Adopting Automated Bug Assignment in Practice - A Longitudinal Case Study at Ericsson
This program is tentative and subject to change.
[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 April 2019. [Objective] Our study evaluates the adoption of TRR within its industrial context at Ericsson, i.e., we provide lessons learned related to the productization of a research prototype within a company. Moreover, we investigate 1) how TRR performs in the field, 2) what value TRR provides to Ericsson, and 3) how TRR has influenced the ways of working. [Method] We conduct a preregistered industrial case study combining interviews with TRR stakeholders, minutes from sprint planning meetings, and bug-tracking data. The data analysis includes thematic analysis, descriptive statistics, and Bayesian causal analysis. [Results] TRR is now an incorporated part of the bug assignment process. Considering the abstraction levels of the telecommunications stack, high-level modules are more positive while low-level modules experienced some drawbacks. Most importantly, some bug reports directly reach low-level modules without first having passed through fundamental root-cause analysis steps at higher levels. On average, TRR automatically assigns 30% of the incoming bug reports with an accuracy of 75%. Auto-routed TRs are resolved around 21% faster within Ericsson, and TRR has saved highly seasoned engineers many hours of work. Indirect effects of adopting TRR include process improvements, process awareness, increased communication, and higher job satisfaction. [Conclusions] TRR has saved time at Ericsson, but the adoption of automated bug assignment was more intricate compared to similar endeavors reported from other companies. We primarily attribute the difference to the very large size of the organization and the complex products. Key facilitators in the successful adoption include a gradual introduction, product champions, and careful stakeholder analysis.
This program is tentative and subject to change.
Wed 30 AprDisplayed time zone: Eastern Time (US & Canada) change
11:00 - 12:30 | |||
11:00 15mTalk | Critical Variable State-Aware Directed Greybox Fuzzing Research Track Xu Chen Institute of Information Engineering at Chinese Academy of Sciences, China / University of Chinese Academy of Sciences, China, Ningning Cui Institute of Information Engineering at Chinese Academy of Sciences, China / University of Chinese Academy of Sciences, China, Zhe Pan Institute of Information Engineering at Chinese Academy of Sciences, China / University of Chinese Academy of Sciences, China, Liwei Chen Institute of Information Engineering at Chinese Academy of Sciences; University of Chinese Academy of Sciences, Gang Shi Institute of Information Engineering at Chinese Academy of Sciences; University of Chinese Academy of Sciences, Dan Meng Institute of Information Engineering at Chinese Academy of Sciences; University of Chinese Academy of Sciences | ||
11:15 15mTalk | LWDIFF: An LLM-Assisted Differential Testing Framework for WebAssembly Runtimes Research Track Shiyao Zhou The Hong Kong Polytechnic University, Jincheng Wang Hong Kong Polytechnic University, He Ye Carnegie Mellon University, Hao Zhou The Hong Kong Polytechnic University, Claire Le Goues Carnegie Mellon University, Xiapu Luo Hong Kong Polytechnic University | ||
11:30 15mTalk | No Harness, No Problem: Oracle-guided Harnessing for Auto-generating C API Fuzzing Harnesses Research Track | ||
11:45 15mTalk | Parametric Falsification of Many Probabilistic Requirements under Flakiness Research Track | ||
12:00 15mTalk | REDII: Test Infrastructure to Enable Deterministic Reproduction of Failures for Distributed Systems Research Track Yang Feng Nanjing University, Zheyuan Lin Nanjing University, Dongchen Zhao Nanjing University, Mengbo Zhou Nanjing University, Jia Liu Nanjing University, James Jones University of California at Irvine | ||
12:15 15mTalk | Adopting Automated Bug Assignment in Practice - A Longitudinal Case Study at Ericsson Journal-first Papers Markus Borg CodeScene, Leif Jonsson Ericsson AB, Emelie Engstrom Lund University, Béla Bartalos Verint, Attila Szabo Ericsson | ||