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Mutation Operators for Large Scale Data Processing Programs in Spark

This paper proposes a mutation testing approach for big data processing programs that follow a data flow model, such as those implemented on top of Apache Spark. Mutation testing is a fault-based technique that relies on fault simulation by modifying programs, to create faulty versions called mutant...

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Detalles Bibliográficos
Autores principales: de Souza Neto, João Batista, Martins Moreira, Anamaria, Vargas-Solar, Genoveva, Musicante, Martin Alejandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266460/
http://dx.doi.org/10.1007/978-3-030-49435-3_30
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author de Souza Neto, João Batista
Martins Moreira, Anamaria
Vargas-Solar, Genoveva
Musicante, Martin Alejandro
author_facet de Souza Neto, João Batista
Martins Moreira, Anamaria
Vargas-Solar, Genoveva
Musicante, Martin Alejandro
author_sort de Souza Neto, João Batista
collection PubMed
description This paper proposes a mutation testing approach for big data processing programs that follow a data flow model, such as those implemented on top of Apache Spark. Mutation testing is a fault-based technique that relies on fault simulation by modifying programs, to create faulty versions called mutants. Mutant creation is carried on by operators able to simulate specific and well identified faults. A testing process must be able to signal faults within mutants and thereby avoid having ill behaviours within a program. We propose a set of mutation operators designed for Spark programs characterized by a data flow and data processing operations. These operators model changes in the data flow and operations, to simulate faults that take into account Spark program characteristics. We performed manual experiments to evaluate the proposed mutation operators in terms of cost and effectiveness. Thereby, we show that mutation operators can contribute to the testing process, in the construction of reliable Spark programs.
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spelling pubmed-72664602020-06-03 Mutation Operators for Large Scale Data Processing Programs in Spark de Souza Neto, João Batista Martins Moreira, Anamaria Vargas-Solar, Genoveva Musicante, Martin Alejandro Advanced Information Systems Engineering Article This paper proposes a mutation testing approach for big data processing programs that follow a data flow model, such as those implemented on top of Apache Spark. Mutation testing is a fault-based technique that relies on fault simulation by modifying programs, to create faulty versions called mutants. Mutant creation is carried on by operators able to simulate specific and well identified faults. A testing process must be able to signal faults within mutants and thereby avoid having ill behaviours within a program. We propose a set of mutation operators designed for Spark programs characterized by a data flow and data processing operations. These operators model changes in the data flow and operations, to simulate faults that take into account Spark program characteristics. We performed manual experiments to evaluate the proposed mutation operators in terms of cost and effectiveness. Thereby, we show that mutation operators can contribute to the testing process, in the construction of reliable Spark programs. 2020-05-30 /pmc/articles/PMC7266460/ http://dx.doi.org/10.1007/978-3-030-49435-3_30 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
de Souza Neto, João Batista
Martins Moreira, Anamaria
Vargas-Solar, Genoveva
Musicante, Martin Alejandro
Mutation Operators for Large Scale Data Processing Programs in Spark
title Mutation Operators for Large Scale Data Processing Programs in Spark
title_full Mutation Operators for Large Scale Data Processing Programs in Spark
title_fullStr Mutation Operators for Large Scale Data Processing Programs in Spark
title_full_unstemmed Mutation Operators for Large Scale Data Processing Programs in Spark
title_short Mutation Operators for Large Scale Data Processing Programs in Spark
title_sort mutation operators for large scale data processing programs in spark
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266460/
http://dx.doi.org/10.1007/978-3-030-49435-3_30
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