CoLadder: Manipulating Code Generation via Multi-Level Blocks
Ryan Yen, J. Zhu, Sangho Suh, Haijun Xia, Jian Zhao
Abstract
This paper adopted an iterative design process to gain insights into programmers’ strategies when using LLMs for programming. We proposed CoLadder, a novel system that supports programmers by facilitating hierarchical task decomposition, direct code segment manipulation, and result evaluation during prompt authoring. A user study with 12 experienced programmers showed that CoLadder is effective in helping programmers externalize their problem-solving intentions flexibly, improving their ability to evaluate and modify code across various abstraction levels, from their task’s goal to final code implementation.
Topics & Concepts
Computer scienceCode (set theory)Code generationProgramming languageParallel computingOperating systemKey (lock)Set (abstract data type)E-Learning and Knowledge ManagementModel-Driven Software Engineering TechniquesOpen Education and E-Learning