Oracle today revealed it is developing a generative artificial intelligence assistant that leverages multiple large language models to create Java and SQL code, in a way that is tuned to an organization’s existing code bases and best practices that an organization employs.
Vijay Kumar, vice president of product marketing for application development services and developer relations for Oracle, said Oracle Code Assist will also enable DevOps teams to create code for provisioning IT infrastructure resources hosted on the Oracle Cloud Infrastructure (OCI) service.
Scheduled to become available at an unspecified future date, Oracle Code Assist will also be designed to update, upgrade and refactor code written in most modern programming languages. In addition, upgrading from older versions of programming languages will become more automated.
Pinpointing Bugs
Deployed as a plugin for integrated development environments (IDEs) such as JetBrains, IntelliJ IDEA, or Microsoft Visual Studio Code, Oracle Code Assist will be specifically trained to provide expert, opinionated feedback such as code snippets, dependency analysis, error mitigation alternatives, test cases, annotation, summarization and documentation that will make it simpler to pinpoint the precise location of bugs within an application, noted Kumar.
Benefits will include code suggestions based on learned context and patterns to reduce the time spent writing boilerplate code, summarizations of existing code, increased text coverage and faster code reviews.
Finally, any code generated will not be sourced from examples lacking non-permissive licenses, to minimize potential compliance issues.
In effect, Oracle is committing to training LLMs to generate code using samples it has vetted to eliminate hallucinations that occur when general-purpose LLMs such as ChatGPT are invoked. A general-purpose LLM is trained using samples of code of varying quality, pulled from across the web. As a result, they are more likely to create code that, for example, contains known vulnerabilities.
One immediate benefit of Oracle Code Assist should be an acceleration to a more recent version of Java. Oracle most recently made available Java 22, but many organizations are still running older, slower versions of Java that are less secure. Conversely, however, generative AI is also being used to accelerate the conversion of Java into other programming languages.
Ultimately, DevOps teams will be able to take advantage of Oracle Code Assist to create an automated feedback loop, noted Kumar. Additionally, he added, onboarding developers to existing application development projects will become much easier.
It’s not clear whether senior or junior developers will benefit most from generative AI. In theory, junior developers should be able to take on more complex tasks. However, senior developers may find that many of the manual tasks that today conspire to reduce their productivity are being eliminated.
One way or another, the overall pace at which applications are being developed and deployed is thanks to the rise of generative AI is now being accelerated. The only thing left to determine is how best to ensure the quality of the code being generated meets the requirements of enterprise IT organizations that today depend more on software than ever before.