Systems | Development | Analytics | API | Testing

Latest News

Interview With Telecoms Software Engineer, Shaman Bhat

In this latest entry of our captivating interview series that focuses on major players in the global tech arena, we welcome Software Engineer Shaman Bhat. We will explore his career development, provide tips for aspiring software engineers, and discuss the key lessons he has learned in his software engineering journey.

Transforming QA Into a Strategic Value Added Initiative

Quality assurance (QA) activities are often seen as a necessary yet time-consuming and expensive process. This outlook can often limit the potential and impact of good QA. In reality, QA is not just about finding and fixing bugs; it’s a strategic value-add that can drive innovation, improve product stickiness, accelerate time-to-market, and enhance overall product quality. Yet, finding the balance between a necessary task and strategic impact can be challenging for many organizations.

Practical Guide to Defect management in Software 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.

Data Fabric: A Complete Guide | Architecture, Benefits & Implementation

Data fabric is an architecture that integrates different data systems and tools. It provides unified access to data stored across various locations to organize, manage, and govern it without moving it to a central database or data warehouse or changing its format. Data fabric relies on metadata to ‘understand’ the data’s structure, lineage, and meaning across various sources. This information enables informed decision-making and optimized data usage.

How to Fix The IllegalStateException in Java

An IllegalStateException is a runtime exception in Java that is thrown to indicate that a method has been invoked at an illegal or inappropriate time. To use an analogy, invoking a method in Java when the system is not in the appropriate state is like trying to start a car while it is in "Drive". Just as the car will not start because it is unsafe, a method call results in an IllegalStateException when the internal conditions necessary for its execution are not met.

Understanding the Differences: Smoke Testing vs Functional Testing

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 Do's and Don'ts of Regression Testing

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.

What is the Future of Apache Spark in Big Data Analytics?

Started in 2009 as a research project at UC Berkeley, Apache Spark transformed how data scientists and engineers work with large data sets, empowering countless organizations to accelerate time-to-value for their analytics activities. Apache Spark is now the most popular engine for distributed data processing at scale, with thousands of companies (including 80% of the Fortune 500) using Spark to support their big data analytics initiatives.

Pioneering the Future: Generative AI's Impact on Medical Devices

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.