Tootfinder

Establishing Technical Debt Management -- A Five-Step Workshop Approach and an Action Research Study
Marion Wiese, Kamila Serwa, Anastasia Besier, Ariane S. Marion-Jetten, Eva Bittner
https://arxiv.org/abs/2508.15570

Establishing Technical Debt Management -- A Five-Step Workshop Approach and an Action Research Study
Context. Technical debt (TD) items are constructs in a software system providing short-term benefits but hindering future changes. TD management (TDM) is frequently researched but rarely adopted in practice. Goal. This study aimed to establish a TDM process in an IT company based on a predefined workshop concept. We analyzed which research approaches practitioners adopted for each TD activity and the TDM's long-term effect on TD awareness. Method. We used action research (five action cycles in …

Non Technical Debt in Agile Software Development
Muhammad Ovais Ahmad, Tomas Gustavsson
https://arxiv.org/abs/2509.01445 https://arxiv.org/pdf/2509.01445…

Non Technical Debt in Agile Software Development
NonTechnical Debt (NTD) is a common challenge in agile software development, manifesting in four critical forms, Process Debt, Social Debt, People Debt, Organizational debt. NODLA project is a collaboration between Karlstad University and four leading Swedish industrial partners, reveals how various debt types disrupt large scale Agile Software Development (ASD) environments. Through extensive surveys, indepth interviews, and statistical analyses involving a diverse group of software profession…

Technical debt to society
Technical debtor's prisons

ARRC: Explainable, Workflow-Integrated Recommender for Sustainable Resource Optimization Across the Edge-Cloud Continuum
Brian-Frederik Jahnke, Ren\'e Brinkhege, Jan Peter Meyer, Daniel Tebernum, Falk Howar
https://arxiv.org/abs/2507.12032

ARRC: Explainable, Workflow-Integrated Recommender for Sustainable Resource Optimization Across the Edge-Cloud Continuum
Achieving sustainable, explainable, and maintainable automation for resource optimization is a core challenge across the edge-cloud continuum. Persistent overprovisioning and operational complexity often stem from heterogeneous platforms and layered abstractions, while systems lacking explainability and maintainability become fragile, impede safe recovery, and accumulate technical debt. Existing solutions are frequently reactive, limited to single abstraction layers, or require intrusive platfo…

Today I'm fixing about a gazillion little issues with our website, mostly for SEO reasons:
- All pages should now have a semantically relevant H1 Tag
- Found the last few page titles that didn't make sense and fixed them
- Our logo had no ALT attribute
- The font in the Survey Chart Tooltips was wrong
- Generally survey charts had wayyy to many decimals
- OpenGraph tags are weird but whatever
Keeping technical debt down is like brushing your teeth…

ACE: Automated Technical Debt Remediation with Validated Large Language Model Refactorings
Adam Tornhill, Markus Borg, Nadim Hagatulah, Emma S\"oderberg
https://arxiv.org/abs/2507.03536

ACE: Automated Technical Debt Remediation with Validated Large Language Model Refactorings
The remarkable advances in AI and Large Language Models (LLMs) have enabled machines to write code, accelerating the growth of software systems. However, the bottleneck in software development is not writing code but understanding it; program understanding is the dominant activity, consuming approximately 70% of developers' time. This implies that improving existing code to make it easier to understand has a high payoff and - in the age of AI-assisted coding - is an essential activity to ensure…

Growing Mathlib: maintenance of a large scale mathematical library
Anne Baanen, Matthew Robert Ballard, Johan Commelin, Bryan Gin-ge Chen, Michael Rothgang, Damiano Testa
https://arxiv.org/abs/2508.21593

Growing Mathlib: maintenance of a large scale mathematical library
The Lean mathematical library Mathlib is one of the fastest-growing libraries of formalised mathematics. We describe various strategies to manage this growth, while allowing for change and avoiding maintainer overload. This includes dealing with breaking changes via a deprecation system, using code quality analysis tools (linters) to provide direct user feedback about common pitfalls, speeding up compilation times through conscious library (re-)design, dealing with technical debt as well as wri…

Does Editing Improve Answer Quality on Stack Overflow? A Data-Driven Investigation
Saikat Mondal, Chanchal K. Roy
https://arxiv.org/abs/2507.21329 https://…

Does Editing Improve Answer Quality on Stack Overflow? A Data-Driven Investigation
High-quality answers in technical Q&A platforms like Stack Overflow (SO) are crucial as they directly influence software development practices. Poor-quality answers can introduce inefficiencies, bugs, and security vulnerabilities, and thus increase maintenance costs and technical debt in production software. To improve content quality, SO allows collaborative editing, where users revise answers to enhance clarity, correctness, and formatting. Several studies have examined rejected edits and ide…

BitsAI-Fix: LLM-Driven Approach for Automated Lint Error Resolution in Practice
Yuanpeng Li, Qi Long, Zhiyuan Yao, Jian Xu, Lintao Xie, Xu He, Lu Geng, Xin Han, Yueyan Chen, Wenbo Duan
https://arxiv.org/abs/2508.03487

BitsAI-Fix: LLM-Driven Approach for Automated Lint Error Resolution in Practice
As enterprise codebases continue to grow in scale and complexity, the volume of lint errors far exceeds engineers' manual remediation capacity, leading to continuous accumulation of technical debt and hindered development efficiency. This paper presents BitsAI-Fix, an automated lint error remediation workflow based on Large Language Models (LLMs), designed to address this critical challenge in industrial-scale environments. BitsAI-Fix employs tree-sitter for context expansion and generates sear…