An annotation-based approach for finding bugs in neural network programs-Reference-Cited by-同舟云学术

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An annotation-based approach for finding bugs in neural network programs

Published:2023-07 Issue: Volume:201 Page:111669
ISSN:0164-1212
Container-title:Journal of Systems and Software
language:en
Short-container-title:Journal of Systems and Software

Author:

Rezaalipour Mohammad^ORCID,Furia Carlo A.^ORCID

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Software

Reference46 articles.

1. Automated black-box testing with abstract VDM oracle;Aichernig,1999

2. A systematic review of the application and empirical investigation of search-based test case generation;Ali;IEEE Trans. Softw. Eng.,2010

3. Introduction to Software Testing Edition 2;Ammann,2017

4. An orchestrated survey of methodologies for automated software test case generation;Anand;J. Syst. Softw.,2013

5. Deal: A python library for design by contract;Anon,2018

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An empirical study of fault localization in Python programs;Empirical Software Engineering;2024-06-13

2. aNNoTest: An Annotation-based Test Generation Tool for Neural Network Programs;2023 IEEE International Conference on Software Maintenance and Evolution (ICSME);2023-10-01

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