A series of articles to interviewing ESE practitioners from various companies to understand how ESE processes are implemented in industry, e.g, how practitioners decide on what to study, how research results are used within companies and beyond.
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.
This research will focus on empirically examining the software testing criteria undertaken by SMEs in India and its effect on quality indicators, which are defect density, customer-reported defects, and time-to-market.
Priya Nandihal· Journal of Intelligent Decis...· 0 citations
User Stories are key artifacts in Requirement and Software Engineering. Despite their wide adoption, their writing in industrial contexts tends to diverge from the principles initially stated in Agile methodologies. In this context, sets of metrics such as INVEST or QUS emerged to qualify these items. In this paper, we...
M. Ortega, Hassan Imhah, N. Mellouli et al.· Proceedings of the ACM on So...· 0 citations
Despite the rapid adoption of Large Language Models in professional software engineering, limited research has investigated how early career professionals develop effective AI assisted work practices during their transition into industry. We report findings from a mixed methods survey with 75 novice software engineers...
Julia Alencar, R. E. de Souza Santos, Ítalo Santos et al.· 0 citations
Large Language Models (LLMs) are increasingly used in software development and are becoming part of software engineering education. However, there is limited empirical evidence on how students use AI tools across development tasks in project-based Software Engineering courses. This paper presents an empirical study bas...
Christos Hadjichristofi, Dimitrios-Triantafyllos Gerokonstantis, P. Papadeas et al.· Conference on Computer Scien...· 0 citations
Artificial intelligence is likely the largest disruptor to the discipline of software engineering since third and fourth generation languages arrived and we have all heard the stories of its impact. Productivity increases of more than 100x, faster delivery and reduced workforces, but also drops in quality, shifts in co...
J. Noppen· Proceedings of the 41st IEEE...· 0 citations
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