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How Will 2020 Shape Up For Software Quality Assurance
The IT industry is witnessing rapid changes with new technologies and methodologies playing an important role in developing quality products at faster turnarounds. Software quality assurance has become an integral part of the whole Software Development Life Cycle (SDLC). It involves evaluating the performance of the system components based on a slew of parameters. Furthermore, with Agile and DevOps software development (and testing) methodologies becoming the norm, software quality assurance needs to keep up with the changing times. It needs to ensure the quality of a software application remains top-notch in terms of performance, usability, security, and functionality, among others. Let us discuss the QA software testing trends that are going to dominate in the year 2020.
# Big data testing: Many IT processes belonging to verticals like healthcare, banking, telecom, retail, etc., generate a huge quantum of data at high speeds. These need to be tested for integrity, consistency, and redundancy. Testing of such data is important in terms of evaluating the functionality and performance of applications. Also, since these data are leveraged for decision making, they need to be optimized, segmented, and validated. The challenges of big data testing are about the requirement of time and resources. The year 2020 might see the introduction of platforms that can mimic the behavior of various layers of application data.
# DevOps Testing: With requirements like Continuous Delivery and Integration, the DevOps model of software development and testing has been adopted by many organizations. The model calls for an increased synergy between the development and QA teams. Here, any
software testing company needs to implement test automation to execute DevOps testing in the development sprint. It helps in the quick development of a glitch-free software that delivers better user experience and improves ROI for the business.
# IoT Testing: The growth in smart devices has been phenomenal and is likely to touch a figure of 20.6 billion by 2020 (Source: Gartner). Since these devices have embedded software applications to perform a slew of activities, these need to be tested thoroughly. The quality assurance software testing services undertaking IoT testing validate the quality of embedded applications on parameters like security, functionality, usability, and trustworthiness. In doing so, they face challenges related to the monitoring of operating systems and communications protocols, and the possible combination of elements that are part of the IoT environment. In 2020, IoT testing might involve the following:
Validating the compatibility of devices, their versions, and protocols
Monitoring the delay in the connection of elements
Safety, security, and scalability of components
# Security Testing: Digital transformation encompassing increased connectivity of devices has brought the spectre of security threats. According to statistics, cybercrime is likely to cost the world more than $6 trillion by 2021 (Source: Herjavecgroup.com). Thus,
security testing will arguably become the key focus area for any QA testing services company. It will incorporate vulnerability assessment and testing, penetration testing, and chance appraisal to ensure the modules and hubs in an application framework do not get ruptured. Furthermore, the security need will involve actualizing the measure of security layers and the incorporation of DevSecOps in the SDLC. According to the latter, security becomes the shared responsibility of everyone in the organization, notably Development and Operations.
# Testing Centre of Excellence (TCoE): Enterprises have been looking at establishing TCoEs to develop standard protocols, formats, frameworks, and tools for testing. The growing need for quality applications with faster turnarounds has necessitated the setting up of TCoEs.
# Performance Engineering: As opposed to merely testing the performance of a product and its components, the trend now is to focus on parameters such as customer value, throughput, memory usage, latency, quality of configuration, the practicality of usage, and convenience, among others.
# AI Testing: AI and ML have slowly made their way into the IT infrastructure of today and are going to consolidate their presence even further. In 2020 and beyond, AI and ML will be utilized in testing to attain objectives such as:
Predicting test configurations based on the previous checks
Identifying checks to be executed automatically
Identifying high-risk areas in applications to prioritize regression tests
The changing dynamics of business and shifting customer preferences have necessitated software testing to change as well. With manual testing increasingly giving way to automated testing, the year 2020 will witness a hybrid of these two types of testing. Furthermore, the year 2020 and beyond will have an increased role of the QA department and companies that do not include QA in their scheme of things are going to falter big time.
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