Legacy code, a relic of past development practices, poses significant security risks and development challenges to public sector organizations. These outdated systems are often incompatible with modern security tools and create vulnerabilities that cybercriminals can exploit.
Beyond security, maintaining legacy code is a costly endeavor, requiring specialized skills and significant developer time. As a result, organizations are trapped in a cycle of technical debt, struggling to innovate and adapt to changing business needs.
By leveraging AI-driven testing, security capabilities, and code refactoring techniques, organizations can modernize their legacy systems, mitigate security risks, and empower development teams to focus on innovation.
What’s the problem with legacy code?
Legacy code refers to an existing code base that a team inherits from previous team members and continues to use and maintain. The codebase may function correctly, but its long history of modifications by various developers can obscure its original intent and introduce unintended consequences. The current team may struggle to distinguish between valuable and unnecessary changes. Furthermore, the code might rely on outdated frameworks or programming languages, increasing the risk of vulnerabilities and maintenance difficulties.
Organizations that choose to retain legacy code expose themselves to a multitude of risks. Because the code wasn’t designed for newer technologies, teams may be unable to integrate it with modern software, potentially impacting product performance, scalability, and customer experience.
A particularly significant concern is the lack of security scanners designed for legacy code. This leaves organizations exposed to undetected vulnerabilities, especially when updates are made by developers unfamiliar with the codebase or its underlying language. Moreover, legacy code frequently relies on memory-unsafe languages like C or C++, which are proven to host 70% of identified vulnerabilities.
The U.S. Cybersecurity and Infrastructure Security Agency (CISA) has emphasized the heightened security risks associated with using unsupported software in critical infrastructure and the subsequent risk to national security. By continuing to rely on outdated code, organizations jeopardize their security posture and undermine their ability to innovate and adapt to the evolving technology landscape.
The solution is code refactoring
Code refactoring, a controlled technique for improving the design of an existing code base, allows the securing and modernizing of legacy code without obscuring its original functionality. There are many refactoring techniques – from inline refactoring, which involves simplifying code by removing obsolete elements, to refactoring by abstraction, where duplicate code is deleted.
What’s important to know is that code refactoring requires time and significant developer skills to do well. It also requires a lot of testing when developers are already busy working on their other tasks. While code refactoring is certainly the answer to bringing your legacy code into the future, making it readable, efficient, and secure, it is a project in and of itself, especially at scale.
How AI can help
AI is already accelerating software development, and there’s a lot that AI can do to help teams accelerate the refactoring process. AI-powered tools can decipher complex legacy code, generate new code, and bridge knowledge gaps for developers unfamiliar with specific languages. By automating tedious tasks and providing intelligent assistance, AI can speed up the modernization of legacy systems.
AI can further enhance refactoring by automating testing and security tasks. By analyzing root causes, generating tests, and identifying vulnerabilities, AI can help developers remediate vulnerabilities efficiently. With AI as a powerful ally, code refactoring is accessible and achievable for organizations.
According to GitLab research, 34% of all respondents using AI across the software development lifecycle already use AI to modernize legacy code. This is even higher in the financial services industry (46%).
While AI offers significant potential for accelerating code modernization, it also requires testing, guardrails, and human oversight. To ensure optimal security, teams should combine AI-powered tools with other security measures, such as creating a dynamic software bill of materials (SBOM). An SBOM provides a comprehensive inventory of software components, including legacy code, enabling organizations to identify and mitigate potential vulnerabilities.
Bring your codebase into the future
While the transition from legacy codebase maintenance to modernization may seem daunting, it is a crucial step toward ensuring organizational security and future-proofing operations. Organizations can streamline processes, reduce costs, and boost efficiency by embracing modern tools and techniques.
Instead of allocating valuable resources to deciphering outdated languages and frameworks, development teams can focus on innovative product development. AI-powered tools can automate the complex task of code refactoring, ensuring that legacy code is not only secure but aligned with modern best practices.
About the Author
Joel Krooswyk has over 25 years of experience in the Software industry. His end-to-end software development life cycle expertise benefits customers and employees alike. His leadership experience spans not only the U.S. Public Sector, but also small, mid-market, and enterprise businesses globally. Joel is an experienced leader, team builder, communicator, thought leader and researcher.
His experience spans development, QA, product management, portfolio planning, and technical sales, and he has written a half million lines of unique code throughout his career. On an average day, you’ll find him discussing software modernization, cybersecurity, governance and compliance, AI, ongoing digital transformation, and automation.
Learn more about GitLab at https://about.gitlab.com/solutions/public-sector/ and follow Joel on LinkedIn at https://www.linkedin.com/in/joelrkrooswyk/.
