Skip to main content
Kent Academic Repository

Model extraction and test generation from JUnit test suites

Seijas, Pablo Lamela and Thompson, Simon and Francisco, Miguel Ángel (2016) Model extraction and test generation from JUnit test suites. In: Proceedings of the 11th International Workshop on Automation of Software Test. ICSE International Conference on Software Engineering . ACM, New York, USA, pp. 8-14. ISBN 978-1-4503-4151-6. (doi:10.1145/2896921.2896927) (KAR id:55751)

Abstract

In this paper we describe how to infer state machine models of systems from legacy unit test suites, and how to generate new tests from those models. The novelty of our approach is to combine control dependencies and data dependencies in the same model, in contrast to most other work in this area. Combining both kinds of dependency helps us to build more expressive models, which in turn allows us to produce smarter tests. We illustrate those techniques with examples from our implementation, the James tool, designed to apply these techniques in practice to Java code and tests.

Item Type: Book section
DOI/Identification number: 10.1145/2896921.2896927
Projects: PROWESS
Uncontrolled keywords: model, Unit, Quviq QuickCheck, Erlang, finite state machine, inference, Interoud,VoDKATV, James
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76 Computer software
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Funders: [UNSPECIFIED] European Union
Depositing User: S. Thompson
Date Deposited: 01 Jun 2016 10:01 UTC
Last Modified: 16 Feb 2021 13:35 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/55751 (The current URI for this page, for reference purposes)

University of Kent Author Information

Seijas, Pablo Lamela.

Creator's ORCID:
CReDIT Contributor Roles:

Thompson, Simon.

Creator's ORCID: https://orcid.org/0000-0002-2350-301X
CReDIT Contributor Roles:
  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.