Enhancing Search-based Testing with Testability Transformations for Existing APIs

Author:

Arcuri Andrea1ORCID,Galeotti Juan P.2ORCID

Affiliation:

1. Kristiania University College and Oslo Metropolitan University, Oslo, Norway

2. Depto. de Computación, FCEyN-UBA, and ICC, CONICET-UBA, Argentina

Abstract

Search-based software testing (SBST) has been shown to be an effective technique to generate test cases automatically. Its effectiveness strongly depends on the guidance of the fitness function. Unfortunately, a common issue in SBST is the so-called flag problem , where the fitness landscape presents a plateau that provides no guidance to the search. In this article, we provide a series of novel testability transformations aimed at providing guidance in the context of commonly used API calls (e.g., strings that need to be converted into valid date/time objects). We also provide specific transformations aimed at helping the testing of REST Web Services. We implemented our novel techniques as an extension to EvoMaster , an SBST tool that generates system-level test cases. Experiments on nine open-source REST web services, as well as an industrial web service, show that our novel techniques improve performance significantly.

Funder

European Research Council

UBACYT-2018

Publisher

Association for Computing Machinery (ACM)

Subject

Software

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4. A Systematic Review of the Application and Empirical Investigation of Search-Based Test Case Generation

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