4 Debugging & Diagnostics

Debugging and Diagnostics Methods

Logicytics employs several methods to enhance its functionality and user experience. These methods contribute to efficient data collection, troubleshooting, and customization of the tool.

1. Live Feedback

Live feedback is a crucial feature in Logicytics that provides immediate insights into the application's behavior during execution. This method is essential for:

• Early identification of issues in the development process
• Real-time monitoring of system performance metrics
• Outputting logs to the console for instant visibility
• Providing immediate feedback on actions taken by the program

Users should always check the default log for any errors or warnings related to the project itself, rather than their specific use case - So if a error is due to a missing file, and it actually doesn't exist, Then it's not a problem with the code, but the use-case itself, However, if the error is a crash or a bug or something false, then it's a problem with the code.

2. Debug Mode

Debug mode extends the live feedback mechanism by offering more detailed information during runtime. Key features include:

• Providing extra insight into the main program execution
• Aiding developers in understanding how their code is running

To activate Debug mode:

[Settings]
log_using_debug = true

Note: This file is found in the config.ini file in the CODE subdirectory.

This configuration change enables DEBUG level logs, offering deeper insights into Logicytics' operations.

3. Debugger

The debugger component is a powerful tool for analyzing the state of Logicytics at various points in time. Its primary functions include:

• Checking file integrity to ensure consistency across the codebase
• Verifying updates to maintain the latest version of the software
• Analyzing the operating system and external factors affecting application behavior

To run the debugger:

python Logicytics.py --debug

This command generates a special DEBUG log, providing comprehensive information for troubleshooting and issue reporting.

These methods collectively contribute to Logicytics' robustness and user-friendliness, making it an effective tool for data collection and system analysis in various contexts.