What is your debugging approach?

Do you have a pattern you follow when tasked to track down a bug?

Comments

[Damien Cosset]

1- Panic
2- Question my ability to do shit as a developer
3- Calm down, start to look at the logs
4- Start spamming console.log()
5- Rage because there are too many console.log to keep track
6- If bug is complicated, get back to 1)
7- Making progress, adding a fix
8- Commit/push
9- Realize some other part is broken because of the fix
10- Back to 1)
11- Around 6PM, throw my hands in the air, yell "Fuck this shit", and leave.
12- Around 9AM the next morning, realize it was a typo.

[Mario]

Start spamming console.log()

console.log('here1');
console.log('here2');
console.log('here3');
console.log('blabla');
console.log('bananas');
console.log('hmmm');

[Damien Cosset]

I feel you! I'm more of a:

console.log('HI')
console.log('HELLO')
console.log('HHEEEEEEYYYYY')

kind of dev, but I see where you're coming from :D

[Daragh Byrne]

12, every bloody time!!

[zoso1166]

Dude, I read this and left for like 10 minutes !! Thanks for making my day 😁

[momo-barro]

your answer made my day :'‑) :'‑) :'‑)

[kleene1]

Yeh..lol haha 😄

[Arpit Mohan]

1. Grep through the logs for any obvious issues or errors. With decent logging, 50% RCA happens here.
2. Try to replicate the scenario in local environments and see the bug in action.
3. Keep adding printf statements after each line of execution. Occasionally use the debugger as well on local to triage the issue.
4. Forget to remove printf statements when committing fix.
5. Create hotfix commit to remove debug logs 😄
6. Actually deploy fix to production.

[Renato Byrro]

👏 claps for honesty! 😄

[Krishna Damaraju]

1. First thought - "Oh shit" 🤭
2. Check the git commit and understand the code changes went with that.
3. Put on the headphones 🎧 with the debugging playlist
4. Use debugger and console.log to debug
5. Bang my head around it 😂
6. Realise the issue was small 🤦‍♂️
7. Look at my self in the mirror 😏
8. Fixing it 💪
9. Writing test cases
10. Make a hot fix with a typo
11. Deploy and forget 😂

[Srinivasa Rao]

Here is my approach

1. Reproduce the bug
2. Locate the bug ( I use bunch of print statements, pdb here)
3. Fix the bug
4. Test it carefully
5. Deploy on to staging and test again
6. Deploy on to production

[Renato Byrro]

I wouldn't say I have a pattern. Debugging is like an art. There are rarely two contexts where I can address the exact same way.

What I try to do all the time is to consider the context. I have lost too much time in the past for focusing too much on a single line or function, not understanding why it's failing.

In many cases, bugs are a product of a combination of factors.

Considering the context, what else is going on when the bug was produced, usually allows me to understand the cause faster.

[Stewart Smith]

I develop in a space where you can't trust the hardware you're running on. With that in mind:

1) check the logs
2) replicate the failure
3) come up with a minimal repro and pray that it fails consistently
4) use debugger Foo
5) consult hardware manuals for expected behaviour and interface
6) start tracing register activity and traffic to the hardware unit
7) start bit banging registers
8a) complain about the problem to coworkers
8b) learn about something seemly unrelated that is broken right now
8c) find out your problem is a corner case of that issue
9) file a driver or hardware bug
10) participate in long email threads followed by a meeting where the HW engs explain their change has no software impact and shouldn't break anything
11) HW engs end the meeting with "well in that case it does impact SW"

[Dave]

1. Tell the PM to discuss with QA, because Dev have no access to production.
2. Kick the Jira report back to QA as it doesn't have reproduction data.
3. Re-read and kick back again because it doesn't have logs attached.
4. Raise a ticket with ops to enable remote debug in production.
5. Connect to production debug port, add conditional breakpoints where I think the issue is.
6. Observe the issue in production.
7. Receive the updated Jira & confirm it reports the issue observed.
8. Repeat 5&6 until 7 is completed.
9. Write a test case that reproduces the bug & fails the build because of it.
10. Confirm expected behaviour with a BA.
11. Repeat 9&10 until happy.
12. Assign Jira to a junior dev, with a comment of "can you fix the build for this please?"
13. Coffee break.

[Prasanna Natarajan]

Recent favorite is testing a fix directly in production by monkey-patching the existing code with the fix (not recommended (but totally recommended)).

I'm a MonkeyPatch Debugger

Prasanna Natarajan ・ Sep 24 ・ 3 min read

#rails #ruby #debugging

The usual favorites are the ones mentioned in Aaron Patterson's puts debugging methods. I have a vim shortcut (space + D) to put out these puts statements:

puts "^^ #{?# * 90}" #DEBUG
p caller.join("\n") #DEBUG
puts "$$ #{?# * 90}" #DEBUG

For sql, I have sample queries for quick reference that does all sorts of queries that I'd mostly require in my current project (CTEs, window functions, certain joined tables etc)

[yucer]

If you write perfect patches maybe.

But if you're app use a shared state like the database, and your patch is wrong you might become nightmares.

The wrong states resulting for your mistake are left in the database. And worst is that normally the code is not made to handle inconsistent states.

If you note the mistake in the patch you can make a correction patch but also need an sql query to correct the wrong states.

Is you don't detect it son, the code might generate wormy states for the related entities and this situation spreads.

By the time you note the database might be so inconsistent that you better drop it.

[Prasanna Natarajan]

Yes, I'm aware of the risks of this approach.

I mentioned it explicitly in the post too.

Even if I know how the patch works inside out, I don't ever try this when it involves database changes. Too risky.

[Gerard Klijs]

Not really a pattern. If it's in some new functionality it's probably a typo somewhere. Logs might be useful, but it's also common for something expected not to happen, this no logging. If possible by debugging/ looking into the database check if some of the assumptions done might be wrong. Maybe there's a clue in the git log. Has SRE changed anything? Time to maybe as some logging statements to check assumptions. When it was Clojure I could just as them on the fly, and inspect the data directly.. and then it turns out it was a typo after all, ouch.

[chandrahasa k]

1. Reproduce the issue (entrust it to others if parallelism is possible.needed)
2. Check logs analyze the stack/error traces
3. If not enough detail available on the existing logs up the log level
4. Analyze the code as wirtten and see if there is an issue.
5. If step fails then run the code on local machine and debug it
6. Apply the fix, test and write automated tests to catch that in the future.
7. Release