Generative AI applications in test automation and testing include: 9- Generating test cases 10- Generating test code 11- Test script maintenance 12- Test data generation 13- Test documentation 14- Test result analysis Generative AI Tools for Software Development Testing is critical in software and generative AI can support testing in a similar way to its support for software coding. It can analyze code for adherence to coding style guidelines, ensuring consistency and readability across a codebase. It can be used to automate the process of refactoring code, making it easier to maintain and update over time. ChatGPT is fixing a Python code that tries to calculate factorial of a number but runs into an error 7- Code refactoring It can help identify and fix bugs in the generated code by analyzing code patterns, identifying potential problems, and suggesting fixes.įigure 3. The mechanism of Amazon’s CodeWhisperer for reviewing code Generative artificial intelligence can also be used to make the quality checks of the existing code and optimize it either by suggesting improvements or by generating alternative implementations that are more efficient or easier to read.įigure 2. This can save time and reduce errors, especially for repetitive or tedious tasks. One of the most straightforward uses of generative AI for coding is to suggest code completions as developers type. Generating a simple Python script with OpenAI’s ChatGPT 4- Code completion This involves training a neural network on a large dataset of code examples, and then using the fine tuned network to generate code that is similar in structure and function to the examples it has been trained on.įigure 1. Writing code with generative AI is possible through a technique known as neural code generation. Generative AI in Coding 3- Code generation regarding security) which can be completed. 2- Requirement completionĪnalysts may forget important requirements (e.g. Generative AI applications in requirements analysis include: 1- Generating requirementsĪnalysts can prompt their high level requirements to fine-tuned large language models that have been exposed to best practice requirements documents.
Without clear requirements, software development process cannot start. Explain the top 3 use case areas of generative AI in coding.To help technical leaders form their generative AI approach about software engineering, we will Though generative AI tools have potential to accelerate the software development process, they come with challenges such as hallucination which can slow down coding or introduce critical issues to software.
Generative AI is the latest addition to approaches and technologies to speed up the development time. Software development tends to take longer and cost more than expected.
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