Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

From Logic to Toolchains: An Empirical Study of Bugs in the TypeScript Ecosystem

TianYi Tang, Saba Alimadadi, Nick Sumner

TL;DR

The paper investigates faults in the TypeScript ecosystem through a large-scale empirical study of 633 bug-related artifacts from 16 open-source projects. It builds an empirically grounded taxonomy of 11 bug categories, combining manual labeling with a few-shot embedding model, and links fault types to project attributes and build-system complexity using non-parametric statistics. A longitudinal comparison with JavaScript suggests that static typing reduces runtime and type-errors but shifts fragility toward toolchains, configuration, and asynchronous integration issues. The work provides a public dataset and analysis pipeline, highlighting ecosystem-level reliability challenges and offering guidance for testing, debugging, and tooling improvements in typed web development.

Abstract

TypeScript has rapidly become a popular language for modern web development, yet its effect on software faults remains poorly understood. This paper presents the first large-scale empirical study of bugs in real-world TypeScript projects. We analyze 633 bug reports from 16 popular open-source repositories to construct a taxonomy of fault types, quantify their prevalence, and relate them to project characteristics such as size, domain, and dependency composition. Our results reveal a fault landscape dominated not by logic or syntax errors but by tooling and configuration faults, API misuses, and asynchronous error-handling issues. We show that these categories correlate strongly with build complexity and dependency heterogeneity, indicating that modern failures often arise at integration and orchestration boundaries rather than within algorithmic logic. A longitudinal comparison with JavaScript studies shows that while static typing in TypeScript has reduced traditional runtime and type errors, it has shifted fragility toward build systems and toolchains. These findings offer new insight into how language design and ecosystem evolution reshape the fault profiles of large-scale software systems.

From Logic to Toolchains: An Empirical Study of Bugs in the TypeScript Ecosystem

TL;DR

The paper investigates faults in the TypeScript ecosystem through a large-scale empirical study of 633 bug-related artifacts from 16 open-source projects. It builds an empirically grounded taxonomy of 11 bug categories, combining manual labeling with a few-shot embedding model, and links fault types to project attributes and build-system complexity using non-parametric statistics. A longitudinal comparison with JavaScript suggests that static typing reduces runtime and type-errors but shifts fragility toward toolchains, configuration, and asynchronous integration issues. The work provides a public dataset and analysis pipeline, highlighting ecosystem-level reliability challenges and offering guidance for testing, debugging, and tooling improvements in typed web development.

Abstract

TypeScript has rapidly become a popular language for modern web development, yet its effect on software faults remains poorly understood. This paper presents the first large-scale empirical study of bugs in real-world TypeScript projects. We analyze 633 bug reports from 16 popular open-source repositories to construct a taxonomy of fault types, quantify their prevalence, and relate them to project characteristics such as size, domain, and dependency composition. Our results reveal a fault landscape dominated not by logic or syntax errors but by tooling and configuration faults, API misuses, and asynchronous error-handling issues. We show that these categories correlate strongly with build complexity and dependency heterogeneity, indicating that modern failures often arise at integration and orchestration boundaries rather than within algorithmic logic. A longitudinal comparison with JavaScript studies shows that while static typing in TypeScript has reduced traditional runtime and type errors, it has shifted fragility toward build systems and toolchains. These findings offer new insight into how language design and ecosystem evolution reshape the fault profiles of large-scale software systems.
Paper Structure (57 sections, 5 figures, 3 tables)

This paper contains 57 sections, 5 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Study Design and Methodology
  3. Research Questions
  4. Dataset Construction and Project Selection
  5. Bug collection and filtering.
  6. Labeling pipeline.
  7. Taxonomy Development
  8. Quantitative Analyses
  9. Historical Comparison RQ3
  10. Category mapping.
  11. Prevalence comparison.
  12. Reliability and Validity
  13. RQ1: Categories and Prevalence of Bugs
  14. Bug Categories
  15. Asynchrony / Event.
  16. ...and 42 more sections

Figures (5)

  • Figure 1: Bug category distributions across and within projects. Top: Overall prevalence of each bug category across all analyzed Type-Script projects, with stacked segments showing per-project contributions. Bottom: Normalized distribution of bug categories within each project, showing the relative composition of fault types across systems.
  • Figure 2: Project attributes and bug categories correlations.
  • Figure 3: Standardized (z-scored) median frequency of each bug category per domain, showing relative over- or underrepresentation across domains.
  • Figure 4: Correlation heatmap among bug categories. Colour represents the strength and direction of correlations ($\rho$).
  • Figure 5: Correlations between dependency categories and bug types. Colour shows correlation strength and direction.