A practical, collaborative approach for modeling big data analytics application requirements

Hourieh Khalajzadeh, Andrew Simmons, Mohamed Abdelrazek, John Grundy, John Hosking, Qiang He, Prasanna Ratnakanthan, Adil Zia, Meng Law

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

1 Citation (Scopus)


Data analytics application development introduces many challenges including: New roles not in traditional software engineering practices-e.g. data scientists and data engineers; use of sophisticated machine learning (ML) model-based approaches; uncertainty inherent in the models; interfacing with models to fulfill software functionalities; deploying models at scale and rapid evolution of business goals and data sources. We describe our Big Data Analytics Modeling Languages (BiDaML) toolset to bring all stakeholders around one tool to specify, model and document big data applications. We report on our experience applying BiDaML to three real-world large-scale applications. Our approach successfully supports complex data analytics application development in industrial settings.

Original languageEnglish
Title of host publicationProceedings - 2020 ACM/IEEE 42nd International Conference on Software Engineering
Subtitle of host publicationCompanion Proceedings, ICSE-Companion 2020
EditorsGregg Rothermel, Doo-Hwan Bae
Place of PublicationNew York NY USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages2
ISBN (Electronic)9781450371223
Publication statusPublished - Jun 2020
EventInternational Conference on Software Engineering 2020 - Online, Seoul, Korea, South
Duration: 27 Jun 202019 Jul 2020
Conference number: 42nd
https://dl.acm.org/doi/proceedings/10.1145/3377811 (Proceedings)
https://conf.researchr.org/home/icse-2020 (Website)


ConferenceInternational Conference on Software Engineering 2020
Abbreviated titleICSE 2020
Country/TerritoryKorea, South
Internet address

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