Bridging Incremental Programming and Complex Software Development Environments

Abstract

In modern software development, programmers typically choose between two main types of coding environments: Incremental Programming Environments (IPEs), such as the Read-Eval-Print-Loop (REPL) interpreter IPython and the Jupyter Computational Notebook, and Integrated (text-based) Development Environments (IDEs), such as Visual Studio Code. IPEs excel in providing immediate feedback for iterative development, testing, and debugging, making them ideal for fields like data science and AI. However, their typically linear and isolated interface struggles with managing the complexity of larger software projects. Conversely, traditional IDEs support extensive project management and debugging tools suited for complex applications but lack the interactive and incremental nature of IPEs. This paper reports on an ongoing investigation and design of a hybrid environment that combines benefits of IPEs and IDEs and the programming styles they naturally support. Central to our design is a graph structure representing code fragments as nodes and code structure as edges. By considering various types of nodes and relationships (e.g. for representing class membership, execution order, documentation, and dependencies) we can facilitate aspects of both incremental programming (in IPEs) and complexity management (in IDEs). We demonstrate our approach with a prototype, called Incremental Graph Code (IGC), by presenting its architecture and a showcase. We demonstrate IGC’s functionality and discuss its potential advantages over existing environments. Key features include advanced code visualization, modular and incremental development, and complexity management. IGC aims to provide a unified, extensible, and flexible development environment that bridges the gap between different styles of programming.