Empirical Software Engineering in Practice: Insights from Google
Roberto Verdecchia, Justus Bogner
Abstract
While it is fairly well known how empirical software engineering (ESE) is used in the academic world, we have limited knowledge of how ESE is practiced in industry. As part of our regular column on empirical software engineering (ACM SIGSOFT SEN-ESE), we want to dedicate a series of articles to interviewing ESE practitioners from various companies. Among other things, we want to understand how ESE processes are implemented in industry, e.g., different research methods, how practitioners decide on what to study, how research results are used within companies and beyond, and if they face recurrent impediments to using ESE methods in industrial contexts. In the first edition of "ESE in Practice", we are joined by Ciera Jaspan and Collin Green from the Developer Intelligence team at Google. This article is a faithful account of our conversation from August 13, 2026, which we edited for our column.
Create a lesson
Related papers
ProgramDistill: From Interactive Web Apps to Verifiable Reference-Guided SWE Tasks
Jeonghye Kim, Minseon Kim, Young Jin Kim et al.
Evaluating the Health of Open-Source Smart City Platforms
Rodrigo Bravo Simões, Fernando Brito e Abreu, Vasco Amaral
From Component Snapshots to Lifecycle Traces: Agent-Based Software Composition Analysis
Chaofan Li, Zhengduo Xue, Chengxiang Li et al.
A Study on the Impact of Natural Language Differences in Prompts on Automatic Code Generation Using LLMs
Haruka Tokumasu, Masanari Kondo, Alexander Serebrenik et al.
A Study of the Reliability of Agentic AI-Generated Programs
Ayesha Shafique, Barton P. MIller, Elisa R. Heymann
Relationally Guided Use Case Modeling with LLMs
Guangyu Wang, Bangqi Li, Ji Wu et al.