Rethinking Software Engineering in the Foundation Model Era: From Task-Driven AI Copilots to Goal-Driven AI Pair Programmers
Ahmed E. Hassan, Gustavo A. Oliva, Dayi Lin, Boyuan Chen, Zhen Ming, (Jack) Jiang

TL;DR
This paper advocates for a paradigm shift in software engineering from task-driven AI copilots to goal-driven AI pair programmers that collaborate holistically with humans, aiming to improve productivity and software quality.
Contribution
It introduces the concept of goal-driven AI pair programmers, emphasizing their attributes and the challenges to transition from current task-driven copilots.
Findings
Proposes a new paradigm for AI in SE focusing on goals and collaboration.
Highlights key attributes needed for effective AI pair programmers.
Discusses challenges and future directions for goal-driven AI in SE.
Abstract
The advent of Foundation Models (FMs) and AI-powered copilots has transformed the landscape of software development, offering unprecedented code completion capabilities and enhancing developer productivity. However, the current task-driven nature of these copilots falls short in addressing the broader goals and complexities inherent in software engineering (SE). In this paper, we propose a paradigm shift towards goal-driven AI-powered pair programmers that collaborate with human developers in a more holistic and context-aware manner. We envision AI pair programmers that are goal-driven, human partners, SE-aware, and self-learning. These AI partners engage in iterative, conversation-driven development processes, aligning closely with human goals and facilitating informed decision-making. We discuss the desired attributes of such AI pair programmers and outline key challenges that must be…
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Taxonomy
TopicsScientific Computing and Data Management · Cloud Computing and Resource Management · Software System Performance and Reliability
