A collection of software engineering challenges for big data system development
O Hummel, H Eichelberger, A Giloj… - 2018 44th Euromicro …, 2018 - ieeexplore.ieee.org
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 …
data (so-called Big Data) has become an important sub-discipline of software engineering …
Composing high-level stream processing pipelines
T Mahapatra - Journal of Big Data, 2020 - Springer
The growing number of Internet of Things (IoT) devices provide a massive pool of sensing
data. However, turning data into actionable insights is not a trivial task, especially in the …
data. However, turning data into actionable insights is not a trivial task, especially in the …
Variability modeling with the integrated variability modeling language (IVML) and EASy-producer
K Schmid, C Kröher, S El-Sharkawy - Proceedings of the 22nd …, 2018 - dl.acm.org
EASy-Producer is an open-source research toolset for engineering product lines, variability-
rich software ecosystems, and dynamic software product lines. In this tutorial, we will focus …
rich software ecosystems, and dynamic software product lines. In this tutorial, we will focus …
Topological feature selection
In this paper, we introduce a novel unsupervised, graph-based filter feature selection
technique which exploits the power of topologically constrained network representations …
technique which exploits the power of topologically constrained network representations …
Graphical flow-based spark programming
T Mahapatra, C Prehofer - Journal of Big Data, 2020 - Springer
Increased sensing data in the context of the Internet of Things (IoT) necessitates data
analytics. It is challenging to write applications for Big Data systems due to complex, highly …
analytics. It is challenging to write applications for Big Data systems due to complex, highly …
High-level graphical programming for Big Data applications
T Mahapatra - 2019 - mediatum.ub.tum.de
The thesis aims to reduce the complexity of writing Big Data applications via domain specific
graphical tools following the flow-based programming paradigm. The graphical …
graphical tools following the flow-based programming paradigm. The graphical …
Dataclouddsl: Textual and visual presentation of big data pipelines
S Tahmasebi, A Layegh, N Nikolov… - 2022 IEEE 46th …, 2022 - ieeexplore.ieee.org
This paper describes the DATACLOUDDSL language and the DEF-PIPE tool for describing
Big Data pipelines. DAT-ACLOUDDSL has both a textual and a visual form and supports …
Big Data pipelines. DAT-ACLOUDDSL has both a textual and a visual form and supports …
[HTML][HTML] aFlux: Graphical flow-based data analytics
T Mahapatra, C Prehofer - Software Impacts, 2019 - Elsevier
Abstract aFlux is a graphical flow-based programming tool designed to support the
modelling of data analytics applications. It supports high-level programming of Big Data …
modelling of data analytics applications. It supports high-level programming of Big Data …
Variability modeling with easy-producer
K Schmid, H Eichelberger - … of the 21st International Systems and …, 2017 - dl.acm.org
EASy-Producer is an open-source research toolset for engineering product lines, variability-
rich software ecosystems, and dynamic software product lines. In this tutorial, we will focus …
rich software ecosystems, and dynamic software product lines. In this tutorial, we will focus …
Feasibility Study of Software Engineering Aspects of Bigdata Analytics Applications for Academicians
Aim of the work is to find research scope specifically for academicians with little or no big
data application development knowledge. Observation made are based on research …
data application development knowledge. Observation made are based on research …