Importance of Structured Prompt Engineering to Generate Effective Test Cases

As demand for Artificial Intelligence (AI) grows, best practices for using different AI tools are becoming critical. To scale AI implementation enterprise-wide, prompt engineering has become vital in developing AI-enabled applications and utilizing them to complete day-to-day engineering tasks. One such task is creating functional test cases. Software testing is a crucial stage in the Software Development Life Cycle and consumes a significant portion of the overall development timeline. This study was conducted while evaluating a test management tool that utilizes AI to generate test cases for UI (User Interface) and API (Application Programming Interface) applications. While generative AI is the future, using AI without proper guardrails and prompt standards can become counterproductive. This study demonstrates this by using multiple real-time industry use cases.

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Publication Details

Journal
International Journal of Computer Science and Engineering
Published
2025-08-30
DOI
https://doi.org/10.14445/23488387/ijcse-v12i8p104
Primary Topic
Risk and Safety Analysis
Type
article
Field-Weighted Citation Impact
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article

Importance of Structured Prompt Engineering to Generate Effective Test Cases

International Journal of Computer Science and Engineering
Risk and Safety Analysis
article

Importance of Structured Prompt Engineering to Generate Effective Test Cases

article en

Abstract

As demand for Artificial Intelligence (AI) grows, best practices for using different AI tools are becoming critical. To scale AI implementation enterprise-wide, prompt engineering has become vital in developing AI-enabled applications and utilizing them to complete day-to-day engineering tasks. One such task is creating functional test cases. Software testing is a crucial stage in the Software Development Life Cycle and consumes a significant portion of the overall development timeline. This study was conducted while evaluating a test management tool that utilizes AI to generate test cases for UI (User Interface) and API (Application Programming Interface) applications. While generative AI is the future, using AI without proper guardrails and prompt standards can become counterproductive. This study demonstrates this by using multiple real-time industry use cases.

International Journal of Computer Science and EngineeringVol. 12(8)
Optech (Canada) (CA)
Openalex Percentile: Top 75%
Risk and Safety Analysis
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