Abstract:
Large Language Models have emerged rapidly as powerful coding tools, in some cases showing the ability to create entire working programs, and (more commonly) providing help with the details of a great many APIs and frameworks. This emergence raises a number of questions for the PPIG community. Will these tools change what programmers do, in ways that affect "the psychology of programming"? Given the (apparent) command that these systems have of natural language, and of the semantics of a great many domains of activity, can they be used to enhance the kinds of interactions with software tools that PPIG researchers have studied? Noting that large language models exhibit analogical reasoning as an emergent capability, can they leverage insights from early research on programming by analogy? Does predictive modelling, as a key cognitive process that can be applied in many domains, suggest new ways to think about programming not based on text?
PPIG 2023 - 34th Annual Workshop
Large Language Models and the Psychology of Programming