K:Dataset provenance and dependency
Dataset provenance and dependency
Editorial topic mappings connect related questions across sources and book chapters.
SE@PoliMi bibliography 31
- W012 — Agentic Coding in the Wild: Characterizing GitHub Copilot Traces at Production Scale
Liu · 2026 - W021 — The AI Engineering Report 2026: The Acceleration Whiplash
Faros AI · 2026 - W022 — AI Coding Agents: Adoption Trends
JetBrains Research · 2026 - W023 — Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
Becker · 2025 - W033 — How AI Coding Agents Modify Code: A Large-Scale Study of GitHub Pull Requests
Ogenrwot · 2026 - W034 — Comparing AI Coding Agents: A Task-Stratified Analysis of Pull Request Acceptance
Pinna · 2026 - W035 — Security in the Age of AI Teammates: An Empirical Study of Agentic Pull Requests on GitHub
Siddiq · 2026 - W039 — Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity
Cotroneo · 2025 - W046 — Do Users Write More Insecure Code with AI Assistants?
Perry · 2023 - W049 — The Range Shrinks, the Threat Remains: Re-evaluating LLM Package Hallucinations on the 2026 Frontier-Model Cohort
Churilov · 2026 - W054 — Not All Agents Are Equal: Code Quality and Post-Merge Maintenance Across Five Autonomous Coding Agents in the Wild
Kraishan · 2026 - W057 — How Do AI Coding Agents Contribute to Software Development? An Empirical Study of Agentic Pull Requests
Mazloomzadeh · 2026 - W065 — These Aren't the Reviews You're Looking For: How Humans Review AI-Generated Pull Requests
Duma · 2026 - W068 — Behind Agentic Pull Requests: An Empirical Study on Developer Interventions in AI Agent-Authored Pull Requests
Khelifi · 2026 - W071 — Why Are Agentic Pull Requests Merged or Rejected? An Empirical Study
Peralta · 2026 - W079 — Correlated Errors in Large Language Models
Kim · 2025 - W081 — Deep Learning-based Code Reviews: A Paradigm Shift or a Double-Edged Sword?
Tufano · 2025 - W086 — Quality Evaluation of Modern Code Reviews Through Intelligent Biometric Program Comprehension
Hijazi · 2023 - W095 — Beyond Code Generation: Reliability, Verification, and Cost Economics in the Agentic Software Development Lifecycle
Bhati · 2026 - W105 — Beyond Lexical Metrics: Sentence-Embedding Detection of Reviewer Habituation in AI Code Review
Yu · 2026 - W112 — Novice Developers Produce Larger Review Overhead for Project Maintainers while Vibe Coding
Asdaque · 2026 - W157 — ClawVM: Harness-Managed Virtual Memory for Stateful Tool-Using LLM Agents
Rafique · 2026 - W161 — Examining ownership models in software teams: A systematic literature review and a replication study
Koana · 2024 - W171 — Revisiting Turnover-Induced Knowledge Loss in Software Projects
Nassif · 2017 - W172 — Measuring neural efficiency of program comprehension
Siegmund · 2017 - W175 — Code Ownership and Software Quality: A Replication Study
Greiler · 2015 - W177 — Stuck and Frustrated or in Flow and Happy: Sensing Developers' Emotions and Progress
Müller · 2015 - W183 — Moving into a New Software Project Landscape
Dagenais · 2010 - W190 — How do Humans and LLMs Process Confusing Code?
Abdelsalam · 2025 - W191 — Where Do AI Coding Agents Fail? An Empirical Study of Failed Agentic Pull Requests in GitHub
Ehsani · 2026 - W192 — AIDev: Studying AI Coding Agents on GitHub
Li · 2026
The Pragmatic Engineer 23
- P003 — State of the software engineering job market in 2024
Gergely Orosz · 2024-10-22 - P008 — IDEs with GenAI features that Software Engineers love
Gergely Orosz · 2024-11-26 - P009 — The Pragmatic Engineer in 2024
Gergely Orosz · 2024-11-29 - P023 — Where did TikTok’s software engineers go?
Gergely Orosz · 2025-02-06 - P025 — State of the startup and scaleup hiring markets in 2025 – as seen by recruiters
Gergely Orosz · 2025-02-18 - P026 — Software engineering job openings hit five-year low?
Gergely Orosz · 2025-02-20 - P028 — Trimodal Nature of Tech Compensation in the US, UK and India
Gergely Orosz · 2025-03-04 - P030 — Survey: What’s in your tech stack?
Gergely Orosz; Elin Nilsson · 2025-03-18 - P036 — More than one million readers
Gergely Orosz · 2025-04-22 - P045 — Builder.ai did not “fake AI with 700 engineers”
Gergely Orosz · 2025-06-12 - P050 — The Pragmatic Engineer 2025 Survey: What’s in your tech stack? Part 1
Gergely Orosz; Elin Nilsson · 2025-07-15 - P056 — The Pragmatic Engineer 2025 Survey: What’s in your tech stack? Part 2
Gergely Orosz; Elin Nilsson · 2025-08-19 - P059 — State of the software engineering job market in 2025, part 1, what the data says
Gergely Orosz · 2025-09-02 - P063 — Inside Google’s Engineering Culture: the Tech Stack (Part 2)
Gergely Orosz; Elin Nilsson · 2025-09-30 - P065 — The Pragmatic Engineer 2025 Survey: What’s in your tech stack? Part 3
Gergely Orosz; Elin Nilsson · 2025-10-14 - P089 — AI Tooling for Software Engineers in 2026
Gergely Orosz; Elin Nilsson · 2026-03-03 - P095 — The impact of AI on software engineers in 2026: key trends. Part 1
Gergely Orosz; Elin Nilsson · 2026-04-14 - P099 — TechPays has been acquired by Levels.fyi
Gergely Orosz · 2026-05-12 - P101 — AI’s impact on software engineers in 2026: key trends, Part 2
Gergely Orosz; Elin Nilsson · 2026-05-19 - P102 — State of the software engineering job market in 2026
Gergely Orosz; Jessica Salmon · 2026-05-26 - P104 — State of the software engineering job market in 2026, part 2
Gergely Orosz; Jessica Salmon · 2026-06-09 - P108 — Pollen tried to remove my article about CEO Callum Negus-Fancey and CTO Bradley Wright, and Google is assisting with it
Gergely Orosz · 2026-06-28 - P117 — How software engineering is changing: an essay challenge
Gergely Orosz · 2026-09-01