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As we near the conclusion of 2018, we are also looking ahead at what is advancing in the engineering automation space. It’s clear that pressure continues to increase on businesses to deliver more, quality digital products within shorter cycles. They must also deliver awesome customer experiences, manage rising complexity, and anticipate continuous market changes. Fortunately, there have been significant advancements in new automation technologies, so organizations can deliver solutions faster without compromising on product quality.
Advances in Automating Software Testing
As digital transformation drives the need for faster cycles in software development, the process of testing is also accelerating. Companies need to adapt their software testing methods to stay ahead of the competition. Many companies are looking to gain speed though Continuous Testing, which can be a foundational element in reducing test and delivery time. This type of testing involves an end-to-end, test automation strategy that enables organizations to test quickly and automate early at every phase of product development. If an organization has adopted Agile and DevOps development practices and is also performing Continuous Testing, it’s possible for the organization to achieve hourly release cycles—or even more frequent iterations.
In addition to Continuous Testing, another widely-discussed trend within the software testing community is ‘Shift Left’ testing. With Shift Left testing, companies look for opportunities to begin testing as early as possible in the development cycle. This can include conducting tests in the requirements gathering phase by creating prototypes to collect user feedback. With Shift Left testing, companies can identify and correct defects as early as possible, thereby reducing the possibility for unpleasant surprises at the end of the development cycle, increasing software quality, and shortening long test cycles.
Organizations are also looking at ways to automate the creation of test scripts themselves, which can be done in various coding languages, such as Java, Python, and more.
Other Notable Advancements in Engineering Automation
In addition to automated testing, businesses are looking at other opportunities for engineering automation. For example:
- Companies want to get better at predicting product defects, so they can prevent more problems before they happen, or companies want to learn more from issues that have already been reported when a product is live. As a result, organizations are evaluating opportunities to use Artificial Intelligence (AI) and Machine Learning (ML). By adopting AI & ML technologies, businesses can create a more continuous, self-learning process to improve products based on historical data and learning-based predictions.
- Robotic Process Automation (RPA) is being used to hasten the testing of repeatable processes, which can help companies get their products to market faster.
- Applications built using advanced technologies around Internet of Things and Big Data mean that testing such applications poses new challenges. For example, each IoT device has its own hardware and relies on software to drive it. Application software will also integrate with IoT devices, issuing commands to the device and analyzing data gathered by the device. Because there are so many variants of software and hardware for devices, as well as different versions of firmware and operating systems, it might not be possible to test all possible combinations of hardware and software. Automation can help increase test coverage.
Organizations that can harness the benefits of these advances in engineering automation will gain valuable speed to market. And, companies should expect their software engineering partner to proactively suggest and implement these automation opportunities.
