How do you debug and optimize your SAS code for faster performance and fewer errors?

1 Use the log and the debugger

The log is your best friend when it comes to debugging your SAS code. It shows you the messages, notes, and results of each step of your program, as well as any errors or warnings that may occur. You can use the log to identify the source and the cause of the problem, and to fix it accordingly. You can also use the debugger, a tool that allows you to run your code step by step, pause, resume, and inspect the values of variables and expressions. The debugger can help you find logical errors, syntax errors, or unexpected outcomes in your code.

2 Follow coding standards and conventions

To avoid errors and improve readability, it is essential to follow coding standards and conventions. These guidelines help you create consistent, clear, and well-structured code. For SAS, some of the common standards and conventions include assigning meaningful and descriptive names for variables, datasets, macros, and functions; using indentation, spacing, and comments for readability; using uppercase for keywords, lowercase for user-defined names, and camel case for mixed names; ending each statement with a semicolon; enclosing expressions and arguments with parentheses; and labeling and formatting data to document and display it.

3 Use macros and functions

Macros and functions are reusable blocks of code that can simplify and automate tasks, avoiding repetition and saving time. Macros are segments of code that are replaced by their contents when the program runs, while functions are predefined or user-defined operations that return a value. Through using macros and functions, you can perform calculations, transformations, or validations on your data; create dynamic variables, datasets, or parameters based on conditions or inputs; and execute common or complex tasks with less code and more flexibility.

4 Optimize data processing and storage

Data processing and storage have a direct impact on the performance and efficiency of your SAS code. To optimize them, consider using PROC SQL instead of DATA step for complex queries or joins, as it can be faster and more concise. Additionally, you can apply indexes, where clauses, and subsetting IF statements to filter and access your data more quickly and selectively. Compression, views, or temporary datasets can also help reduce the size and disk space of your data. Finally, consider using arrays, hashes, or lookup tables to store and retrieve data in memory rather than reading from disk.

5 Test and validate your code

Testing and validating your code is essential to ensure that it works as intended and produces accurate and reliable results. To do this, you can use sample data or subsets of data to check the logic and functionality of your code before running it on the full data. You can also use PROC PRINT, PROC MEANS, PROC FREQ, or other procedures to display and summarize your data and results, and compare them with your expectations or benchmarks. Additionally, PROC COMPARE, PROC CONTENTS, or other procedures can be used to compare and verify the structure and values of your datasets or variables. Lastly, error handling techniques, such as PUTLOG, SYMGET, or %SYSFUNC, can be used to capture and report any errors or warnings that may occur during the execution of your code.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?