Summary of the 1st Natural Language-based Software Engineering Workshop (NLBSE 2022)

Abstract

Natural language processing (NLP) refers to automatic computa- tional processing of human language, including both algorithms that take human-produced text as input and algorithms that pro- duce natural-looking text as outputs. There is a widespread and growing usage of NLP approaches to optimize many aspects of the development process of software systems. In particular, since natural language artifacts are used and reused during the software development lifecycle, the availability of natural language-based approaches and tools enabled the envisioning of methods for im- proving efficiency in software engineers, processes, and products. The research community has been discussing these approaches in the 1st edition of the Natural Language-Based Software Engineer- ing Workshop (NLBSE), collocated with ICSE (the International Conference on Software Engineering) in 2022. This event brought together researchers and industrial practitioners from NLP and the software engineering community to share experiences, pro- vide directions for future research, and encourage the usage of NLP techniques and tools for addressing software engineering- speci c challenges. In this paper, we present a summary of the 1st edition of the workshop, which comprised ve full papers, four short/position papers, ve tool competition/demonstration pa- pers, one keynote (\Deep Learning & Software Engineering: Past, Present and Future"by Denys Poshyvanyk), followed by extensive discussion among NLBSE participants. More details can be found at https://nlbse2022.github.io/index.html