At System Verification, we are deeply committed to staying at the forefront of technological advancements and delivering the highest quality services to our clients. One of our key contributors to this mission is Dr. Adha Hrusto, an AI Solutions Engineer whose expertise has significantly enhanced our capabilities in quality assurance and software testing.
Development projects often face hidden costs that can derail budgets and timelines, a challenge prevalent not only in the financial services industry but also in sectors such as technology, healthcare, and manufacturing. Identifying and mitigating these inefficiencies is crucial for project success.
Have you ever wondered how a simple blood test can reveal so much about your health?
Healthcare is undergoing a transformative shift, driven by technological innovation. However, challenges persist—healthcare organizations face increasing demands, staff shortages, and mounting administrative workloads for doctors and nurses.
The healthcare industry is on the cusp of a technological revolution, spearheaded by artificial intelligence (AI). These advancements promise groundbreaking developments, including improved healthcare delivery, innovative research, and better health outcomes for all.
We are currently in the age of AI, with its applications becoming integral to daily life and business. AI’s relevance extends beyond engineers, offering advantages across various jobs and activities. Many professions use AI to streamline processes, save time, and utilize existing knowledge. AI is already being used in many areas of everyday life and business through various types of chatbots. We can all agree that this approach is highly beneficial and time-saving. The key skill people need in this area is knowing how to prompt questions and requests to get the most accurate and valuable answers. There are even predictions that new jobs, such as prompting engineers, will soon emerge.
In the software development lifecycle, testing with reliable and secure data is essential for ensuring quality and compliance. While actual production data may seem like the most natural choice, using it directly when testing comes with significant risks. Production data often contains sensitive information—such as customer details or transaction records—which could lead to privacy breaches and regulatory violations if accidentally exposed. There's also always a risk that actual production data can cause inconsistencies or conflicts when applied across different testing scenarios, potentially impacting test results and reducing repeatability.
A few years ago, our System Verification office in Sarajevo launched an internship program that has since brought many valuable and hardworking employees to our company—many of whom are still with us today. We are very proud of this initiative and look forward to continuing it in the years to come. One of our interns from the 2023 generation, Bilal Đedović, began his first work experience with us through this program. Just a year later, he’s already fully integrated into our team, tackling new challenges with dedication. Check out his journey with us.
Automated test generation has become a critical aspect of modern software development. As software systems grow in complexity, writing exhaustive tests manually becomes time-consuming, prone to errors, and can delay release cycles. Automated unit test generation helps developers create reliable, well-tested code efficiency, saving time and improving code quality.
At System Verification, we understand that working in the IT sector, particularly in Software Quality Assurance (SQA), demands a high level of expertise. Our consultants are expected to navigate complex frameworks, programming languages, and emerging technologies. Yet, technical proficiency alone is not enough to thrive in today’s fast-paced consulting environment.
In Part 1, we explored the challenge of unplanned downtime and the solution offered by AI-powered predictive maintenance. Now, let’s look at the concrete benefits for both manufacturing and software quality assurance (QA).
In both manufacturing and software development, unplanned downtime is a critical issue that can disrupt operations, cause significant financial losses, and reduce productivity. While in manufacturing, downtime often results from equipment failures, in the software world, it can be caused by system crashes, defects, or unexpected technical issues that halt production lines or customer-facing applications.
