Jun 2024· arXiv.org· Vol abs/2406.07021· 13 citations· 26 references
Computer Science
TL;DR
A web-based software tool is introduced that employs an LLM-based agent and prompt engineering to automate the generation of test case scenarios against user requirements and crafting test case scenarios based on these stories.
Abstract
Large Language Models (LLMs) are widely used in Software Engineering (SE) for various tasks, including generating code, designing and documenting software, adding code comments, reviewing code, and writing test scripts. However, creating test scripts or automating test cases demands test suite documentation that comprehensively covers functional requirements. Such documentation must enable thorough testing within a constrained scope and timeframe, particularly as requirements and user demands evolve. This article centers on generating user requirements as epics and high-level user stories and crafting test case scenarios based on these stories. It introduces a web-based software tool that employs an LLM-based agent and prompt engineering to automate the generation of test case scenarios against user requirements.
This systematic review presents an analysis of the "Vibe Coding" methodology — a contemporary approach to the iterative software development process using Large Language Models (LLMs). Code generation tools are transforming software development by enabling programmers to formulate tasks and describe the desired behavio...
A. Dzhonov, S. M. Avdoshin· INFORMACIONNYE TEHNOLOGII· 0 citations
This extended version of Design of Test Cases Based on the Language Extended Lexicon and the Requirements Specification has been enhanced by incorporating active participation from both the testing team and the client during the test-case generation stage, and integrates an AI agent acting as an expert tester in functi...
Julieta Screpnik, Leandro Antonelli, María Alejandra Paz Menvielle· Cadernos do IME - Série Info...· 0 citations
W WiseSpec is proposed, a novel requirements-driven agent framework for repository-level code generation that automatically constructs structured and information-rich requirements, assesses their quality through execution-based evaluation, and iteratively refines them to better guide code generation.
This paper addresses automated unit test generation with large language models (LLMs). LLM-based test generation has not yet attained a quality level sufficient for practical use in industry. Although LLMs often reproduce API syntax faithfully, they frequently disregard semantic usage constraints and execution-environm...
This work proposes TraceDev, a multi-agent framework for automated software development grounded in use cases that contain multiple functional points and complex semantics, and demonstrates the effectiveness of TraceDev in repository-level code generation from requirements.
Evaluated on real-world system-level requirements documents, comprising more than 720 requirements and 72 use cases, the approach generates system-level diagrams comparable to those created by experts and provides valuable architectural recommendations.
Bastian Franze, Dominik Fuchß, Friedrich Wattenberg et al.· IEEE International Requireme...· 0 citations
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