Software Engineering for Big Data Systems

Software engineering for big data systems is complex and faces challenges including pervasive distribution, write-heavy workloads, variable request loads, computation-intensive analytics, and high availability. The articles in this theme issue examine several facets of this complicated puzzle. The W...

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Bibliographic Details
Published inIEEE software Vol. 33; no. 2; pp. 32 - 35
Main Authors Gorton, Ian, Bener, Ayse Basar, Mockus, Audris
Format Journal Article
LanguageEnglish
Published IEEE 01.03.2016
Subjects
Availability
big data
Computer programs
data analytics
Data management
online video processing
operational-log analysis
Recording
Software
software development
Software engineering
strategic prototyping
Stress concentration
Workload
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Summary:Software engineering for big data systems is complex and faces challenges including pervasive distribution, write-heavy workloads, variable request loads, computation-intensive analytics, and high availability. The articles in this theme issue examine several facets of this complicated puzzle. The Web extra at https://youtu.be/YKBGf9EOBUo is an audio recording of Davide Falessi speaking with Ayse Basar Bener and Audris Mockus about the authors, articles, and discussions that went into the IEEE Software March/April 2016 theme issue on software engineering for big data systems.
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SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0740-7459
1937-4194
DOI:10.1109/MS.2016.47