Abstraction Engineering

TL;DR

This paper advocates for Abstraction Engineering as a systematic approach to enhance software development across disciplines, addressing new challenges posed by adaptive, AI-driven, and diverse developer communities.

Contribution

It introduces the concept of Abstraction Engineering, outlining its foundations, challenges, research questions, and a future research roadmap for software engineering.

Findings

Highlights the importance of abstraction in diverse software development contexts

Identifies key challenges in applying abstraction systematically

Proposes a research roadmap for Abstraction Engineering

Abstract

Modern software-based systems operate under rapidly changing conditions and face ever-increasing uncertainty. In response, systems are increasingly adaptive and reliant on artificial-intelligence methods. In addition to the ubiquity of software with respect to users and application areas (e.g., transportation, smart grids, medicine, etc.), these high-impact software systems necessarily draw from many disciplines for foundational principles, domain expertise, and workflows. Recent progress with lowering the barrier to entry for coding has led to a broader community of developers, who are not necessarily software engineers. As such, the field of software engineering needs to adapt accordingly and offer new methods to systematically develop high-quality software systems by a broad range of experts and non-experts. This paper looks at these new challenges and proposes to address them through the lens of Abstraction. Abstraction is already used across many disciplines involved in software development -- from the time-honored classical deductive reasoning and formal modeling to the inductive reasoning employed by modern data science. The software engineering of the future requires Abstraction Engineering -- a systematic approach to abstraction across the inductive and deductive spaces. We discuss the foundations of Abstraction Engineering, identify key challenges, highlight the research questions that help address these challenges, and create a roadmap for future research.