What is software testing?
Delphix transforms software testing methodologies
Software testing is a method of assessing the functionality of a product or service under test. The intent is to evaluate various properties of interest from efficient design to program usability. Typically, software testing involves finding bugs - errors or other defects - in the software; however, the overall process can provide insights into not only the quality of the software but also the risk factors for its users and sponsors. Software testing is a necessary component for firms to guarantee the reliability and subsequent end-user satisfaction of their software.
What is software quality assurance?
Software quality assurance involves the set of activities that guarantee the implementation of processes, standards, and procedures for developed software. This encompasses the entirety of the software development life cycle and represents a range of preventive measures. Many times, the concepts of quality assurance and quality control are evaluated against each other. While they both involve a level of assessment, software quality assurance is process-oriented as opposed to product-oriented, and focuses on creating the foundations for which developed software meets standardized quality specifications.
Types of software testing
Software testing is a crucial step in the development cycle, and depending on the need, different types of testing are needed when evaluating the software. Among these types, the most common include the following: unit, integration, performance, quality assurance, and user acceptance software testing.
Unit Testing – a process performed by software developers, where units of source code are tested (e.g. statements and functions). This approach tests the smallest, testable parts of an application to evaluate its internal structure or inner workings. Unit software testing is commonly a candidate for automation.
Integration Testing – a process that tests the connectivity or interaction of the individual components of an application. This approach necessarily builds upon the results of unit software testing.
Performance Testing – a process that focuses on testing the quality metrics of software. In this case, this type of testing differs from functional software testing in that it prioritizes evaluation of attributes beyond base functionality (e.g. stability and reliability).
User Acceptance Testing – a process performed by end users on developed features or components of an application. This approach focuses on whether the software is aligned with both present business operational needs and with other previously dictated requirements.
What is test data?
Test data is the data, or input, provided to a software program for usage in a variety of testing purposes. These purposes can be either confirmatory or destructive. In the case of confirmatory software testing, test data can be used and evaluated to generate an expected result. On the other hand, destructive testing with test data intends to test application performance in situations that demand unusual or extreme responses.
In reference to the test data above, the various phases of software testing require their respective types of test data. These phases can include subsetting, data masking, and synthetic data creation.
Subsetting – takes full production data and creates smaller representative sample of the data. The intent is to save on storage requirements and theoretically, smaller datasets are more portable and easier to test.
Synthetic Data – creates artificial data that resemble what a production application will encounter in a real environment.
Data Masking – produces structurally similar but masked real-life data without introducing unsafe levels of risk.
Automated software & data testing tools
Automated software testing tools provide a level of maintenance and repeatability of software upkeep. The testing tool software is separate from the software being tested, and controls the execution of phases in the testing cycle with previous iterations. Steps in the overall testing process can be exhaustive or require significant user effort, but test automation helps automate some of these more time-intensive, repetitive tasks. This is especially important in organizations hoping to move towards agile or continuous delivery. The most popular offerings for automated data testing include the following: HP, IBM, Micro Focus, Microsoft, Sauce Labs, ThoughtWorks, and Tricentis.
While these tools provide different levels of automation in the software testing cycle, the delivery of the test data itself still requires both significant time and manual effort. However, data virtualization, or virtual data, provides this missing automation. By masking test data in non-production and provisioning virtual copies, virtual data allows for the delivery of full, masked copies of data into downstream environments. Additionally, these copies represent complete, fresh copies of production, so teams no longer need to rely on subsetting and synthetic data for their testing. With virtual data, teams can improve their software testing cycles and accelerate application development.