QASource Blog

Blockchain, the technology supporting cryptocurrencies, seems to be the driving technology for the next generation of Internet. Blockchain is a novel solution to the age-old problem of trust. It allows to trust the outputs of the system without trusting any institutional body in between. As techies and experts contemplate the potential ramifications both good and bad, lets talk about more about test automation part of it.

Since few years, we have witnessed that big data has become a vital component in banking, healthcare, retail, education, and research domains. As an end user, we are consuming as well as producing data. This information is processed by various applications for analysis, predictions, and decision-making. Enormous growth, efficiency and performance of big data applications can make a huge impact in our daily lives.

Data science is pertinent to many fields including finance, social media, security, healthcare, defense, medicine, economics, marketing, fraud detection, geolocation, and many more.

During different phases of Data Science, data is discovered, conditioned, extracted, compiled, processed, analyzed, interpreted, modeled, visualized, reported, and presented regardless of the size of the data being processed to have some actionable items to be used for business purposes.

In this newsletter, we bring you the concepts that help us to gain insight into Data Science and its trends, Data Science types, Machine Learning Life cycle so that you can have good understanding about it.

As per many software testing experts, code coverage is a good way to identify the untested code. But the percentages aimed do not necessarily contribute to test quality. Such coverage goals encourage poorly designed tests, written with the only intention of meeting system requirements instead of testing the software correctly. We agree that unit testing is important but when aiming at quality its limited. A useful alternative is functional test coverage through test automation, which tracks whether tests execute important values or sequences of values corresponding to software features.

Enterprise Content Management is a kind of revolution which not only makes centrally stored files secure, allows document versioning, and content search, but also provides a provision to manage them easily. The Enterprise Content Management can be on cloud or setup locally. Stored files can be official documents in .xls, .doc, .ppt, .pdf file formats or multimedia files like video clip, audio file, and many more. SharePoint, Google Drive, Dropbox, and Box are some of the central storage repositories. Storing heavy files in bulk is of no use if it delivers at a slow pace. Hence, performance testing is required to verify the functionality under heavy load, session management, and stress capabilities. This time, we avail an opportunity to share our experience with Enterprise Content Management system.

Keep exploring more on performance testing with our quarterly performance testing newsletters.

Continuous integration is a practice to test every change of code done in repository. Further, the process of Continuous Deployment of builds help in achieving the Sprint targets on time. Faster builds speed up the whole system and minimize the integration issues.

As a conclusion, we can say that Continuous deployment of builds save time for both Dev and QA teams.