If we could live in a perfect world nothing would ever fail, however, the reality is everything is somewhat flawed; errors and mistakes are simply a part of life. Within the software world, this is no different. All software is prone to have bugs and studies have shown 50% of software projects fail. It is impossible to test every aspect of a complex software program manually.
The following factors also affect software projects:
- Infrastructure hosting the software
- Connectivity and offline scenarios
- Compatibility with web browsers
- Integration with other components
- Existing data
- Scalability, security, privacy requirements
- Industry requirements
In addition to this, we as humans cannot fully comprehend our wants or needs until we have a seen it in some form. This is the reason why many users and system owners change their “requirements” after the design is completed. In fact, an average software development project experiences more than 20% change in requirements from the design stage to its first release. These changes are a common problem that impacts nearly all software projects.
This calls in a very important question; how do we combat this? If we cannot eradicate an error we must minimise it. Most software dev teams implement processes and strategies such as coding standards, testing methodologies and investments in tools and talent that identify errors; to increase the quality of software builds and decrease risks.
This is imperative for brands and companies as the usability and quality of their software reflects on their brand image and reputation. You don’t want your company to die from a bug. People have perished in the past due to bugs in control systems software.
Low code business applications platforms and cloud frameworks help pacify this problem to a certain degree, however, every software application requires rigorous quality management. This is where Automated Regression Testing differs; it helps find problems before they affect end users. That’s why we are passionate about test automation.