# Bolt's Journal ⚡ This journal is for CRITICAL, non-routine performance learnings ONLY. - Codebase-specific bottlenecks - Failed optimizations (and why) - Surprising performance patterns - Rejected changes with valuable lessons ## 2024-07-25 - MQL5 Native Functions vs. Scripted Loops **Learning:** My assumption that a manual MQL5 loop over a pre-cached array would be faster than built-in functions like `iHighest()` and `iLowest()` was incorrect. The code review pointed out that MQL5's native, built-in functions are implemented in highly optimized C++ and are significantly faster than loops executed in the MQL5 scripting layer. The original comment stating this was correct. **Action:** Always prefer using MQL5's built-in, native functions for calculations like finding highs/lows over manual loops, even if the data is already in a local array. The performance gain from the native implementation outweighs the overhead of the function call. ## 2024-07-26 - Native ArrayMaximum/ArrayMinimum Efficiency **Learning:** Confirmed that native `ArrayMaximum()` and `ArrayMinimum()` are the preferred way to find extreme values in price arrays. Also, when using these functions, it's important to check if they return `-1` to avoid invalid array access, especially if the `count` or `start` parameters might be dynamic. **Action:** When replacing manual loops with native array functions, always include a check for the `-1` return value to ensure robustness while gaining performance. ## 2026-01-19 - Native Object Cleanup in MQL5 **Learning:** While iterating through chart objects manually is flexible, it becomes a major bottleneck if the chart has thousands of objects. For simple prefix-based cleanup (often used in indicators), the native `ObjectsDeleteAll(0, prefix)` is significantly more efficient than a scripted loop calling `ObjectName()` and `StringFind()` for every object on the chart. **Action:** Use `ObjectsDeleteAll()` for bulk object removal by prefix whenever the "keep N latest" logic is not strictly required or can be safely bypassed for performance. ## 2026-01-20 - Robust New Bar Check in MQL5 OnCalculate **Learning:** An early exit in `OnCalculate` based on bar time MUST check `prev_calculated > 0`. If `prev_calculated == 0`, the terminal is requesting a full recalculation (e.g., after a history sync or data gap fill), and exiting early would result in stale data. Also, using `iTime()` is more robust than indexing into the `time[]` array if the array's series state is unknown. **Action:** Always wrap "new bar" early exits in indicators with `if(prev_calculated > 0 && ...)` and prefer `iTime()` for the current bar's timestamp. ## 2026-01-20 - MQL5 OnTick Execution Flow Optimization **Learning:** Significant performance gains in MQL5 EAs can be achieved by carefully ordering the logic in `OnTick`. Moving the `PositionSelect` check before `CopyRates` and `CopyBuffer` avoids expensive data operations when a trade is already active. Additionally, reducing the requested bar count in data fetching functions to the absolute minimum (e.g., 2 instead of 3) and using `SymbolInfoTick` for atomic, lazy price retrieval further reduces overhead. **Action:** Always place 'gatekeeper' checks (new bar, position existence, terminal trading allowed) at the top of `OnTick` and minimize the data payload for indicator and price fetching to only what is strictly necessary for the current bar's logic. ## 2026-02-04 - Pre-calculating Trade Constants in MQL5 **Learning:** Significant performance gains in MQL5 backtesting are achieved by pre-calculating all derived trading constants in `OnInit()`. This includes inverse multipliers for lot steps and margin (to replace divisions with multiplications), combined clamping limits (merging symbol limits and user input limits), and fixed point offsets for SL/TP. These operations, while small, add up when executed millions of times in the tester. **Action:** Always scan `CalculateLots`, `CalculateSL`, and `CalculateTP` for expressions involving constant inputs or symbol properties. Move these calculations to `OnInit()` and store the results in global variables for rapid access in the `OnTick` path.