Quality and functionality are critical factors in software development. This is where testing methodologies like smoke testing and functional testing come into play. Smoke testing is a high-level, preliminary testing process to ensure that a software program’s most critical functions are working correctly. In contrast, functional testing is a more detailed and thorough testing process.

The modern-day SDLC methodologies such as agile, CI/CD, and DevOps are flexible enough to incorporate change requests in each sprint, which increases the probability of introducing errors in existing functionality. This makes validating existing functionality, detecting newly introduced bugs, and resolving them mandatory in each build release. Whether manual or automated, such software testing is widespread and referred to as regression testing.

Defect management is the systematic process of detecting, documenting, and resolving defects within software applications. A defect refers to any flaw or deviation from the expected behavior, which can arise from coding errors, incorrect logic, incomplete implementations, or unforeseen interactions between software components.

According to the World Health Organization (WHO), Up to 50% of medical errors in primary care stem from administrative issues. There is a projected shortfall of 10 million health workers by 2030. Given the statistics highlighting device errors and a shortage of maintenance professionals exacerbate healthcare challenges, Generative AI in medical devices offers diversified solutions.

A balanced combination of manual and automated testing is the way to go if you want to achieve higher test coverage and efficiency. They cover for each other. Manual testing is easy to learn and do, but it is highly likely to create inconsistent test results, and sometimes it takes a lot of time and effort. On the other hand, automation testing requires a lot of technical expertise to create and maintain scripts, but it checks bugs much faster with higher consistency.

In the world of banking, where customer expectations are continually evolving, and regulatory landscapes are becoming increasingly complex, the integration of intelligent automation stands out as a pivotal solution. Intelligent automation, which combines artificial intelligence (AI) with robotic process automation (RPA), allows banks to streamline operations, enhance customer experiences, and maintain compliance with ever-changing regulations.