that helps organizations identify and address critical cybersecurity competencies across a broad range of IT job families; extending beyond cybersecurity specialists.
CodeRabbit is now available on the Visual Studio Code editor.
The integration brings CodeRabbit’s AI code reviews directly into Cursor, Windsurf, and VS Code at the earliest stages of software development—inside the code editor itself—at no cost to the developers.
Chainguard announced Chainguard Libraries for Python, an index of malware-resistant Python dependencies built securely from source on SLSA L2 infrastructure.
Sysdig announced the donation of Stratoshark, the company’s open source cloud forensics tool, to the Wireshark Foundation.
Pegasystems unveiled Pega Predictable AI™ Agents that give enterprises extraordinary control and visibility as they design and deploy AI-optimized processes.
Kong announced the introduction of the Kong Event Gateway as a part of their unified API platform.
Azul and Moderne announced a technical partnership to help Java development teams identify, remove and refactor unused and dead code to improve productivity and dramatically accelerate modernization initiatives.