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Software design analysis and technical debt management based on design rule theory
Journal article   Open access   Peer reviewed

Software design analysis and technical debt management based on design rule theory

Yuanfang Cai and Rick Kazman
Information and software technology, v 164, 107322
Dec 2023
DOI: https://doi.org/10.1016/j.infsof.2023.107322
url
https://doi.org/10.1016/j.infsof.2023.107322View
Accepted (AM)Open Access (License Unspecified),  Open

Abstract

Automated analysis Design debt Industrial case studies Software architecture Software design
In this paper we reflect on our decade-long journey of creating, evolving, and evaluating a number of software design concepts and technical debt management technologies. These include: a novel maintainability metric, a new model for representing design information, a suite of design anti-patterns, and a formalized model of design debt. All of these concepts are rooted in options theory, and they all share the objective of helping a software project team quantify and visualize major design principles, and address the very real maintainability challenges faced by their organizations in practice. The evolution of our research has been propelled by our continuous interactions with industrial collaborators. For each concept, technology, and supporting tool, we embarked on an ambitious program of empirical validation—in “the lab”, with industry partners, and with open source projects. We reflect on the successes of this research and on areas where significant challenges remain. In particular, we observe that improved software design education, both for students and professional developers, is the prerequisite for our research and technology to be widely adopted. During this journey, we also observed a number of gaps: between what we offer in research and what practitioners need, between management and development, and between debt detection and debt reduction. Addressing these challenges motivates our research moving forward.

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3 citations in Web of Science
1 citations in Scopus

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Collaboration types
Domestic collaboration
Web of Science research areas
Computer Science, Information Systems
Computer Science, Software Engineering
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