Home Scripting Script Enhancements

Script Enhancements

Script enhancements are performed on recorded scripts to make them reusable, maintainable, parameterized and correlation enabled. Enhancements ensure that scripts can simulate real user behavior and support different test scenarios and load conditions.

Make Script Reusable

Parameterization, correlation and reusable functions.

Improve Performance

Reduce unnecessary traffic and optimize transactions.

Increase Reliability

Handle dynamic data, avoid errors and test consistently.

Support Scenarios

Data driven scripts for multiple users, scenarios and loads.

Maintainable Scripts

Clean, modular and easy to maintain scripts.

Enhancement Areas (What & Why)

Area What We Do Why We Do It Example
Parameterization Replace hard coded values with parameters Make script data driven and reusable {userID}, {password}
Correlation Extract dynamic values using rules/regex Handle dynamic content and maintain session OrderID, SessionID
Think Time Add realistic delays between user actions Simulate real user behavior Random/Fixed think time
Transactions Define transaction start and end points Measure accurate response time StartTransaction("Login")
Rendezvous / Sync Synchronize virtual users at specific points Simulate real world user behavior rendezvous points
Checks / Assertions Validate server responses and content Ensure application correctness Response code, text checks
Error Handling Handle errors and continue or stop Avoid script failure and better logging Try/Catch, On Error Continue
Modular Functions Create reusable functions/actions Improve maintainability login(), search(), logout()
Data Management Use external data files / DB / Parameters Handle large data sets efficiently CSV, Excel, DB, Parameters
Logging & Reporting Add logs for key events and validations Easier debugging and analysis LogMessage, Log Status

Tool Wise Enhancements Overview

HP

LoadRunner

C / C++ based scripting

  • Parameterize data using Parameter List.
  • Correlate dynamic values using web_reg_* functions.
  • Add think time using lr_think_time().
  • Define transactions using lr_start_transaction() lr_end_transaction().
  • Add checks using web_reg_find(), web_reg_save_param().
  • Use custom functions and reusable actions.
  • Enhance using vuser_init(), Action(), vuser_end().
  • Generate test data using data files / databases.
JMeter

JMeter

Java based open source tool

  • Parameterize using User Defined Variables / CSV Data Set Config.
  • Extract dynamic values using Regular Expression Extractor / JSON Extractor / XPath Extractor.
  • Add timers (Think Time) – Constant / Uniform / Gaussian Random Timer.
  • Add Assertions – Response Assertion, Duration Assertion.
  • Use Transaction Controller for transaction.
  • Use Pre Processors, Post Processors, Listeners.
  • Use Beanshell / JSR223 for advanced logic.
NeoLoad

NeoLoad

Scriptless / Coded hybrid approach

  • Parameterize using Data Sources (CSV, DB, Excel).
  • Correlate using Dynamic Variables & Extractors.
  • Add think time using Pacing Profiles.
  • Define transactions using Transaction Points.
  • Add checks using Verification Points.
  • Use scenarios and reusable actions (User Paths).
  • Enhance using JavaScript / Custom Code.
  • Data management using Data Sources.

Side by Side Comparison

Enhancement LoadRunner JMeter NeoLoad
Parameterization Parameter List, lr_eval_string() User Defined Variables, CSV Data Set Config Data Sources (CSV, DB, Excel)
Correlation web_reg_save_param(), web_reg_save_param_ex() Regex Extractor, JSON Extractor, XPath Extractor Extractors, Dynamic Variables
Think Time lr_think_time() Timers (Constant, Uniform, Gaussian Random) Pacing Profiles
Transactions lr_start_transaction(), lr_end_transaction() Transaction Controller Transaction Points
Checks / Assertions web_reg_find(), lr_assert() Assertions (Response, Duration, Size) Verification Points
Data Management Data files (dat), DB, Parameter List CSV, Excel, DB, Variables Data Sources (CSV, DB, Excel)
Error Handling On Error Continue, lr_error_message() Assertion Results, If Controller, Try Catch Error Handling Blocks
Logging lr_output_message(), lr_save_string() Listeners (View Results, Summary, Logs) Logs, Monitors, Reports

Detailed Enhancement Examples

1. Parameterization
Replace hard coded value with parameter.
web_set_header("UserID", "12345");
web_set_header("UserID", lr_eval_string("{UserID}"));
2. Correlation
Extract dynamic value.
web_reg_save_param( "OrderId", "LB=<orderId>((^|*))<", "RB=</orderId>", LAST);
3. Think Time
Add realistic delay.
lr_think_time( rand(3, 7) );
4. Transaction
Measure response time.
lr_start_transaction( "PlaceOrder"); // steps lr_end_transaction( "PlaceOrder", LR_AUTO);
5. Check / Assertion
Validate response.
web_reg_find( "Text=Thank you for your order", LAST);

Best Practices

  • Parameterize all input data.
  • Correlate all dynamic values.
  • Use realistic think time.
  • Create modular and reusable functions.
  • Add checks and assertions for validations.
  • Use external data sources for large data.
  • Log important events and errors.

Common Pitfalls

  • Hard coding values in scripts.
  • Missing correlation causing script failures.
  • Using fixed think time everywhere.
  • Improper transaction boundaries.
  • Hard coded data in multiple places.
  • Ignoring error handling and validations.

Outcome

  • Reusable and maintainable scripts.
  • Accurate performance results.
  • Realistic simulation of user behavior.
  • Support multiple scenarios and loads.
  • Reduced maintenance effort and time.