The rise of new technologies is leading us to develop innovative solutions to make our lives easier. Most of the innovation we see today is about making breakthroughs to support client demands and end-user needs. As expectations increase, so too do the stakes for organizations to meet demands with superior quality and within ever-shrinking timelines. To cope with testing expectations and current scenarios, new emerging technologies, such as artificial intelligence, machine learning, can help us meet the quality needs of the future.
With this new digital era, the need for quality and agility is a top priority across all industries. This also calls for robust product and system testing. Over the past few years, software testing has undergone a significant transformation. In this blog, I will introduce our new services for quality engineering EvoQE.
Evolution of testing practices (Verification and Validation)
On the software front, until about 40 years ago, the primary method of testing was manual testing. From the 1980s, the focus gradually started shifting to automated testing. In 1990s, the agile methodology of development emerged giving momentum to increase automation in testing. From the 2000s and the rise of the internet era, a plethora of technological choices have led to the development of several automation tools for both functional and non-functional areas of testing.
Apart from traditional black-box testing, there has been a constant evolution in white-box testing as well with the rise of SDET (Software Development in Test). This is now crucial with the rise of a new concept – the “Shift Left” in testing. “Shift left” is the practice of finding and preventing defects early in the software delivery process. This can be achieved by various means, including static code analysis, dynamic code analysis, and unit testing, during the development stage itself.
In the automation industry, hardware-in-the-loop (HIL), software-in-the-loop (SIL), and model-in-the-loop (MIL) solutions make it possible to validate the developed solution with simulations of real-time situations. As the complexity of electronic control units (ECUs) increases, the number of tests required increases as well. With the older testing practices, one had to wait for the controller design to be integrated into the final system before the system issues could be identified. Hardware-in-the-loop testing simulates sensors, actuators, and mechanical components in a way that connects all the I/O of the ECU being tested much before the integration, thereby accelerating the design and enhancing the quality. This also reduces the need for real prototypes and physical tests.
Over the past 10 years, new frameworks such as Behavior Driven Development (BDD) and Test-Driven Development (TDD) have gained prominence. As more and more technological changes occur, more of the testing is automated; right from the actual process of testing to the automation of the development process.
On the mechanical front, advanced equipment and tools are being developed for performing tensile stress, compression, flexure, and impact testing, among others. The evolving list of standards and reliability testing has led to the rise of improved quality in mechanical testing.
Another concept that has become significant in the last 10 years is the rise of DevOps. DevOps is a set of software development practices that combines software development (Dev) and information technology operations (Ops) to reduce the systems development lifecycle. DevOps improves the QA process as all the teams work in collaboration. This brings the testing and development process in coordination, ensuring software quality and helping reduce time to market. In DevOps, with the focus on automation through continuous integration tools, the role of the QA team is to ensure that the application is receiving comprehensive testing in the areas that are crucial, identify all opportunities for automated tests, and manage manual testing needs.
Quality engineering for the new digital era
As per the World Quality Report (WQR) 2018–2019, companies are harnessing use of analytics for intelligent automation, predictive analytics, and more for self-learning cognitive platforms. For an industry viewpoint, the automotive sector is scaling up with the adoption of agile, automation, and DevOps. The energy and utilities sector will see greater adoption of digital, analytics, and IoT in the coming years. For healthcare and medical devices, digitalization and smart automation are going to be the key drivers. As per the Nelson Hall market assessment (2018), the adoption of big data in the form of open source software and data visualization tools coupled with digital transformation are going to be the biggest disruptors in coming future.
To succeed in this new era, Capgemini offers a range of next-generation solutions for emerging trends to transform product and system testing into an insight-driven, quality-engineering function. Our solutions such as TestVox and CodeVox use analytics and AI, immersive technologies, robotics, and automation to enhance testing. CodeVox is an analytics and machine learning model that factors data from repositories such as code reviews, requirement management, defect management, and static code analysis, to determine the riskier source files/components. TestVox is the model that leverages the data from test, defect, requirements, project repositories along with CodeVox recommendations to perform test selection and prioritization.
Our robotic automation, digital tester, and connected product solutions for product and system testing offer a new testing experience, with best digital technologies improved test strategy for end-to-end test automation. Our managed testing services are provisioned through customer-centric, right–shore test labs and operational environments providing significant cost benefits.
With a combination of traditional forms of testing coupled with these cutting-edge services for newer emerging trends our Product and System testing group is placed to aid in the continuous evolution of quality engineering in the coming decade.
Ajit Rajshekar, Senior Manager with over 14 years of Verification & Validation experience, mainly in the Product Engineering domain (Healthcare) now working as part of a V&V Center of Excellence group with primary focus on Test Automation and the use of cognitive intelligence within testing.
As Senior Director – Technology in Verification & Validation Practice, Vivek Jaykrishnan is responsible for developing service offerings for multiple industries across Product Engineering verticals.