Verifying big data topologies by-design: a semi-automated approach

Marcello M. Bersani (Corresponding author), Francesco Marconi, Damian A. Tamburri (Corresponding author), Andrea Nodari, Pooyan Jamshidi

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
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Abstract

Big data architectures have been gaining momentum in recent years. For instance, Twitter uses stream processing frameworks like Apache Storm to analyse billions of tweets per minute and learn the trending topics. However, architectures that process big data involve many different components interconnected via semantically different connectors. Such complex architectures make possible refactoring of the applications a difficult task for software architects, as applications might be very different with respect to the initial designs. As an aid to designers and developers, we developed OSTIA (Ordinary Static Topology Inference Analysis) that allows detecting the occurrence of common anti-patterns across big data architectures and exploiting software verification techniques on the elicited architectural models. This paper illustrates OSTIA and evaluates its uses and benefits on three industrial-scale case-studies.

Original languageEnglish
Article number40
Number of pages23
JournalJournal of Big Data
Volume6
Issue number1
DOIs
Publication statusPublished - 18 May 2019

Keywords

  • Big data architectures
  • Big data systems verification
  • Software design and analysis

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