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Debugging AI-generated code

Beginner⏱ 11 min read📅 Updated: 2026-02-17

🐛 Introduction – Why AI Code Needs Debugging

AI oru amazing code generator – but perfect code generator illa! 😅

AI-generated code la issues varum because:

🎭 Hallucination – Non-existent functions/APIs use pannum
📅 Outdated knowledge – Old library versions, deprecated methods
🧩 Context missing – Your project specifics theriyaadhu
⚠️ Edge cases – Happy path mattum handle pannum
🔒 Security gaps – Vulnerabilities miss pannum

Real stat: Studies show AI-generated code la 30-40% bugs irukku without proper review! 😱

But don't worry – debugging AI code oru learnable skill. Indha article la master pannalam! 💪

🔍 Common AI Code Bugs – Know Your Enemy

AI commonly make panra mistakes:

Bug Type	Description	Frequency	Severity
Hallucinated APIs	Non-existent methods use	Very common	High
Wrong versions	Deprecated syntax	Common	Medium
Missing error handling	No try-catch, no null checks	Very common	High
Security holes	SQL injection, XSS	Common	Critical
Logic errors	Wrong conditions, off-by-one	Common	High
Hardcoded values	Magic numbers, hardcoded URLs	Common	Medium
Type mismatches	Wrong data types	Common	Medium
Import errors	Wrong package names	Common	Low

Most dangerous: Security holes – AI code la SQL injection and XSS vulnerabilities frequently varum! 🔒

🎬 Real Debugging Scenario

✅ Example

Situation: AI generate panna login function work aagala.

AI-generated code:

javascript

async function login(email, password) {
  const user = await db.query(
    "SELECT * FROM users WHERE email = '" + email + "'"
  );
  if (user.password === password) {
    return generateToken(user);
  }
}

Bugs found: 🐛🐛🐛

1. ❌ SQL Injection – String concatenation! Use parameterized queries

2. ❌ Plain text password – password hash compare pannanum

3. ❌ No error handling – user null check illa

4. ❌ No return for failed login – undefined return aagum

5. ❌ No rate limiting – brute force attack possible

5 bugs in 7 lines! This is why debugging AI code is critical! 🎯

🛠️ Debugging Strategy 1: Read Before Run

First rule: AI code directly run pannadheenga! READ first! 📖

Reading checklist:

📋 Line by line padingа
🔍 Each function enna panudhu nu understand pannunga
⚠️ Error handling irukka nu check pannunga
🔒 Security issues spot pannunga
📦 Import/dependencies correct aa nu verify pannunga

Red flags to look for:

🚩 String concatenation in database queries
🚩 No input validation
🚩 Hardcoded credentials or URLs
🚩 Missing null/undefined checks
🚩 No error handling (no try-catch)
🚩 Deprecated method usage
🚩 Any function you don't recognize

Pro tip: Code readability good aa irundha, bugs easy aa spot pannalam. AI code messy aa irundha, first refactor pannunga! 🧹

🧪 Debugging Strategy 2: Test Immediately

AI code ku tests write pannunga before integrating!

Testing approach:

1. Happy path test ✅

Normal input la correct output varudhaa?

2. Edge case test 🔄

Empty input, null, undefined, very large values, special characters

3. Error case test ❌

Invalid input la proper error varudhaa?

4. Boundary test 📏

Min/max values, array boundaries, string length limits

Test Type	Example Input	Expected
Happy path	valid email	Login success
Empty input	""	Error message
Null input	null	Error, not crash
SQL injection	"'; DROP TABLE--"	Sanitized/blocked
Long input	10000 char string	Handled gracefully
Special chars	"test@#$%"	Proper validation

AI kitta ae test generate panna sollunga:

"Write comprehensive unit tests for this function, including edge cases, error cases, and security tests" 🧪

🔧 Debugging Strategy 3: Console & Debugger

Classic debugging techniques – AI code ku um apply aagum!

Console.log debugging:

javascript

// Strategic logging points
console.log('Input:', input);
console.log('After processing:', result);
console.log('API response:', response);
console.log('Final output:', output);

Debugger usage:

VS Code la breakpoints set pannunga
Step through AI code line by line
Variable values inspect pannunga
Call stack check pannunga

When to use which:

Method	Best For	Speed
console.log	Quick checks	⚡ Fast
Debugger	Complex logic	🔄 Thorough
Network tab	API issues	⚡ Fast
Error stack	Crash debugging	⚡ Fast
AI assistance	Understanding logic	🔄 Medium

Pro tip: AI code la step-by-step execution pannunga debugger la. Oru line skip pannadheenga – unexpected behavior hidden aa irukkum! 🔍

🤖 Debugging Strategy 4: Use AI to Debug AI

Ironic but effective – AI use panni AI code debug pannunga! 😂

Method 1: Error + Code paste

code

I got this error: [error message]
In this code: [code]
Expected behavior: [what should happen]
Actual behavior: [what happened]

Method 2: Code review request

"Review this code for bugs, security issues, performance problems, and edge cases"

Method 3: Explain and find

"Explain this code line by line. Point out any potential issues."

Method 4: Fix specific issue

"This function returns undefined when input is empty array. Fix it and explain why."

Tips for AI debugging:

📋 Always provide full context – partial code = partial solutions
🎯 Be specific about the problem
🔄 If first fix doesn't work, provide the new error
🧪 Ask AI to write tests for the fix too

Warning: AI might introduce new bugs while fixing old ones! Always re-test! 🔄

🔒 Security Debugging – Critical!

AI code la security bugs most dangerous!

Common security issues in AI code:

Vulnerability	AI Mistake	Fix
SQL Injection	String concat in queries	Parameterized queries
XSS	Unescaped user input	Sanitize/escape output
IDOR	No authorization check	Verify ownership
Hardcoded secrets	API keys in code	Environment variables
No rate limiting	Unlimited API calls	Implement rate limits
CORS misconfigured	Allow all origins	Specific origins only
Missing auth	No authentication	Add auth middleware

Security review checklist:

🔍 User input validate aagudhaa?
🔒 Database queries parameterized aa?
🔑 Secrets code la hardcode aagala illai?
🛡️ Authentication/authorization check irukka?
📝 Sensitive data logged aagala illai?
⏱️ Rate limiting irukka?

Rule: Security issues fix pannaamal never deploy pannunga! 🚨

📋 AI Code Review Checklist

Every AI-generated code ku indha checklist follow pannunga:

Functionality ✅

[ ] Code expected output kodukudhaa?
[ ] Edge cases handle pannudhaa?
[ ] Error handling proper aa irukka?

Security 🔒

[ ] Input validation irukka?
[ ] No SQL injection?
[ ] No XSS vulnerabilities?
[ ] No hardcoded secrets?
[ ] Auth checks proper aa?

Code Quality 📝

[ ] Variable names meaningful aa?
[ ] Functions small and focused aa?
[ ] DRY principle follow pannudhaa?
[ ] Comments/docs irukka?

Performance ⚡

[ ] Unnecessary loops illa?
[ ] N+1 query problem illa?
[ ] Memory leaks potential illa?

Dependencies 📦

[ ] Packages exist and correct version aa?
[ ] No deprecated APIs used?
[ ] License compatible aa?

🔄 Iterative Debugging Workflow

AI code debugging workflow:

Round 1: Quick Scan 👀 (5 min)

Code read pannunga
Obvious bugs spot pannunga
Red flags identify pannunga

Round 2: Run & Observe 🏃 (10 min)

Code run pannunga
Console output check pannunga
Error messages note pannunga

Round 3: Test 🧪 (15 min)

Unit tests write pannunga
Edge cases test pannunga
Failing tests note pannunga

Round 4: Fix 🔧 (20 min)

Bugs fix pannunga (manually or AI help)
Security issues address pannunga
Re-run tests

Round 5: Verify ✅ (10 min)

All tests pass?
Original requirements meet aagudhaa?
New bugs introduce aagalai?

Total time: ~1 hour for thorough debugging. Worth it compared to production bugs! 💰

🧰 Debugging Tools for AI Code

Essential tools for debugging:

Tool	Purpose	Platform
VS Code Debugger	Step-through debugging	All
Chrome DevTools	Frontend debugging	Web
Postman	API testing	All
ESLint	Code quality checks	JS/TS
TypeScript	Type error catching	JS/TS
SonarQube	Security scanning	All
Jest	Unit testing	JS/TS
React DevTools	Component debugging	React

AI-specific tools:

🤖 Claude/ChatGPT – Explain errors, suggest fixes
🔍 Copilot Chat – In-editor debugging help
🛡️ Snyk – Security vulnerability scanning
📊 CodeClimate – Automated code review

Pro tip: TypeScript use pannunga! Type errors build time la catch pannalam – AI code la type issues common! 📝

💡 Preventing AI Code Bugs

Prevention better than cure! 🏥

Better prompts = Fewer bugs:

📝 Specify error handling requirements
🔒 Mention security requirements
🧪 Ask for edge case handling
📦 Specify exact library versions
🏗️ Provide project context

Example good prompt:

"Write a Node.js Express endpoint for user registration. Use bcrypt for password hashing, parameterized queries for PostgreSQL, input validation with Joi, proper error handling with specific error messages, and rate limiting. Handle: empty fields, duplicate email, weak password, database errors."

vs bad prompt:

"Write a registration endpoint"

Good prompt result: 80% clean code

Bad prompt result: 40% clean code

Prevention Method	Effort	Bug Reduction
Detailed prompts	Low	40%
TypeScript	Medium	30%
Linting	Low	15%
Code review	Medium	25%
Testing	Medium	35%

🛠️ Practice Exercise

Debugging skills improve panna try pannunga:

code

Exercise: AI kitta indha prompt kudunga:
"Write a todo list API with CRUD operations"

Then:
1. Code generate pannunga
2. Our checklist use panni review pannunga  
3. How many bugs you find?
4. Fix each bug
5. Write tests
6. Compare: original vs fixed version

Challenge: 5+ bugs find pannunga! (Usually easy with AI-generated CRUD code) 🎯

📝 Summary

Key Takeaways:

✅ AI code always has bugs – never trust blindly

✅ Common issues: hallucinated APIs, security holes, missing error handling

✅ Debug strategy: Read → Test → Console/Debugger → AI assist → Verify

✅ Security review is non-negotiable

✅ Use AI to debug AI – but verify the fix too!

✅ Prevention: detailed prompts, TypeScript, linting, testing

✅ Follow the review checklist for every AI-generated code

Debugging AI code oru essential skill for modern developers. Master pannunga – your code quality 10x improve aagum! 🐛💪

🏁 Mini Challenge

Challenge: Debug Intentionally Buggy AI Code

Oru debugging exercise practice pannunga (30 mins):

Generate Buggy Code: AI kitta "Write a JWT authentication middleware for Express" nu ask panni code generate pannunga
Add Bugs: AI-generated code la 3-4 intentional bugs add pannunga
Time Yourself: Debug panna time track panni start pannunga
Debug Systematically: Our checklist (security, error handling, edge cases, performance) use pannunga
Write Tests: Each bug verify panna test cases write pannunga
Document: Each bug type analysis panni learning capture panni

Tools: VS Code Debugger, Node.js, Jest for testing

Success Criteria: All bugs caught and fixed, tests passing 🐛

Interview Questions

Q1: AI kitta code generate panna after, review process enna step-by-step?

A: Read code manually, check for obvious issues, run with test inputs, use debugger for flow verification, security review (injection, auth, secrets), error handling review, performance check.

Q2: Most common bugs AI-generated code la irukkum – examples kodu panni?

A: Missing error handling, hardcoded values, security vulnerabilities (SQL injection, XSS), off-by-one errors in loops, missing null checks, incorrect type assumptions, not handling edge cases.

Q3: AI hallucinations enna? How catch pannalam?

A: AI made-up function names, libraries, or APIs invent pannum. Catch pannalam by testing code, checking if imported packages actually exist, and verifying API documentation.

Q4: TypeScript AI code errors reduce panna help panala?

A: Absolutely! TypeScript catches many errors at compile time instead of runtime. Type checking, interface validation, auto-complete improvements – all help catch bugs early.

Q5: AI code debug panra time vs manual code debug panra time – comparison enna?

A: AI code usually simpler, straightforward bugs have, faster debug possible. But security/edge case bugs find harder because AI generated patterns might repeat across code. Targeted review approach necessary.

❓ Frequently Asked Questions

❓ AI code la bugs varumo?

Definitely varum! AI hallucinate pannum, outdated patterns use pannum, edge cases miss pannum. Always review and test pannanum.

❓ AI code debug panna special tools venuma?

Regular debugging tools ae podhum – browser DevTools, console.log, debugger. Plus AI itself debug help pannum!

❓ AI code la common bugs enna?

Off-by-one errors, missing error handling, security vulnerabilities, wrong library versions, hardcoded values, and logic errors in edge cases.

❓ AI kitta ae debug panna sollalamaa?

Yes! Error message + code + context paste pannunga. AI good debugging assistant. But blindly trust pannaama verify pannunga.

🧠Knowledge Check

Quiz 1 of 1

AI code debugging concepts test pannunga:

0 of 1 answered

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