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C:C08

Chapter 8: Code Review and Trust Calibration

A guide to the published second edition, with literal citations separated from wider editorial reading suggestions.

Open this group in the atlasChapter catalogue entry

Chapter guide

Allocates review effort by consequence and uncertainty. It examines human and AI reviewers, false positives, shared blind spots and automation bias, then separates finding disposition, coverage of acceptance obligations and the accountable release verdict.

Code review e calibrazione della fiducia

Sintesi in italiano

Distribuisce il lavoro di revisione in base a conseguenze e incertezza. Esamina reviewer umani e AI, falsi positivi, punti ciechi condivisi e automation bias, distinguendo la gestione delle osservazioni, la copertura degli obblighi di accettazione e il verdetto di rilascio.

Learning goals

  • allocate review effort by consequence and uncertainty
  • recognize when two reviewers share the same error source
  • distinguish the disposition of a review finding, coverage of acceptance obligations and release authority
Obiettivi in italiano

Obiettivi di apprendimento

  • distribuire l'impegno della review in base alle conseguenze e all'incertezza
  • riconoscere quando due reviewer condividono la stessa fonte di errore
  • distinguere l'esito di un finding di review, la copertura degli obblighi di accettazione e l'autorità necessaria per la release
Chapter outline
  • 8.1 Why review becomes the scarce resource
  • 8.2 The influence of code complexity and provenance
  • 8.3 Human intervention in agent pull requests
  • 8.4 What AI reviewers catch—and miss
  • 8.5 False positives, verbosity and developer response
  • 8.6 Self-review, cross-model review and shared blind spots
  • 8.7 Automation bias in software review
  • 8.8 Risk-based review allocation
  • 8.9 The review verdict is an artifact, not a comment count
  • 8.10 From comments to accountable acceptance
  • 8.11 Worked engineering example: review the riskiest uncertainty first
  • 8.12 Practice exercise: review two plausible agent pull requests
Struttura del capitolo
  • 8.1 Perché la review diventa la risorsa scarsa
  • 8.2 L'impatto della complessità e della provenienza del codice
  • 8.3 Interventi umani nelle pull request degli agent
  • 8.4 Che cosa trovano, e che cosa non trovano, gli AI reviewer
  • 8.5 Falsi positivi, verbosità e risposta degli sviluppatori
  • 8.6 Self-review, review tra modelli diversi e punti ciechi condivisi
  • 8.7 Automation bias nella code review
  • 8.8 Assegnare la review in base al rischio
  • 8.9 Il verdetto della review è un artefatto, non un conteggio di commenti
  • 8.10 Dai commenti all'accettazione responsabile
  • 8.11 Esempio svolto: esaminare prima l'incertezza più rischiosa
  • 8.12 Esercizio: esaminare due pull request plausibili create da agent

Cited in the published chapter

28 linked atlas references from literal citations in the English and Italian editions. General bibliography membership and identifier-index entries are counted separately.

SE@PoliMi bibliography 25

Addy Osmani 2

The Pragmatic Engineer 1

Trace literal citations to chapter sections

Locations come from the supplied English and Italian source files. Chapter text and figure captions are identified separately; identifier-index references and general bibliography membership are not treated as chapter citations.

Complete citation locators and source hashes

Editorial reading mappings

Broader topical suggestions can overlap the cited sources. A mapping does not add a citation to the published edition or establish that a practice is effective.

SE@PoliMi bibliography 71

Addy Osmani 5

The Pragmatic Engineer 5

Martin Fowler’s website 6

Earlier Non-Deterministic books 11

Software Engineering Practices 7