As the industry of software development in Sri Lanka and beyond (especially those that offer offshoring services) strive to stay at the top of trending technologies, there’s always a process or two that can be improved. Software testing is one such aspect, as internal QA teams toil away to ensure products being rolled out are bug-free and as per customer expectations. Cloud support services have made this process even more streamlined, but more needs to be done in order to determine what and how test processes need to be automated.
Before we get to the nitty-gritty of software testing automation, it’s key to understand a thing or two about today’s digital landscape. People are working remotely more than ever before, and depending on online platforms to satisfy daily needs such as groceries, medicines and even telehealth consultations. As more people flock towards the web to make ends meet, businesses are overwhelmed with competition that’s aggressive as it is overshadowing. While endless consumer options and swift abandonment have been predicaments that businesses have had to deal with for a long time, the stakes are much higher as of current.
As a result, either business objectives have had to be expedited, or overhauled; and both options are such that they require plenty of reinforcement both in the form of overheads, as well as the right tools. With trending technologies such as AI and machine learning, many otherwise monotonous tasks have been replaced by bots that are more efficient and less prone to errors. As such use cases delve into other complex scenarios that require more strategic insight (which a human is better equipped to deliver), more opportunities open up in the arena of automating tasks – and freeing teams to focus on goals that really need most of their time and effort.
Irrespective of the technologies used to build digital products and services, customer experience is an essential ingredient, for it eventually determines whether your brand is successful and well-loved over the web. Data has long since been a requisite for businesses today, in order to help leaders gauge what their customers are thinking, and what their preferences are. Plugging in other powerful aspects such as data science and business intelligence are certainly helpful on both a macro and micro scale, but is there another way to plug in data for better customer insights?
While data has been commonly associated with analytics that happen from a business intelligence standpoint, it has other, more versatile uses. No wonder that data has long since been crowned as the ‘king’ for all things technology, and companies are keen to store, organize and safeguard their precious data more carefully than ever before. The arena of software testing has also seen potential here, as applications go beyond simply automating repetitive testing tasks that may constitute as ‘busy work’ for QA engineers.
Instead, cutting-edge automated testing platforms are going the extra mile by injecting AI and machine learning to first analyse what customers want, and then using that data to determine what needs to be tested. By monitoring how users are interacting with a website or application, such automated testing platforms are able to gauge which interactions are core, edge and even popular among certain segments. These findings are then translated to software testing, where automations are made to test various aspects of the code, with little to no human intervention.
Therefore, automated software testing, in essence, goes beyond simply automating an otherwise mechanical part of the whole testing process. It incorporates active data to ascertain how users are interacting with your digital product, and then test those key areas to ensure everything is functioning smoothly. This is particularly advantageous for regression testing, where continuous iterations to existing code are checked to determine whether other, previous functions are still operating as normal.
Furthermore, such data-driven testing processes will also offer software development teams a bird’s eye perspective of what their customers like and dislike. At-a-glance visualizations can lead the way to deduce where customer requirements are headed over time, so the overall product can be improved to serve users better, and stay in line with bottom-line objectives.
Freeing up teams to focus on tasks of a more strategic or analytical nature has been the premise of automation, all in all. Likewise, developers and QA engineers alike are freed from spending time on repetitive tasks that are required to conduct manual software testing, and instead divert their attention towards better product development strategies. Manual intervention could involve anything from building the code to run software tests, to testing different areas of the program by hand. While manual software testing can be viable for smaller projects of a less complex nature, this is rarely the case for software development these days – even among boutique companies.
With programs closely integrated with others, conducting manual tests across the board isn’t only a massive undertaking, but one that’s highly susceptible to errors. Add to this the fact that software development teams and their codebases are constantly scaling up, and you have a predicament that needs to be solved with an optimal yet cost-effective solution. Hiring more QA engineers isn’t always the most feasible option, especially for corporations that have highly intricate codebases for their proprietary applications.
Does this mean that QA engineers will be rendered obsolete? Not at all! As a matter of fact, your QA team will be better positioned to carry out software testing that’s punctual and free from errors, with reporting happening in an equally timely and organized manner as well. The leverage that automated software testing can provide is of high value, as even the most complex codebases can be tackled by your existing QA team – with tasks that previously took hours would now be solvable in minutes.
Customizing digital applications to suit any device, display or OS has long since been the norm. But the journey to make your application agnostic is easier said than done. Cloud computing has been a wondrous force forward in the aim to develop digital products without heavy infrastructure, so much so that companies are able to form dedicated partnerships with vendors to meet all their cloud needs (such as becoming an AWS partner, for example). However, can the same level of versatility and autonomy be applied to cross-platform software testing as well? Can QA engineers forgo a slew of physical devices by their side in order to ensure the application being tested can perform optimally across any device, display or OS?
Automated software testing becomes a boon in this case, as the same logic can be applied on a cross-platform basis as well. Need to test across multiple devices, displays and operating systems? Use a tool which helps you achieve just that, and mark where the errors are. From elementary unit testing to UI/UX testing, teams can converge to identify what has been flagged by a centralized testing platform, so that fixes can be prioritized with faster turnaround times. There’s no need to keep actual devices handy in order to conduct testing; automate this too, so that your QA and development teams are freed from doing the mundane.
With the web and its digital platforms experiencing an ever-increasing influx of users into the space, the risks associated with high traffic is manifold. Security breaches are a commonality even among the most advanced organizations, thereby giving many smaller businesses enough perspective to prioritize on their own security needs. Testing your software for possible vulnerabilities can be done from the development stage itself, so any loopholes are promptly addressed and resolved. By being security-focused from your software’s infancy, you reduce the likelihood of any breaches – whether it’s with your own company data, or that of your customers’.
Just like any other aspect pertaining to bespoke software, security scans also aren’t a one-time process. They need to be ongoing, just like the iterations that happen to applications in the interest of rolling out an update. Therefore, security infrastructure needs to be laid from the ground-up, depending on variables such as endpoints, networks and data. Stopping possible attacks in their tracks from the get-go, including zero-day attacks is essential; with the alternative option being complete debilitation of your IT systems. Whether it’s a niche security solution or something on a broader scale (such as UTM or SIEM), round-the-clock monitoring is crucial to remediate any possible attacks, or quarantine/disinfect/block potential threats.
Existing and functional software systems that follow an iterative Agile cycle need to be integrated with security components that can constantly be in the works testing for leaks and other loopholes. Penetration testing is a good example, as it scours your entire software to detect any gaps that could be entry points for possible threats. Taking things a step further, ‘red teaming’ orchestrates an attack on the system to observe how staff will react, so that relevant training and remediation procedures can be carried out to further strengthen the security perimeter of your software systems.
On the other hand, does your software have to deal with confidential data such as credit card details and passwords? Many industries such as e-commerce and fintech are common constituents for confidential data, all of which needs to be securely managed with a dedicated identity/access management system. Is your software reacting appropriately to login attempts, especially suspicious ones? This is a key factor to consider when conducting software testing. More so, AI-backed automated testing can further streamline this process to detect and alert on possible errors, so that they can be fixed immediately.
With companies increasingly turning digital thanks to a technologically-oriented modern environment, software development teams have been left juggling with multiple tasks and challenges. Users are highly reliant on online products and services to meet basic needs, while companies have been working remotely more than ever before. The digital landscape is cluttered with limitless options for consumers; it’s no surprise that consumers are seldom loyal to a single brand these days. Add to this the high levels of abandonment experienced by brands. So how is a business supposed to stand out?
Stellar user experiences are essential to not only deliver what customers are looking for – but to keep them coming back for more. While business assessments and advanced data analytics can help organizations achieve this, automated software testing can further add momentum by combining user behavioural data with automated testing sequences. This will ensure that common user journeys are always being tested for smooth functionality, while interfaces are iterated based on user-generated data.
With automation bearing the premise to reduce workloads, automated software testing also achieves just that. Developers and QA engineers alike are freed from repetitive tasks that can otherwise be automated, so that they can focus on overseeing operations within their forte, and also contribute better to challenges of a more strategic or analytical nature. Automation can also help alleviate any of the errors that may be prevalent while conducting testing manually – another key advantage.
Cross-platform testing can also be automated, so that a single, unified console can test applications across multiple devices, displays and operating systems. There’s no need for QA engineers to maintain actual physical devices, and therefore manually check for errors during the testing process. While such automated tools provide leverage to your QA team, they can also be highly useful from a security context. Check for gaps that could be potential entry points for attackers, and integrate the right security components so monitoring can be performed round-the-clock in order to ensure your overarching IT systems are always protected.