Efficient Software testing – By Automating Test Data ... · !!!!!Automating!Test!Data!generation!!!!! 4! Current Solutions and Drawbacks This section will explain the solutions

Automating Test Data generation

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Running Head – Automating Test Data Generation

Efficient Software testing – By Automating Test Data Generation

Mayank Sinha

White Paper for Professional Writing (GEB5212: 01EA) Dr. Priscilla Berry

University Of Florida 4 April 2013


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Efficient Software testing – By Automating Test Data Generation

Author: Mayank Sinha

TestoLogic Inc. 2834, SW Archer Road, Gainesville, FL -‐32608


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Abstract

In order to improve the quality of the software and to reduce the high cost of manual testing, practitioners and researchers have tried to automate the date generation. The automation of test data generation increases the reliability of the testing process.

This paper will explore the importance of automating the “good” test data generation along with the sound remedy to achieve the goal of automation. To adequately understand the subject material, the paper will provide the information on importance of test data, current techniques of data generation and their drawbacks and today’s requirements. Introduction

A major component of software testing is generation of test data. In software development, 50% of the total cost is invested on testing (Abdelaziz M. Khamis et al., 2007). Automating the manual process of testing and data development could reduce this cost.

The creation of test data was used to be simpler by replicating the production data with the required edits. Government regulations are changing the way IT professionals should handle test and production data (Tom Jesionowski, March 2008). The increasing size and scale of modern data makes the method of using production data risky and expensive.

These forces are driving the requirement for more cost effective methods of high volume test data generation that provide accuracy, scalability, high performance testing environment, integrity and protection against data breaches. Importance of Good test data

This section will discuss the importance of test data. Also, this section will help in understanding and determining, if the test data is accurate and reliable for intense testing. Current Problems

This section will explain the existing problems with the manual testing and data generation. This section will discuss the following problems in detail –

1. Changing rules for test data 2. Inefficient Solutions – exposure to risk during testing 3. Reduced Scalability – Bad performance testing


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Current Solutions and Drawbacks

This section will explain the solutions used in industries today along with their drawbacks such as –

1. Use production data - Risk 2. Manual data generation - Cost and Time inefficient

Requirements of the New Era

This section will discuss about the requirements for generating good test data automatically such as-

1. To test complete and relevant range of data 2. To test scalability. 3. To test performance with high volume data. 4. To eliminate sensitive data 5. To test data against various environments.

We offer: DataGen – One Solution to multiple problems

DataGen was developed by TestoLogic to offer the remedy to the new emerging business requirements. It is capable of generating high volume of data with minimal human intervention. The developers have addressed all the problems discussed above offering the best possible solution software. Thus, increasing the cost effectiveness and reliability.

DataGen can create business data through GUI (Graphical User Interface) for various databases such as –

1. Microsoft SQL 2. Oracle 3. DB2

DataGen is designed to efficiently capture and manage the business and system

requirements as shown in Figure 1.


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Source: Meridian Technologies Figure 1. Fundamentals of Test and Data Management Additional Support

DataGen incorporates four additional functionalities, which provides remedy to the problems of Quality Assurance engineers. These functionalities are:

1. Drop validation: This module automatically tests the new software drop to be released after generating the relevant test data.

2. Performance testing: This module performs the performance testing of the

software determining the reliability and scalability.

3. Auto Installation: This module provides the functionality of installing the product without human intervention and performing any of the above modules.

4. Report generation: This module generates the report for data generation and for

all of the modules mentioned above. Conclusion For many years, test data has become the most critical component of testing. A thoughtful investment is needed to improve the software quality and to reduce the business risk. The automation of the data generation process will ensure scalability and repeatability. The appropriate automation choices will reduce the complexity and enable teams to focus on the actual task of detecting the defects before they become the customer problems. “Quality is never an accident; it is always the result of high intention, sincere effort, intelligent direction and skillful execution; it represents the wise choices of many alternatives.” (William. A. Foster)


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References 1. Tom Jesionowski, (2008). Safe, Realistic Test Data: The case for RowGen. Prime

Data Consulting. URL: http://www.iri.com/pdf/RowGen2-WhitePaper.pdf 2. Stephanie Chace, (2011). Test Data Management – Best Practices. Meridian

Technologies Inc. URL:http://www.meridiantechnologies.net/WhitePapers/TestDataManagement%20-%20BestPracticeV2.pdf

3. Jon Edvardsson, (2000). A survey on Automatic Test Data Generation. Dept. of

Computer and Information Science, Linkoping University, Sweden. URL:http://staff.unak.is/not/andy/MScTestingMaintenance0607/Lectures/SurveyAutomaticTestDataGeneration.pdf

4. K. Krishna Murthy, Janardhana S Channagiri, (2009). Test Data Management -

Enabling reliable testing through realistic test data. Infosys Ltd. URL:http://www.infosys.com/IT-services/independent-validation-testing-services/white-papers/Documents/test-data-management-strategy.pdf

5. Emina Torlak, (2012). Scalable Test Data Generation from Multidimensional Models.

U.C. Berkeley URL: http://people.csail.mit.edu/emina/pubs/testblox.fse12.pdf