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UX Debt: Developers Borrow While Users Pay

Sebastian Baltes, Veronika Dashuber

TL;DR

The paper reframes technical debt by introducing UX debt and classifying it into code-centric, architecture-centric, and process-centric categories, arguing that end users often bear the interest. It combines an exploratory industrial case study with an online practitioner survey to validate the taxonomy, and provides concrete mitigation strategies such as UI-focused static analysis and domain reviews. The work broadens the debt model to include usability impact, emphasizes user workflows, and suggests tooling and visualization approaches to detect and manage UX debt early in development. The findings underscore the importance of integrating UX considerations into software debt discussions to reduce user inefficiency, confusion, and churn, with clear implications for practice and future research.

Abstract

Technical debt has become a well-known metaphor among software professionals, illustrating how shortcuts taken during development can accumulate and become a burden for software projects. In the traditional notion of technical debt, software developers borrow from the maintainability and extensibility of a software system for a short-term speed up in development time. In the future, they are the ones who pay the interest in form of longer development times. User experience (UX) debt, on the other hand, focuses on shortcuts taken to speed up development at the expense of subpar usability, thus mainly borrowing from user efficiency. Most research considers code-centric technical debt, focusing on the implementation. With this article, we want to build awareness for the often overlooked UX debt of software systems, shifting the focus from the source code towards users. We outline three classes of UX debt that we observed in practice: code-centric, architecture-centric, and process-centric UX debt. In an expert survey, we validated those classes, with code-centric and process-centric UX debt getting the strongest support. We discuss our participants' feedback and present recommendations on how software development teams can mitigate UX debt in their user-facing applications.

UX Debt: Developers Borrow While Users Pay

TL;DR

The paper reframes technical debt by introducing UX debt and classifying it into code-centric, architecture-centric, and process-centric categories, arguing that end users often bear the interest. It combines an exploratory industrial case study with an online practitioner survey to validate the taxonomy, and provides concrete mitigation strategies such as UI-focused static analysis and domain reviews. The work broadens the debt model to include usability impact, emphasizes user workflows, and suggests tooling and visualization approaches to detect and manage UX debt early in development. The findings underscore the importance of integrating UX considerations into software debt discussions to reduce user inefficiency, confusion, and churn, with clear implications for practice and future research.

Abstract

Technical debt has become a well-known metaphor among software professionals, illustrating how shortcuts taken during development can accumulate and become a burden for software projects. In the traditional notion of technical debt, software developers borrow from the maintainability and extensibility of a software system for a short-term speed up in development time. In the future, they are the ones who pay the interest in form of longer development times. User experience (UX) debt, on the other hand, focuses on shortcuts taken to speed up development at the expense of subpar usability, thus mainly borrowing from user efficiency. Most research considers code-centric technical debt, focusing on the implementation. With this article, we want to build awareness for the often overlooked UX debt of software systems, shifting the focus from the source code towards users. We outline three classes of UX debt that we observed in practice: code-centric, architecture-centric, and process-centric UX debt. In an expert survey, we validated those classes, with code-centric and process-centric UX debt getting the strongest support. We discuss our participants' feedback and present recommendations on how software development teams can mitigate UX debt in their user-facing applications.

Paper Structure

This paper contains 9 sections, 2 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. Methodology
  4. Case Study
  5. Code-centric UX Debt
  6. Architecture-centric UX Debt
  7. Process-centric UX Debt
  8. Online Survey
  9. Conclusion

Figures (2)

  • Figure 1: Initial framework of UX debt classes and indicated changes according to our survey feedback.
  • Figure 2: Bar charts show number of participants who observed the corresponding UX debt classes in practice ($n=21$); box plots show participants' ratings for who's primarily paying the debt in the different UX debt classes ($n=21$).