  [Background/Context] The continuous inflow of bug reports is a considerable
challenge in large development projects. Inspired by contemporary work on
mining software repositories, we designed a prototype bug assignment solution
based on machine learning in 2011-2016. The prototype evolved into an internal
Ericsson product, TRR, in 2017-2018. TRR's first bug assignment without human
intervention happened in 2019. [Objective/Aim] Our exploratory study will
evaluate the adoption of TRR within its industrial context at Ericsson. We seek
to understand 1) how TRR performs in the field, 2) what value TRR provides to
Ericsson, and 3) how TRR has influenced the ways of working. Secondly, we will
provide lessons learned related to productization of a research prototype
within a company. [Method] We design an industrial case study combining
interviews with TRR developers and users with analysis of data extracted from
the bug tracking system at Ericsson. Furthermore, we will analyze sprint
planning meetings recorded during the productization. Our data analysis will
include thematic analysis, descriptive statistics, and Bayesian causal
analysis.
