API refers to a set of functions or classes or procedures that define the business logic layer. In other words, the API (application program interface) is a set of protocols, processes, routines, and tools that help to build critical software applications. It gives value to an application and helps people streamline their business processes. API testing services is necessary because if it doesn't work effectively and efficiently, it would be hard to convince your customer to adopt an application. To acquire the quality, instant ROI, time & cost savings, API testing becomes the challenging concept of the chain of software & QA testing to ensure that the digital lives will run seamlessly.
Types of Bugs that One Can Easy to Discover with API Testing:
- Security issues and multi-threading issues.
- Unused flags.
- Duplicate or missing functionality.
- Reliability issues & performance issues.
- Response data is not structured accurately (XML or JSON).
- Improper warnings/errors to a caller.
- Faulty management of valid argument values.
Read More: API Automation Testing
Test automation framework is a collection of tools used by software testing companies with following proper guidelines and set of rules to develop & design the test cases and test scripts, including preparing for the test recording.
Various types of automation frameworks are available to test different mobile, web & desktop-based applications on distinct testing platforms, servers, operating systems like Mac OS and Windows, etc. The rules that are developed for the test automation framework can be coding standards, processes, practices, concepts to handle the test data or safely store the test results. It allows us to test any business niche’s application with automated strategies. It includes several functions from test data, libraries to reusable modules for performing numerous test automation services such as functional testing, unit testing, smoke testing, integration testing, and regression testing.
Types of automation framework in testing:
- Linear Scripting Framework
- Modular Testing Framework
- Keyword-Driven Testing Framework
- Data-Driven Testing Framework
- Behavior Driven Development Framework
- Hybrid Testing Framework
- Test Library Architecture Framework
Read In Detail: Benefits Of Automation frameworks
Data crunching is a method that is used to cover the analysis of data and make useful decisions from the vast amount of data and information (big data) if possible. It also refers to the early phase of data processing in which fresh data sets or disorganized data sets are crushed to meet proper research and exploration. It includes planning, system modelling, or application that is being used. Data is everywhere, and it is sorted, processed, and maintained in a structured form before performing iterations or running algorithms. The data which is already processed and imported into one system known as the crushed data.
Why Need of Data Crunching Techniques:
You can consider data crunching for the following situations:
- If you have a lot of data and there are too many complications, you can then break that data into the available list and represent in just a few lines.
- If unit testing gives you aggression while producing the correct output, you can think of data crunching and perform the process in many cases.
- When the enterprise-scale infrastructure doesn’t support well or when it is impossible to make the system compatible with hundreds of thousands of servers.
- If the issue occurs due to the speed of the disk, your network, or database, on that point, you can consider the basic program rather than the trickiest codes.
Read More about Tools: Data Crunching
From QA managers to testers, everyone in the testing team highly uses exploratory testing in agile because it gives them the freedom to investigate, discover, and
learn many things while working on any business project.
Importance of Exploratory Testing in Agile
The agile is new normal for all latest software testing because it includes short sprints of about one month, and the tight deadlines are setting up to complete the
project on-time. Agile plays a vital role in exploratory testing because its focus is to give speedy deliveries and meet consumers' demands in a limited period. For
this, the testers have to understand customers' requirements before using their skills and intuitions for testing.
Popular Exploratory Testing Tools:
- Test Studio
- JIRA Capture
- Session Tester
Read More: Benefits Of Exploratory Testing
To meet the digitally equipped customers' expectations, every industry is relying on Quality Assurance (QA). Similar goes for the banking sectors, consumers want the best of their services, and digital transformation in banking is picking up the pace. Banking digital transformation will result in increased data transparency, removal of intermediates in the process, and fast and secure methods to access financial and intellectual data.
Digital transformation in banking can automate numerous manual operations, which in turn enhances customer satisfaction. With the combination of Artificial Intelligence (AI) and the Internet of Things (IoT), banks can collect and analyze personal data of the customers and create more personalized offers for clients.
In today's time, bank applications have become more complex and interconnected to provide flexibility, transparency, and speed. Quality assurance helps to bring best out of this banking digital transformation with the help of reliable testing tools while achieving high-cost savings through fully managed or automated testing services.
Read the blog to know how quality assurance helps to bring the best out of this banking digital transformation.