Blog

Big Data model as a means of testing web-based applications

Testing is a process of execution of the program to detect defects. The testing process of not only new but also earlier codes that are written during the previous iterations of development is called regression testing.
21 October 2014
Big data testing
Web app testing
The article by a1qa
a1qa

Testing is a process of execution of the program to detect defects. The generally accepted methodology for the iterative software development Rational Unified Process presupposes the performance of a complete test on each iteration of development. The testing process of not only new but also earlier codes written during the previous iterations of development, is called regression testing.

It’s advisable to use the automated tools when performing this type of testing to simplify the tester work. “Automation is a set of measures aimed at increasing the productivity of human labor by replacing part of this work, the work of machines”. The process of automation of software testing becomes part of the testing process.

The requirements formulation process is the most important process for software developed. The V-Model is a convenient model for information systems developing. It’s become government and defense projects standard in Germany.

The basic principle of V-model is that the task of testing the application that is being developed should be in correspondence with each stage of application development and refinement of the requirements. One of the development model challenges is the system and acceptance testing.

Typically, this type of testing is performed according to the black box strategy and is difficult for automation because automated tests have to use the application interface rather than API. “Capture and replay” is the one of the most widely used technologies for web application test automation according to the black box strategies today. In accordance with this technology the testing tool records the user’s actions in the internal language and generates automated tests.

Practice shows that the development of automated tests is most effective if it is carried out using modern methods of software development: it is necessary to analyze the quality of the code, merge into the library the duplicate codes of tests, which must be documented and tested. All this requires a significant investment of time and the tester should have the skills of the developer.

Thus, the question arises of how to combine the user actions recording technology and the manually automated tests development, how to organize the automated tests verification, and whether it is possible to develop an application and automated tests in parallel according to the methodology of the test-driven development (TDD).

There are systems capable of determining the set of tests that must be performed first. Such systems offer manually associate automated tests with the changes in the source files of application under test. However, the connection between the source and the tests can be expressed in terms of conditional probabilities.

The probabilistic networks used in the artificial intelligence, could also be useful when defining the relations automatically based on the statistics of tests results. By using Big Data networks we can link interface operations and test data and this will allow reducing the complexity of automation.

Get the full artilce here.

More Posts

The year in valuable conversations: recapping 2023 a1qa’s roundtables for IT executives 
8 December 2023,
by a1qa
3 min read
The year in valuable conversations: recapping 2023 a1qa’s roundtables for IT executives 
From dissecting novel industry trends to navigating effective ways of enhancing software quality — let’s recall all a1qa’s roundtables. Join us!
Big data testing
Cybersecurity testing
Functional testing
General
Interviews
Performance testing
QA trends
Quality assurance
Test automation
Usability testing
Web app testing
30 July 2021,
by a1qa
4 min read
Big data testing 101: the complete guide
Check out three QA practices to ensure well-organized big data systems and high data quality.
Big data testing
30 November 2020,
by a1qa
5 min read
Acumatica: ensuring sound business operations with well-tested ERP system
Internal business activities are advancing, while ERP systems’ usage is growing rapidly. Explore how to ascertain their accurate work through timely applying QA.
Big data testing
Cybersecurity testing
ERP testing
Functional testing
Performance testing
Test automation
28 October 2020,
by a1qa
5 min read
eHealth software testing: taking the digital Hippocratic oath
Medicine has broken new ground. However, there’s still no room for errors. Get to know more information about effective testing approach in the health sector. 
Big data testing
Functional testing
Performance testing
Test automation
27 May 2020,
by a1qa
5 min read
Following six main 2020 retail trends with QA
In this article, we are talking about how QA supports prime retail trends.
Big data testing
Localization testing
QA trends
20 February 2020,
by a1qa
6 min read
Finding technologies value during digital transformation journey
To develop and make a good profit in the context of digital transformation, businesses have to follow the trends in this area. Make sure you know how technologies can help in the process of digital transformation.
Big data testing
Blockchain app testing
Cloud-based testing
IoT testing
7 January 2020,
by Performance R&D
6 min read
How to enhance performance of your web software product?
In this article, we are highlighting the aspects that can help get an objective picture of the performance health of your software product and make it more high-quality.
Performance testing
QA consulting
Web app testing
18 September 2019,
by a1qa
4 min read
Client-side performance: make your end users stay
Let's have a wider look at performance testing and discover how client-side testing can improve the customer experience of a software product.
Performance testing
Web app testing
21 January 2019,
by a1qa
5 min read
IT trends that will shape the face of QA in 2019
We’ve rounded up the top 11 tendencies that will determine the future of testing in 2019 and beyond.
Agile
Big data testing
Cloud-based testing
Cybersecurity testing
IoT testing
Performance testing
QA trends
Test automation

Get in touch

Please fill in the required field.
Email address seems invalid.
Please fill in the required field.
We use cookies on our website to improve its functionality and to enhance your user experience. We also use cookies for analytics. If you continue to browse this website, we will assume you agree that we can place cookies on your device. For more details, please read our Privacy and Cookies Policy.