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Test Data & Tools Available

January 13, 2017
Qa tools, qa test, qa data

The QA data can be specified as the documented data which are used for Software/Application testing. The test data is the input data of any kind of QA test prepared by QA tools. They can be done in any format like  XML test data, SQL QA data, system test data etc… The design of test data is important as they determine the behavior of the system for correct, valid or invalid inputs. They ensure the adequate design of the QA test scenario. 

Types of Test Data QA tools

The QA data can be classified into 5 types based on the purpose of test cases generated. The execution of test cases will complete only by using the proper QA data.

  • Valid Test Data: The test data which verify whether the functions of the software gives the expected result with the input. A valid data should give a valid output.
  • Invalid Test Data: The test cases accept the invalid test data i.e acceptance testing to ensure that the software responds properly when the input is wrong. Should show the proper error messages, notify the user the invalid data and should explain the validation process, the expected result etc..
  • Boundary Test Data: The boundary value analysis is processed by using boundary test data. These are most common when the range of float or integer values are checked.
  • Wrong Data: While entering wrong data to a QA test case execution the software should respond with the correct error message. This should cause a no response or wrong result.
  • Absent Data: Blank data for specific fields in the functioning should show the proper error message and validation messages. How the system reacts to the blank data is important as blank data will affect the expected result as a whole and the entire functionality.

Test Data Creation

The creation of test data can be carried out in different ways as given below:

  • Manually
  • Copy production data to the QA test environment.
  • Copy test data from the client system to the QA test environment.
  • Generate test data using automation QA tools.

Generating test data before starting the execution phase is important as the process of data creation is time-consuming. The test data creation process requires many pre-steps to get prepared for the execution.

QA Data Creation for Performance Testing

Performance testing process makes sure the behavior of the application to the real-time data. For the performance evaluation, the test data creation mainly focuses on detecting the bottlenecks.

The performance testing for e-commerce websites is a tedious task when comes to designing the QA test data. The security constraints and sensitive data from the customers should be considered while creating test data. Should make use of anonymous data for sensitive customer data like SSN, credit card number, bank details etc..

QA Test Data Creation for Security Testing

Security Testing is the process which measures how effectively the system protects from mischievous data. The test data designed for the measure of security is associated with the concepts like Authorisation, Authentication, Data Integrity, Data Confidentiality.

Authorisation: Specifies the user roles and privileges. The QA test data should be created based on the operations designed and should valid for the authentication.

Authentication: Here the identity of the user is specified. Test data is created as the combinations of username and password which ensures the user is authorized to use the application. Invalid data will be hecelpful to measure the security features of the system.

Data Integrity: Check the data integrity by creating QA data after a detailed study of the design, code, databases, and file structure. The test data is more attached to the functionalities of the Software.

Data Confidentiality: The test data created should be capable of ensuring the strict confidence of the user data. The data encryption and decryption processes should be verified to avoid any chance of data leakage.

Test Data Creation for BlackBox Testing

BlackBox Testing tests the overall functionality of the software without penetrating into the internal structure or working. So the QA data created for BlackBox testing will depend merely on the validity(valid or invalid) of data, void data, the user acceptance criteria, data for field validation, data for module integration etc..

Test Data Creation for Whitebox Testing

Whitebox Testing tests the internal structures or working on the application. The test data created should be associated with the coding style, logical flow, source code paths etc..The test data created may also depend on the parameter creation for calls to functions.

There may arise some cases of excess memory usage rather than expected while the execution. Such cases may arise due to the repeated calls to the functions. This kind of coding mistakes can be detected by using correct data for testing.

Automated Test Data Generation QA Tools

The automation QA tools for test data creation helps to speed up the process and to generate high volume data with accuracy. To fill the database with the real-time QA  data, data generators can be used with help of QA tools.

DTM Data Generator

SQLEdit is the Vendor of DTM Data Generator. The QA tools automatically fill the Database with data. The purpose of the QA tools is to generate data values and objects like tables, views, procedures, triggers etc..

There are available extra data sources like the databases, Excel spreadsheets, XML documents, CSV files, Web resources etc.. The QA tools help to load data directly into the database and output will be generated in the formats SQL, text, XML or JSON.

GS Data Generator

GS Data Generator by GSApp is the data generation QA tools helps the QA experts to create test data. The QA tools help to create industry specific data for the demo. The most important feature is data privacy by creating a clone of the existing data.

                                                                                                        

YDE Data Generator(YAN Data)

This is a free, online test data generator QA tools. The tool generates 10000 rows of data in various file formats like CSV, Excel, SQL, JSON, HTML, XML.

The online QA tools accept the specifications from the user and create mock data randomly generated. The format selected on the home page will accept to create the file with randomly generated data.

                                                            

How to prepare proper QA Test Data?

Test data creation is a part of preparing test setup. The software and hardware requirements should be analyzed and set using the predefined data values.

According to the testing requirements, the test data values should be set. This will help to develop and execute the exact test cases. The tester should be responsible for creating the test data for every test cases. The test data generated should be double checked for the sufficiency of all the possible test cases related to the module.

Sometimes, it may need to reuse the same set of test data for similar scenarios. The testers are advised to keep the copies of their test data before appending to extra data as per the requirements.

More than one tester may responsible for accessing the same resources and the data may get appended repeatedly. The QA data append to existing data should be kept as unique copies for future references.

The live environment test data will be more effective than dummy data created while QA data development. The availability of live data will demo a smooth functioning of the application for valid inputs.

Conclusion

To conclude, the development and execution of effective test cases result from a data set of perfectly generated test data.

The data values generated manually will have the power to anticipate the possibility of test cases to be executed in future. Automated QA data generators make possible a time-bound generation of test data in a specific format.

The testers should provide the exact prerequisites for generating data. The QA tools implemented will be helpful to generate significantly highlighted large volumes of similar data. The bulk volume data requirements for performance, functional, load/stress testing can be achieved by the automated QA tools.

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