Data Driven Framework - An Introduction, Data Driven Framework Tutorial

Framework is a term we hear a good number of times in discussions about software development and testing. Framework is nothing but a set of guidelines or best practices which will help to execute developing or testing smoothly and effectively. There are different types of frameworks and the major ones are

  • Linear framework
  • Keyword driven framework
  • Data driven framework
  • Hybrid framework

Of these different types, Data Driven framework is the most widely used and the most important part of any Hybrid Frameworks.

It may not always be possible to test an application with all possible options and to execute a test with all possible values. Here is the need for a mechanism to run the tests with different data or same data. Data driven framework comes to help in such a situation and it is the significance of this type of framework.

In data driven framework, the test data is driven by data files such as Excel files, Text files etc. In other words, when you use data driven framework the input and output values for tests will be fetched from the data files. This data can be entered manually in the data file or can be generated automatically with test scripts.

Advantages of Data driven Testing (Data Driven Framework)

Following are the advantages of Data driven testing.

  • The test scripts can be prepared even when the developmental procedures are still in progress.
  • Unnecessary creation of duplicate automated test scripts and redundancy can be reduced with the modular type of design and by using files or records both for inputs and for verifying the data.
  • Only the test script related the specific business function needs to be changed in case of any changes in the functionalities.
  • Valuable information including input, output and expected results etc can be stored as text files which are easy to manage.
  • This framework offers better error handling which results in robust test scripts.

Disadvantages of Data driven Testing

Following are the major disadvantages of data driven testing.

  • Demands high expertise of scripting languages.
  • Many data files are needed for each test and there will be many data inputs and there will be a need for constant verification. Hence there is a need to keep the data files in different directories.
  • Re-entering the test plan data in various concerned data files and managing test plan data needs a lot of talent and expertise. Hence a project manager is required.
  • We should take extra care while using text editor such as notepad for creating and maintaining data files to save them in the right format, failing which many error reports may be generated.

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