Swinburne
Browse
- No file added yet -

Path-directed source test case generation and prioritization in metamorphic testing

Download (533.31 kB)
journal contribution
posted on 2024-07-11, 14:57 authored by Chang-ai Sun, Baoli Liu, An Fu, Yiqiang Liu, Huai LiuHuai Liu
Metamorphic testing is a technique that makes use of some necessary properties of the software under test, termed as metamorphic relations, to construct new test cases, namely follow-up test cases, based on some existing test cases, namely source test cases. Due to the ability of verifying testing results without the need of test oracles, it has been widely used in many application domains and detected lots of real-life faults. Numerous investigations have been conducted to further improve the effectiveness of metamorphic testing, most of which were focused on the identification and selection of “good” metamorphic relations. Recently, a few studies emerged on the research direction of how to generate and select source test cases that are effective in fault detection. In this paper, we propose a novel approach to generating source test cases based on their associated path constraints, which are obtained through symbolic execution. The path distance among test cases is leveraged to guide the prioritization of source test cases, which further improve the efficiency. A tool has been developed to automate the proposed approach as much as possible. Empirical studies have also been conducted to evaluate the fault-detection effectiveness of the approach. The results show that this approach enhances both the performance and automation of metamorphic testing. It also highlights interesting research directions for further improving metamorphic testing.

Funding

ARC | DP210102447

Context-aware verification and validation framework for autonomous driving : Australian Research Council (ARC) | DP210102447

History

Available versions

PDF (Accepted manuscript)

ISSN

0164-1212

Journal title

Journal of Systems and Software

Volume

183

Article number

111091

Pagination

111091-

Publisher

Elsevier BV

Copyright statement

Copyright © 2021 the author(s). This final, peer reviewed author's accepted manuscript is licensed under Attribution-NonCommercial-NoDerivatives 4.0 International. See https://creativecommons.org/licenses/by-nc-nd/4.0/.

Language

eng

Usage metrics

    Publications

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC