M01-02 · AI-Assisted Software Development

Software Engineering Practice — Debugging, Testing, and Code Review

Teaches the core engineering practices that make a developer effective on a team: reading unfamiliar codebases, systematic debugging, writing and running tests, and participating in code review. Students learn to trace requests through a full-stack application, find root causes methodically, write tests that prevent regressions, and give and receive constructive code review — the skills that fill the first 30-60 days at any development job.

40 Hours

9 Learning objectives

Create Bloom's ceiling (?)

5 Competencies

What You'll Be Able To Do

Learning Objectives

Objectives

Depth

Navigate an unfamiliar codebase using git log, git blame, IDE search, and AI-assisted exploration to build a mental model of architecture and conventions Apply
Reproduce, isolate, and diagnose bugs systematically: read error messages, form hypotheses, use browser DevTools and logging, and trace requests through frontend, API, and database layers Analyze
Write unit, integration, and end-to-end tests using modern test frameworks (Jest/Vitest/Pytest), achieving meaningful coverage of critical paths Apply
Identify and fix common bug categories: timezone issues, state management bugs (stale closures, missing dependencies), race conditions, N+1 queries, and missing input validation Analyze
Open pull requests with clear descriptions, linked tickets, screenshots for visual changes, and appropriate scope (one logical change per PR) Apply
Review other developers' pull requests: identify missing error handling, untested paths, naming clarity issues, and convention violations Evaluate
Address code review feedback professionally: distinguish style preferences from correctness issues, ask clarifying questions, and iterate without defensiveness Apply
Use AI tools strategically for debugging (generating hypotheses, explaining unfamiliar code) while verifying AI suggestions against actual codebase behavior Evaluate
Write regression tests that specifically target the root cause of fixed bugs to prevent recurrence Create

Levels: Remember · Understand · Apply · Analyze · Evaluate · Create — highest demands most original thinking.

Core Competencies

What You'll Master

Codebase Navigation

Reading unfamiliar code using git history, blame, search, PR review, and AI-assisted exploration.

Systematic Debugging

Reproducing issues, hypothesis-driven root cause analysis, using DevTools, logging, and database inspection.

Test Engineering

Writing meaningful tests at unit, integration, and e2e levels; understanding test infrastructure and flaky test management.

Code Review Practice

Reviewing others' code for correctness, readability, and convention adherence; responding to review feedback constructively.

Git Workflow

Branching strategies, commit hygiene, PR creation, merge conflict resolution.

Portfolio Artifact

What You'll Build

Bug Hunt Case Study — Student receives a codebase with 5-7 planted bugs across the stack (frontend state bug, API validation gap, database query performance issue, race condition, timezone error). They document the full debugging process for each: reproduction steps, hypotheses tested, root cause analysis, fix implementation, and regression test written. Includes 2 code reviews of peers' work with actionable feedback.

Tools You'll Use

Industry Tools, Not Toy Projects

Git & GitHub

Version control, pull requests, blame, and code review workflows for team-based development.

VS Code / Cursor

Professional code editors with integrated debugging, search, and AI-assisted code exploration.

Jest / Vitest

Modern JavaScript test frameworks for unit, integration, and end-to-end testing.

Browser DevTools

Chrome/Firefox developer tools for inspecting network requests, debugging JavaScript, and profiling performance.

React DevTools

Browser extension for inspecting React component trees, state, props, and re-render behavior.

Postman / curl

API testing tools for sending requests, inspecting responses, and debugging backend endpoints.

PostgreSQL

Relational database with CLI and GUI tools (TablePlus) for inspecting data and debugging queries.

Claude Code & GitHub Copilot

AI coding assistants for generating debugging hypotheses, explaining unfamiliar code, and accelerating test writing.