A Collection of Software Engineering Challenges for Big Data System Development

In recent years, the development of systems for processing and analyzing large amounts of data (so-called Big Data) has become an important sub-discipline of software engineering. However, to date there exits no comprehensive summary of the specific idiosyncrasies and challenges that the development...

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Published in2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) pp. 362 - 369
Main Authors Hummel, Oliver, Eichelberger, Holger, Giloj, Andreas, Werle, Dominik, Schmid, Klaus
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2018
Subjects
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DOI10.1109/SEAA.2018.00066

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Abstract In recent years, the development of systems for processing and analyzing large amounts of data (so-called Big Data) has become an important sub-discipline of software engineering. However, to date there exits no comprehensive summary of the specific idiosyncrasies and challenges that the development of Big Data systems imposes on software engineers. With this paper, we aim to provide a first step towards filling this gap based on our collective experience from industry and academic projects as well as from consulting and initial literature reviews. The main contribution of our work is a concise summary of 26 challenges in engineering Big Data systems, collected and consolidated by means of a systematic identification process. The aim is to make practitioners more aware of common challenges and to offer researchers a solid baseline for identifying novel software engineering research directions.
AbstractList In recent years, the development of systems for processing and analyzing large amounts of data (so-called Big Data) has become an important sub-discipline of software engineering. However, to date there exits no comprehensive summary of the specific idiosyncrasies and challenges that the development of Big Data systems imposes on software engineers. With this paper, we aim to provide a first step towards filling this gap based on our collective experience from industry and academic projects as well as from consulting and initial literature reviews. The main contribution of our work is a concise summary of 26 challenges in engineering Big Data systems, collected and consolidated by means of a systematic identification process. The aim is to make practitioners more aware of common challenges and to offer researchers a solid baseline for identifying novel software engineering research directions.
Author Schmid, Klaus
Hummel, Oliver
Eichelberger, Holger
Werle, Dominik
Giloj, Andreas
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Snippet In recent years, the development of systems for processing and analyzing large amounts of data (so-called Big Data) has become an important sub-discipline of...
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StartPage 362
SubjectTerms Big Data
Challenges
Computer architecture
Data analysis
Data privacy
Software
Software Development
Software engineering
Systematics
Title A Collection of Software Engineering Challenges for Big Data System Development
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