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Usability Evaluation of Augmented Reality: A Neuro-Information-Systems Study

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Technology adoption performance evaluation applied to testing industrial REST APIs.

Alexander Poth¹, Olsi Rrjolli¹, Andrea Arcuri²

¹Volkswagen AG, Wolfsburg, Germany.

Automated Software Engineering

|December 5, 2024

Summary

This summary is machine-generated.

Automated test-case generation tools aid software testing. A systematic approach evaluated AI and algorithm-driven methods for REST API testing, showing benefits for test engineers.

Keywords:

API validation Benchmarking LLM Quality engineering Requirements-based testing SBST Test automation Test-case generation

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Area of Science:

Software Engineering
Artificial Intelligence in Software Testing
Automated Software Testing

Background:

Manual software testing is labor-intensive and prone to errors.
Automated test-case generation offers a solution to improve efficiency and correctness.
Various AI (e.g., evolutionary, LLM) and algorithmic approaches exist, each with unique strengths and weaknesses for industrial integration.

Purpose of the Study:

To present a systematic approach for evaluating test-case generation methodologies.
To integrate these methodologies into a scalable enterprise setup for IT product development.
To specifically address black-box testing of REST APIs using OpenAPI schemas.

Main Methods:

Developed and applied the Technology Adoption Performance Evaluation (TAPE) approach.
Conducted a case study within Volkswagen AG's Group IT.
Evaluated existing tools: OpenAPI Generator, EvoMaster, and StarCoder, based on diverse technologies.

Main Results:

The TAPE approach provides a framework for assessing test-case generation tools.
Evaluated tools demonstrated significant benefits for test engineers.
Facilitated test-case specification and design within a large industrial IT environment.

Conclusions:

The systematic evaluation and integration approach (TAPE) is effective for industrial adoption of test-case generation tools.
AI and algorithm-driven tools can enhance the efficiency and quality of software testing for REST APIs.
The study confirms the value of these tools in streamlining IT product development and service delivery.