Systems | Development | Analytics | API | Testing

Smarter Financial Decision-Making With Enterprise Performance Management Connected Solutions.

AI-powered code editors are speeding up API development by automating repetitive tasks, improving security, and optimizing performance. Developers now spend 55% less time on API creation, focusing more on design and business logic instead of boilerplate code. These tools reduce errors, generate real-time documentation, and enhance scalability, making API development faster and more efficient.

Orbit Codes is solving how blockchain data is indexed and analyzed within the COSMOS ecosystem. It extracts raw blockchain data, transforms it into a structured PostgreSQL database, and provides easy access through a GraphQL interface. For deeper insights, data is replicated to ClickHouse, enabling advanced analytics on transactions, fees, and trends. Designed for blockchains, not just users, Orbit Codes offers white-label solutions and custom branding to integrate seamlessly into existing ecosystems.

The “organic” evolution of a software tester should follow the organic evolution of an organization’s QA maturity. A tester can be conveniently imagined as an organism existing within a larger ecosystem (in our case, the organization). An organism does not exist in isolation. Rather, it responds to, adapts to, and evolves along with the environment in which it finds itself.

Shipping high quality apps requires thorough testing, and testing thoroughly requires teams to automate more of their process. Quality isn’t just about testing more – it’s about testing smarter. By optimizing your workflow, you create space to validate every critical part of your application efficiently and reliably. Full-scale quality comes from full-coverage testing.

Hiring a software testing company can be a good way to get more testing done without recruiting expensive, full-time QA engineers. However, through conversations with engineering leaders and developers, we frequently hear complaints about software testing companies bottlenecking release pipelines, missing apparent visual bugs, and highlighting non-issues as bugs.

Enterprises working in Microsoft Azure need to mask data, and they need to mask it quickly.Yet, it can be difficult to find Azure data masking methods that are both swift and secure. The wrong approach can lead to bottlenecks, compromised analytics quality, and significant regulatory risks.

In the evolving landscape of software testing, Behavior-Driven Development (BDD) has emerged as a powerful methodology for improving collaboration between technical and non-technical team members. However, the implementation of BDD tools like Gherkin and Cucumber often falls short of their intended purpose. Let's explore how to effectively use these tools and avoid common pitfalls.

One method that developers use to submit code modifications for evaluation is known as pull requests (PRs). We discussed the advantages of testing PRs in software development in a previous post but before merging into the main branch, they give team members a chance to talk about the changes, make suggestions, and accept or reject the code. To keep code quality high and make sure that the team reviews all changes, this approach is essential.

When it comes to ensuring software quality, having a well-defined Test Plan and Test Strategy is crucial. As a software developer or QA professional, understanding the differences between these two concepts and how to write a Test Plan or execute a test strategy effectively can significantly improve your testing process.