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ING Bank, a large Netherlands-based internationally operating bank, implemented a fully automated continuous delivery pipeline for its software engineering activities in more than 300 teams, that perform more than 2500 deployments to production each month on more than 750 different applications. Our objective is to examine how strong metrics for agile (Scrum) DevOps teams can be set in an iterative fashion. We perform an exploratory case study that focuses on the classification based on predictive power of software metrics, in which we analyze log data derived from two initial sources within this pipeline. We analyzed a subset of 16 metrics from 59 squads. We identified two lagging metrics and assessed four leading metrics to be strong.
Original languageEnglish
Number of pages10
StatePublished - Sep 2017
EventESEC/FSE 2017 -

Conference

ConferenceESEC/FSE 2017
Abbreviated titleESEC/FSE 2017
Period4/09/178/09/17
Internet address

    Research areas

  • Software Economics, Agile Metrics, Scrum, Continuous Delivery, Prediction Modelling, DevOps, Data Mining, Software Analytics

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