Sbir phase i: value-driven design debt management for contemporary software systems

This National Science Foundation (NSF) Small Business Innovation Research (SBIR) Phase I Project Grant, awarded under the NSF Technology, Innovation, and Partnerships program (CFDA 47.084), provides $274,894 to Archdia Inc. to develop a value-driven design debt management system for modern distributed software systems. The one-year project beginning May 1, 2023 will design a framework to discover, quantify, and prioritize design debt using techniques like options theory and knowledge graphs. The system will recommend effective debt reduction strategies and allow managers to simulate refactoring outcomes and evaluate economic implications. If successful, this research could fundamentally change how organizations manage technical debt at the design level for distributed systems and lead to the first framework specialized for this purpose based on financial and design principles.

Abstract

The broader impact/commercial potential of this small business innovation research (sbir) phase i project will design a value-driven design debt management system applicable to modern, distributed, dynamic software systems. This system will pinpoint and quantify design debt and recommend the most e?ective debt-reduction strategies. This system will also support risk analyses for managers and designers, helping them choose a strategy that prevents severe decay in product performance, and maximize product value, productivity, and quality. This small business innovation research (sbir) phase i project provide a value-driven, design-debt management system that (1) discovers and empirically validates design debt in modern distributed and dynamically-typed software systems based on options theory, conway's law, and design principles, leveraging a knowledge graph to capture and manage implicit, heterogeneous, and distributed entities and relations; (2) discovers the intrinsic and implicit relations among multiple design anti-patterns and creates an algorithm to prioritize and recommend the most effective debt-reduction strategies; and (3) bridges the GAP between development and management, enabling a user to simulate refactoring outcomes and evaluate their economic implications by combining monte carlo simulation and datar-mathews option valuations, for each proposed refactoring strategy. The outcome of these research and development activities will lead to the first framework specialized for managing technical debt at the design and architecture level, rooted in financial and design theory, and applicable to modern distributed and dynamically typed software systems. This project has the potential to fundamentally change the management of software, supporting better informed, data driven decisions by focusing on their economic values. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.