Here are five checks that help me approach debugging more systematically.

1. Read the compiler errors carefully

The MetaEditor compiler output is usually the first place I look when a program fails to compile.

I check the reported line number, error description, and surrounding code. Sometimes one missing semicolon or mismatched bracket can cause several additional errors to appear.

Rather than fixing every reported line blindly, I look for the earliest meaningful error first.

2. Check variable types and declarations

MQL5 has different data types for integers, floating-point values, strings, Boolean values, and more.

Using the wrong type or referencing an undeclared variable can cause compilation errors or unexpected behavior.

I also check whether variables are declared in the correct scope and whether their values are initialized before use.

3. Verify function parameters and return values

When a function doesn't behave as expected, I check its parameters, return type, and how it is called.

For built-in MQL5 functions, I refer to the official documentation rather than guessing the expected arguments.

This is especially useful when working with unfamiliar trading, order-management, or market-data functions.

4. Use logs to understand runtime behavior

A program can compile successfully and still behave incorrectly when running.

The Experts and Journal tabs in MetaTrader 5 can provide useful information about runtime errors, rejected requests, and other events.

Adding targeted Print() statements can also help reveal the values a program is receiving and the path its logic is following.

5. Test one change at a time

When several changes are made together, it becomes harder to identify which change fixed the problem—or introduced another one.

I prefer to make a focused change, compile again, and test the affected behavior before moving to the next issue.

For trading software, testing should be performed in an appropriate demo or controlled environment before considering live use.

Final thoughts

Debugging is not just about removing compiler errors. It's about understanding why the program behaves the way it does.

A systematic process makes it easier to isolate problems, verify fixes, and maintain code over time.

What's your first step when debugging an MQL5 program: checking compiler errors, reviewing the logic, or inspecting runtime logs?

I've come across systems with impressive backtests, attractive equity curves, and very promising results. But once you start looking deeper, the picture can change completely.

That's why I started paying less attention to headline profits and more attention to how the system actually behaves.

1. Drawdown matters more than impressive profits

A system making 100% might look great at first.

But if it had to experience a 40% drawdown to achieve that result, the return doesn't tell the whole story.

When testing an EA, I pay close attention to maximum drawdown, consecutive losses, recovery periods, and how the account behaves during difficult market conditions.

2. I look closely at the risk management

One of the first things I want to understand is how the EA handles losing trades.

Does it use a defined stop loss?

Does the lot size increase after losses?

Does it open multiple positions to recover a losing trade?

These details can completely change the risk profile of an automated system.

3. Grid and martingale systems need extra attention

Grid and martingale approaches can produce very smooth-looking results for a period of time.

The problem is that the underlying risk can remain hidden until the market moves strongly in one direction.

A system that appears extremely consistent isn't necessarily low risk.

Understanding how it produces those results is more important than simply looking at the percentage return.

4. Backtests aren't enough

Backtesting is useful, but I don't consider a backtest to be the final proof that an EA works.

Real trading introduces factors such as:

• Spread

• Slippage

• Execution speed

• Broker conditions

• Market volatility

• News events

• Trading session differences

A system can perform very differently in live conditions compared with historical testing.

5. I prefer understanding the system over chasing returns

After testing many different EAs, my approach has changed.

Instead of asking:

"How much profit does this EA make?"

I prefer asking:

"How does this EA make its money, and what happens when the market moves against it?"

That question usually tells me much more.

What I'm exploring

Through MQL5 Trading Lab, I'll be sharing more about:

• MQL5 development

• MetaTrader 5 automation

• EA testing

• Debugging and development problems

• Risk management

• Trading system evaluation

• Lessons from real-world testing

The goal isn't to promote every system I come across.

It's to document what I learn and hopefully help other traders and developers make better decisions when working with automated trading systems.

More testing, less hype.