Can AI Rescue Wall Street from its 'Spaghetti Code' Crisis?

Can AI Rescue Wall Street from its 'Spaghetti Code' Crisis?

In a world where tape cassettes and floppy disks are things of the past, there's a unique tech challenge that hasn't disappeared - Cobol. This 64-year-old programming language is still crucial for processing trillions of dollars in transactions on Wall Street and in the federal government. But with Cobol experts in short supply, keeping these systems up and running is a growing challenge.

Bill Hinshaw, often referred to as the "Cobol Cowboy," is an 82-year-old who leads a team of 600 engineers, some from the '60s and '70s, to keep Cobol systems running. They're often called in for emergency fixes, like when a company's software crashes due to a lack of in-house expertise.

What is the Spaghetti Code Problem?

The 'Spaghetti Code' problem refers to poorly structured and difficult-to-maintain source code within software applications. This term is often used pejoratively to describe code that lacks organization and clear structure. Spaghetti code typically arises due to factors such as changing project requirements, the absence of programming style guidelines, and the inexperience of software developers.

This type of code often relies on GOTO statements instead of structured programming constructs, resulting in complex and tangled control structures that make it challenging to understand and modify. The term "spaghetti" comes from the idea that the program's flow resembles a bowl of tangled and twisted spaghetti, with code paths that are hard to follow.

In some cases, spaghetti code can also refer to an anti-pattern in object-oriented programming, where code is written in a procedural style within the context of an object-oriented language. This might involve creating classes with overly long and messy methods or neglecting key object-oriented principles like polymorphism. Such code can significantly reduce the clarity and comprehensibility of a software system, making it difficult to maintain and extend.

What is the Role of Generative AI?

Now, tech giants like IBM and Microsoft are looking to tackle this problem with generative AI. They aim to use AI to transform outdated Cobol code into modern languages, making it easier to maintain and update. This technology has the potential to save billions for Wall Street and government agencies, reduce costs, and expedite modernization efforts.

IBM, for instance, has developed a tool that uses generative AI to translate Cobol code into Java. Unlike older code translators, this AI can produce well-structured code that is easier to understand and modify. Companies can modernize their code bases faster, potentially saving substantial amounts.

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Business Opportunities for Tech Companies

IBM's generative AI solution has become a major business opportunity. Many Fortune 100 companies have become clients, and the demand for Cobol-to-Java translation software is high.

GitHub, a Microsoft-owned developer platform, has also entered the game with its generative AI-powered assistant, GitHub Copilot. It can help modernize legacy infrastructure by suggesting code changes and even translating Cobol into other languages.

AI's Promise and Human Involvement

While AI holds great promise for code modernization, human involvement remains essential. AI-generated code isn't flawless and should undergo testing. There are risks, such as potential security issues in AI-generated code. Nevertheless, AI offers a ray of hope in untangling the "spaghetti code" that has troubled big banks for years.

AI may be the answer to the 'spaghetti code' crisis that has long plagued Wall Street. While AI solutions like those from IBM and GitHub hold enormous promise, human oversight and testing are crucial for ensuring security and functionality. The finance industry is hopeful that AI can finally resolve this long-standing tech challenge.