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Testing software's changing features with environment-driven abstraction identification.

Zedong Peng¹, Prachi Rathod¹, Nan Niu¹

¹University of Cincinnati, Cincinnati, OH USA.

Requirements Engineering

|September 26, 2022

Summary

This summary is machine-generated.

This study introduces an automated method for identifying abstractions to enhance requirements-based testing. The approach uses novel patterns and pairs to improve testability and bug detection in software systems.

Keywords:

Abstractions Environmental assumptions and conditions Natural language Requirements-based testing

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Area of Science:

Software Engineering
Requirements Engineering
Automated Software Testing

Background:

Domain terms aid in requirements elicitation and modeling.
Extending assistance to requirements validation is crucial for robust software development.
Existing techniques may lack the precision needed for comprehensive testing.

Purpose of the Study:

To present an automated approach for identifying abstractions to support requirements-based testing.
To define novel patterns for generating testable abstractions.
To evaluate the accuracy and effectiveness of the proposed method.

Main Methods:

Utilized Wikipedia pages as a domain-independent corpus.
Defined five novel patterns using part-of-speech tagging and dependency parsing.
Framed candidate abstractions as pairs for testability.

Main Results:

The proposed abstractions demonstrated higher accuracy compared to a state-of-the-art technique.
The abstractions effectively revealed bugs and matched manual environmental assumptions.
Evaluated across Electronic Health Records and Web conferencing systems.

Conclusions:

The automated approach enhances requirements-based testing through accurate abstraction identification.
The abstraction format improves testability and guides testing execution.
The study proposes a new feature testing methodology focusing on environmental condition variations.