Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Computer Science

First Advisor's Name

Peter J. Clarke

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Xudong He

Second Advisor's Committee Title

Committee member

Third Advisor's Name

Masoud Sadjadi

Third Advisor's Committee Title

Committee member

Fourth Advisor's Name

Monique Ross

Fourth Advisor's Committee Title

Committee member

Fifth Advisor's Name

Debra Vandermeer

Fifth Advisor's Committee Title

Committee member

Sixth Advisor's Name

Tariq M. King

Sixth Advisor's Committee Title

Committee member

Keywords

User Requirements, Use Case, User Story, Model to Model, Natural Language processing, Model Driven Software Engineering, Atlas Transformation Language, Test Case

Date of Defense

3-23-2023

Abstract

Testing continues to be the main approach to ensuring software quality during development. Although there have been many attempts to automate the generation of test cases from user requirements (formal or informal), creating test cases continues to be mainly a manual process. However, many studies have shown that automating the generation of test cases from requirements can substantially reduce costs and improve the efficiency of the testing process. Test automation has also proven to show positive effects on software quality. With the advances in Model-driven Software Engineering (MDSE), Artificial Intelligence (AI), and Natural Language Processing (NLP), the possibility of further automating the generation of test cases from requirements is increasing.

We present an automated test case generation approach that uses a model-to-model (M2M) transformation that converts user requirements into test cases with the support of a knowledge base and NLP. The key to this transformation process is defining meta-models for user requirements (use cases and user stories) and test cases. The proposed M2M transformation is composed of three phases. Phase 1 includes creating Enhanced User Requirement Models (EURMs) from user requirements using NLP analysis and an application-specific data model. Phase 2 involves transforming EURMs to Abstract test Cases (ATCs) using the transformation rules defined between EUR and user requirements meta-models. Phase 3 consists of generating concrete test cases from ATCs and an application-specific data model instance. To validate each phase of the transformation process, case studies were conducted using a tool developed to evaluate the feasibility and accuracy of converting user requirements to test cases.

Identifier

FIDC011064

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