T:Verification & review
Verification & review
Current source memberships across the atlas. A source can address more than one stream.
SE@PoliMi bibliography 69
- W002 — Code with Me or for Me? How Increasing AI Automation Transforms Developer Workflows
Chen · 2026 - W005 — Early Adoption of Agentic Coding Tools by GitHub Projects
Raida · 2026 - W009 — Productivity Assessment of Neural Code Completion
Ziegler · 2022 - W016 — The Impact of AI Coding Assistants on Software Engineering: A Longitudinal Study
Vella · 2026 - W018 — Intuition to Evidence: Measuring AI's True Impact on Developer Productivity
Kumar · 2025 - W029 — Beyond Bug Fixes: An Empirical Investigation of Post-Merge Code Quality Issues in Agent-Generated Pull Requests
Cynthia · 2026 - W031 — More Code, Less Reuse: Investigating Code Quality and Reviewer Sentiment towards AI-generated Pull Requests
Huang · 2026 - W032 — Understanding the Impact of AI Code Assistants on Security API Usage
Mousavi · 2026 - W033 — How AI Coding Agents Modify Code: A Large-Scale Study of GitHub Pull Requests
Ogenrwot · 2026 - W035 — Security in the Age of AI Teammates: An Empirical Study of Agentic Pull Requests on GitHub
Siddiq · 2026 - W036 — On the Use of Agentic Coding: An Empirical Study of Pull Requests on GitHub
Watanabe · 2026 - W046 — Do Users Write More Insecure Code with AI Assistants?
Perry · 2023 - W063 — An Endless Stream of AI Slop: How Developers Discuss the Burden of AI-Assisted Software Development
Baltes · 2026 - W064 — Studying Quality Improvements Recommended via Manual and Automated Code Review
Crupi · 2026 - W065 — These Aren't the Reviews You're Looking For: How Humans Review AI-Generated Pull Requests
Duma · 2026 - W066 — Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code Review
Gao · 2026 - W067 — (Don't) Trust, but (Don't) Verify: Developers' Attention to Security in AI-Generated Code
Khalid · 2026 - W068 — Behind Agentic Pull Requests: An Empirical Study on Developer Interventions in AI Agent-Authored Pull Requests
Khelifi · 2026 - W069 — Same Scrutiny, More Time: Eye Tracking Insights into Reviewing LLM-Labelled Code
Khojah · 2026 - W070 — Impact of an LLM-based Review Assistant in Practice: A Mixed Open-/Closed-source Case Study
Olewicki · 2026 - W071 — Why Are Agentic Pull Requests Merged or Rejected? An Empirical Study
Peralta · 2026 - W072 — AI-to-AI Code Reviews of GitHub Pull Requests
Selvanayagam · 2026 - W073 — The Effect of Complexity and Provenance on Code Review Decisions: Evidence from a Controlled Experiment
Singh · 2026 - W074 — RovoDev Code Reviewer: A Large-Scale Online Evaluation of LLM-based Code Review Automation at Atlassian
Tantithamthavorn · 2026 - W075 — Self-Correction Bench: Uncovering and Addressing the Self-Correction Blind Spot in LLMs
Tsui · 2026 - W076 — SWR-Bench: Assessing LLM Performance in Real-World Code Review Comment Generation
Zeng · 2026 - W077 — Evaluating and Mitigating the Misguidance Effect of Buggy Code in LLM-Generated Unit Tests
Zhao · 2026 - W078 — Beyond the Surface: Measuring Self-Preference in LLM Judgments
Chen · 2025 - W079 — Correlated Errors in Large Language Models
Kim · 2025 - W080 — Unit Testing Past vs. Present: Examining LLMs' Impact on Defect Detection and Efficiency
Ramler · 2025 - W081 — Deep Learning-based Code Reviews: A Paradigm Shift or a Double-Edged Sword?
Tufano · 2025 - W082 — LLM Evaluators Recognize and Favor Their Own Generations
Panickssery · 2024 - W083 — A Study on Developer Behaviors for Validating and Repairing LLM-Generated Code Using Eye Tracking and IDE Actions
Tang · 2024 - W084 — Self-Preference Bias in LLM-as-a-Judge
Wataoka · 2024 - W085 — Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance
Dratsch · 2023 - W086 — Quality Evaluation of Modern Code Reviews Through Intelligent Biometric Program Comprehension
Hijazi · 2023 - W087 — Do as AI say: susceptibility in deployment of clinical decision-aids
Gaube · 2021 - W088 — Trustworthiness Perceptions in Code Review: An Eye-tracking Study
Bertram · 2020 - W089 — The Role of Domain Expertise in User Trust and the Impact of First Impressions with Intelligent Systems
Nourani · 2020 - W090 — Decoding the Representation of Code in the Brain: An fMRI Study of Code Review and Expertise
Floyd · 2017 - W091 — Automation bias and verification complexity: a systematic review
Lyell · 2017 - W092 — Complacency and Bias in Human Use of Automation: An Attentional Integration
Parasuraman · 2010 - W093 — Automating Low-Risk Code Review at Meta: RADAR, Risk Calibration, and Review Efficiency
Adams · 2026 - W094 — AI Slop is DDoSing Open Source: Understanding the Impact of AI-Generated Contributions on Open Source Sustainability
Afroz · 2026 - W095 — Beyond Code Generation: Reliability, Verification, and Cost Economics in the Agentic Software Development Lifecycle
Bhati · 2026 - W096 — Go Home Copilot, You're Drunk: Understanding Developer Responses to Agent-Generated Code Review Comments
Cynthia · 2026 - W097 — Programmers Are Poor and Overconfident Judges of LLM-Generated Assertions
Kaufman · 2026 - W098 — Is Agentic Code Review Helpful? Mining Developers' Feedback to CodeRabbit Reviews in the Wild
Lin · 2026 - W099 — From Code Review to Code Critique: Intent, Drift, and Spotlight for AI-Generated Diffs at Scale
Maddila · 2026 - W100 — The End of Code Review: Coding Agents Supersede Human Inspection
Monperrus · 2026 - W101 — Articulate but Wrong: Self-Review Failures in LLM-Based Code Modernization
Purnachandra Reddy · 2026 - W102 — Cross-Model LLM Code Review: Should You Use Claude to Review Codex or Vice Versa?
Xiang · 2026 - W103 — An Eye for Trust: An Exploration of Developers' Trust Perceptions Through Urgency and Reputation
Yabesi · 2026 - W104 — Coding with Enemy: Can Human Developers Detect AI Agent Sabotage?
Ye · 2026 - W105 — Beyond Lexical Metrics: Sentence-Embedding Detection of Reviewer Habituation in AI Code Review
Yu · 2026 - W106 — Code Review Agent Benchmark (c-CRAB)
Zhang · 2026 - W107 — Human-AI Synergy in Agentic Code Review
Zhong · 2026 - W108 — Do LLM Evaluators Prefer Themselves for a Reason?
Chen · 2025 - W109 — LLM Critics Help Catch LLM Bugs
McAleese · 2024 - W110 — Overreliance on AI: Literature Review
Passi · 2022 - W111 — Many SWE-bench-Passing PRs Would Not Be Merged into Main
Whitfill · 2026 - W112 — Novice Developers Produce Larger Review Overhead for Project Maintainers while Vibe Coding
Asdaque · 2026 - W113 — I Would Have Written My Code Differently: Beginners Struggle to Understand LLM-Generated Code
Zi · 2025 - W116 — Using Biometrics to Understand AI-Assisted Coding Performance and its Perception
Burelli · 2026 - W122 — AI Didn't Make Programming Easier. It Just Made It Differently Difficult
Osborn · 2026 - W147 — To Ban or not to Ban? How Open Source Projects Govern GenAI Contributions
Yang · 2026 - W162 — 40 Years of Designing Code Comprehension Experiments: A Systematic Mapping Study
Wyrich · 2024 - 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
Addy Osmani 12
- O001 — The Code Nobody Reads
Addy Osmani · 2026-09-28 - O005 — Human judgment doesn't leave the software factory. It relocates.
Addy Osmani · 2026-08-21 - O007 — Agentic Code Quality
Addy Osmani · 2026-08-08 - O009 — Own the Outer Loop
Addy Osmani · 2026-07-09 - O011 — Agentic Code Review
Addy Osmani · 2026-06-16 - O019 — Code Review in the Age of AI
Addy Osmani · 2026-01-05 - O020 — How Good Is AI at Coding React (Really)?
Addy Osmani · 2025-12-29 - O021 — My LLM coding workflow going into 2026
Addy Osmani · 2025-12-18 - O023 — Treat AI-Generated code as a draft
Addy Osmani · 2025-11-25 - O033 — The "Trust, But Verify" Pattern For AI-Assisted Engineering
Addy Osmani · 2025-06-09 - O043 — Applied "Software Engineering at Google"
Addy Osmani · 2025-03-06 - O051 — Agentic Verification
Addy Osmani · 2026-10-14
The Pragmatic Engineer 13
- P006 — How to debug large, distributed systems: Antithesis
Gergely Orosz; Elin Nilsson · 2024-11-12 - P011 — How GenAI is reshaping tech hiring
Gergely Orosz; Elin Nilsson · 2024-12-03 - P014 — How AI-assisted coding will change software engineering: hard truths
Gergely Orosz; Addy Osmani · 2025-01-05 - P020 — Taking on Google search: Perplexity and Kagi
Gergely Orosz · 2025-01-28 - P029 — AI fakers exposed in tech dev recruitment: postmortem
Gergely Orosz · 2025-03-11 - P032 — AI Engineering in the real world
Gergely Orosz · 2025-03-25 - P035 — Tech hiring: is this an inflection point?
Gergely Orosz · 2025-04-15 - P041 — The AI Engineering Stack
Gergely Orosz; Chip Huyen · 2025-05-20 - P043 — Vibe Coding as a software engineer
Gergely Orosz; Elin Nilsson · 2025-06-03 - P075 — A pragmatic guide to LLM evals for devs
Gergely Orosz; Hamel Husain · 2025-12-02 - P085 — Deepdive: How 10 tech companies choose the next generation of dev tools
Gergely Orosz · 2026-02-03 - P118 — What is happening with code reviews?
Gergely Orosz · 2026-09-08 - P124 — Building resilient AI-powered software, and planning for when things go wrong
Gergely Orosz (introduction); Sam Newman (excerpts) · 2026-10-13
Martin Fowler’s website 13
- F002 — Median - A tale in three functions
Birgitta Böckeler · 2023-07-27 - F003 — In-line assistance - when is it more useful?
Birgitta Böckeler · 2023-08-01 - F004 — In-line assistance - how can it get in the way?
Birgitta Böckeler · 2023-08-03 - F006 — TDD with GitHub Copilot
Paul Sobocinski · 2023-08-17 - F008 — How to tackle unreliability of coding assistants
Birgitta Böckeler · 2023-11-29 - F011 — Expanding the solution size with multi-file editing
Birgitta Böckeler · 2024-11-19 - F014 — Guiding an LLM for Robust Java ByteBuffer Code
Unmesh Joshi · 2025-04-17 - F018 — Autonomous coding agents: A Codex example
Birgitta Böckeler · 2025-06-04 - F019 — I still care about the code
Birgitta Böckeler · 2025-07-09 - F021 — To vibe or not to vibe
Birgitta Böckeler · 2025-09-23 - F024 — Assessing internal quality while coding with an agent
Erik Doernenburg · 2026-01-27 - F031 — TDD inside the agent loop - theater or actual value?
Birgitta Böckeler · 2026-08-10 - F033 — Are Harnesses Worth the Cost?
Naresh Jain · 2026-10-13
Earlier Non-Deterministic books 76
- B005 — Vibe Coding vs. AI-Assisted Engineering
Enrico Papalini · - B007 — New Workflows for the AI Era
Enrico Papalini · - B008 — The Quality Crisis (And How to Prevent It)
Enrico Papalini · - B009 — Measuring What Matters---The Data Behind AI's Real Impact
Enrico Papalini · - B010 — The Adaptation Imperative---What Companies Must Do Now
Enrico Papalini · - B013 — PART I: Core Practices
Enrico Papalini · - B014 — PART II: Quality Assurance
Enrico Papalini · - B015 — PART III: Team Workflows
Enrico Papalini · - B016 — PART IV: Organizational Foundation
Enrico Papalini · - B018 — Antipatterns: What Not to Do
Enrico Papalini · - B020 — Understanding Tool Maturity Levels
Enrico Papalini · - B025 — From Single Agent to Multi-Agent Workflows
Enrico Papalini · - B026 — Development Practices Enhanced by AI
Enrico Papalini · - B027 — Team Collaboration \& Knowledge Sharing
Enrico Papalini · - B028 — Security, Compliance \& Governance
Enrico Papalini · - B029 — Measurement \& Observability
Enrico Papalini · - B030 — Common Pitfalls to Avoid
Enrico Papalini · - B031 — First 90-Days Implementation Roadmap
Enrico Papalini · - B032 — Quick Reference Guides
Enrico Papalini · - B034 — Implementation Guide and Solutions
Enrico Papalini · - B036 — Introduzioni e postfazione — The Bigger Picture
Enrico Papalini · - B037 — Preface
Enrico Papalini · - B038 — The Shift
Enrico Papalini · - B039 — The Process
Enrico Papalini · - B040 — The Toolkit
Enrico Papalini · - B041 — The Integration
Enrico Papalini · - B042 — Advanced Patterns
Enrico Papalini · - B043 — Limitations and Judgment
Enrico Papalini · - B044 — Templates
Enrico Papalini · - B045 — Complete Implementation Examples
Enrico Papalini · - B047 — Introduzioni alle parti — SDD, seconda edizione
Enrico Papalini · - B048 — Preface
Enrico Papalini · - B049 — The Shift
Enrico Papalini · - B050 — The Process: Four Phases, Four Gates
Enrico Papalini · - B054 — The Specification Toolkits: Spec Kit and OpenSpec (openspec.dev)
Enrico Papalini · - B055 — The Agentic Orchestrators: BMAD Method and AI-RPI Protocol
Enrico Papalini · - B056 — Autonomous Loops and Behavioral Foundations
Enrico Papalini · - B058 — Design Boundaries: What to Adopt, What to Avoid
Enrico Papalini · - B059 — Constitution and Architecture: The Framework Foundation
Enrico Papalini · - B060 — The Agent Pipeline and Gates
Enrico Papalini · - B062 — Autonomous Execution: Modes, Budgets, and Governance
Enrico Papalini · - B063 — Advanced Patterns: From Frameworks to Practice
Enrico Papalini · - B064 — Limitations and Professional Judgment
Enrico Papalini · - B065 — How to Design a New Framework
Enrico Papalini · - B068 — Template Reference
Enrico Papalini · - B070 — Enterprise SDD
Enrico Papalini · - B071 — Spec Kit
Enrico Papalini · - B073 — BMAD Method
Enrico Papalini · - B074 — AI-RPI Protocol
Enrico Papalini · - B075 — ralph-copilot
Enrico Papalini · - B076 — Spec Loop Engine
Enrico Papalini · - B081 — AIDD
Enrico Papalini · - B085 — The Continuous Development Revolution
Enrico Papalini · - B086 — The Philosophy of Deterministic Failure
Enrico Papalini · - B088 — The Ralph Loop Pattern
Enrico Papalini · - B089 — Task Decomposition for Machines
Enrico Papalini · - B091 — Quality Gates and Backpressure
Enrico Papalini · - B092 — Advanced Prompting for Autonomous Systems
Enrico Papalini · - B093 — Agentic Patterns in Practice
Enrico Papalini · - B094 — Scheduling and Overnight Execution
Enrico Papalini · - B095 — Multi-Agent Orchestration
Enrico Papalini · - B096 — Safety, Security, and Risk Management
Enrico Papalini · - B097 — Complete Implementation Guide
Enrico Papalini · - B098 — Tool Reference
Enrico Papalini · - B099 — Troubleshooting and Debugging
Enrico Papalini · - B100 — Ralph Loops with VS Code and GitHub Copilot
Enrico Papalini · - B101 — References and Sources
Enrico Papalini · - B103 — Summary
Enrico Papalini · - B104 — Non-Deterministic Loop Engineering: A Critical Assessment
Enrico Papalini · - B105 — The Organization Becomes a Loop
Enrico Papalini · - B106 — The Economics of Loop Engineering
Enrico Papalini · - B107 — The Ralph Loop: Persistent Progress Through Fresh Context
Enrico Papalini · - B108 — Building a Full Local AI Loop
Enrico Papalini · - B109 — Choosing the Right Loop
Enrico Papalini · - B110 — References — 85 voci bibliografiche
Enrico Papalini · - B111 — Glossary
Enrico Papalini ·
Software Engineering Practices 23
- PAT:005 — Feature List as Immutable Contract
- PAT:010 — Inference-Healed Code Review
- PAT:014 — Deterministic Failure Harness
- PAT:015 — Regression Safety Net
- PAT:022 — Trust Calibration
- PAT:027 — Maker–Checker: Separate Production from Acceptance
- PAT:039 — PR babysitter
- PAT:043 — Spec-First Generation
- PAT:044 — Test-Driven AI Development
- PAT:052 — Review Gauntlet
- PAT:061 — Consistency Analysis Gate
- PAT:064 — Specification Scale Management
- PAT:066 — Constitution-Driven Development
- PAT:067 — Clarify Before Plan
- PAT:068 — Progressive Specification
- PAT:069 — Red-Team Specification
- PAT:070 — Gap-Closure Analysis
- PAT:071 — Ambiguity Scoring
- PAT:074 — Anti-Sycophancy Enforcement
- PAT:075 — Convergence Review
- PAT:076 — Gate-Enforced Progression
- PAT:080 — Adversarial Agent Pattern
- PAT:082 — Evidence-Pack Provenance