GenAI is revolutionizing software testing with intelligent automation, self-generating test cases, predictive defect detection, and self-healing scripts. This blog explores key GenAI use cases that enhance speed, accuracy, and efficiency in QA, making testing smarter and more adaptive than ever.

Discover how rigorous SAP testing strategies help manufacturers prevent system failures, ensure process continuity, and achieve zero downtime in production.

Test automation is evolving, and so should your approach. This guide breaks down how enterprise teams can modernize their testing—whether it’s choosing the right tools, integrating AI, or making automation more scalable

Integrate GenAI into your Agile workflow to automate planning, streamline execution, and improve test efficiency. Deliver better software, faster.

Agile teams need speed, and AI-driven testing delivers. It predicts failure points, optimizes test coverage, and adapts to changes—cutting manual effort and accelerating defect detection. The result? Faster releases, fewer bottlenecks, and better software quality.

Migrating to S/4HANA can raise many questions. In this blog, we address the most common ones, offering insights into the benefits, challenges, and best practices for a successful migration. Whether you're just starting or refining your strategy, this guide has you covered.

SAP test automation is all about efficiency and reliability. With the right approach, you can minimize manual effort, detect issues early, and keep everything running smoothly.

AI predictive analytics changes the thought process about the software quality engineering because it makes traditional QA more effective. It detects problems earlier, tests wisely, and keeps track of quality all the time.

In today's rapidly evolving software development landscape, test automation has become an indispensable component of quality assurance strategies.

In the rapidly evolving landscape of software development, testing has transformed from a manual, time-consuming process to a sophisticated, intelligent discipline. As technology continues to push boundaries, artificial intelligence has emerged as a game-changing force in test automation.

In test automation, many teams face a hidden challenge: understanding if their framework is actually meeting their needs. Teams may be operating under different levels of “ignorance”—not realizing their framework’s limitations or recognizing issues but not knowing how to address them.

Zuci has entered into a strategic partnership with Tricentis, a globally recognized innovator in AI-enabled continuous testing and automation solutions for enterprises.

It's a tiresome and exhausting process that limits a tester's ability to focus on other important aspects of their role, such as identifying new gaps in delivery and predicting the unexpected.

Currently we have many test automation frameworks available in our market. But Playwright and Cypress being the modern test automation frameworks in testing web applications, let’s see the battle between these two in terms of unique features, limitations, advantages and much more.

Software complexity is one of the significant factors as they tend to have more intricate code paths, dependencies, and interactions which might need specialized testing techniques such as boundary value analysis, equivalence partitioning and combinatorial testing.

Continuous delivery means the capability to promptly, securely, and consistently deploy various types of changes to software whenever necessary. Teams adept in continuous delivery possess the capacity to introduce software updates.

Test automation framework is the architectural backbone of any automation testing as it structures the entire workflow with a set of guidelines, practices, and tools that streamline and standardize the process of automating tests.

Automation can deliver far more than testing the front end or testing a drop down in a unit test. For years, unit testing and functional testing have dominated the efforts to automate.

Despite being in an Agile-driven SDLC, test automation often remains treated as a distinct process. The seamless integration of the test automation team and developers largely depends on selecting the right test automation partner. This article attempts to give key factors that be considered and taken care of before choosing your test automation vendor.

Flaky tests are a common challenge faced by development teams in their quest to ensure software quality. These intermittent tests produce inconsistent results that may pass or fail unpredictably, even with no changes to the code.

A user's expected behavior when interacting with an application is documented and designed into the application using the agile software development methodology known as Behavior-driven Development (BDD). BDD assists in avoiding bloat, excessive code, unnecessary features, and lack of focus by advising developers to focus solely on the desired behaviors of an app or program.

After all these years, if I were to call one area as the “catch-22” for organizations when it comes to improving their software quality, what do you think would it be?

The important thing to keep in mind is that the approaches for test coverage differ from software to software.

When you see a new tool hitting the market every six months, how do you choose the right one for your business?

The software testing market reached $40 billion in 2021 and is expected to grow at 6% CAGR in 2022-2030

The objective of a QA gap analysis should be to take a deep look at overall engineering processes, not from a QA standpoint alone.

72% of respondents from a Tricentis survey said that regression testing is the most time-consuming aspect of their testing process.

Consulting has always been a hot topic, and whether it's a necessary evil continues to be a topic of debate in boardrooms and among C-suite executives.

Companies are either considering a unique solution to an issue encountered by their esteemed clients or changing their procedures to serve them better.

Despite popular belief, test automation is not a "Silver Bullet"

Suppose you are relatively new to test automation and want to get involved in building a framework.

It's a no-brainer that documenting a neatly articulated test strategy aids in the process of assuring the software quality.

Looking for bugs should be done right from the unit testing phase, with the agile methodology being at the helm of software development.

There are companies with different approaches to software quality, some doing so great, and others have distorted views of quality

Agile does not mention security, and customers have raised concerns about it in the past.

If you're here, chances are you're on the lookout for a Q.A. vendor. When working with an offshore provider, check for these characteristics.

70% of digital (online) businesses fail due to bad usability and poor user experience.

When measuring the effectiveness of Test Automation, there is no one-for-all solution available.

This article will discuss the healthcare trends and focus on implementing them in our system with minimum loss and maximum benefits

A successful release requires coordination between different teams, including design, development, QA, and others.

As the business environment is moving towards more complex models and enterprise transformation, hyper-automation is an answer to their expectations

According to a survey, more than 40% of consumers intend to abandon a website if it takes more than 3 seconds to load.

Are you exploring approaches to take your mobile testing strategy to the subsequent level? There are many techniques for doing this, but you have confined time and resources.By empowering testing and QA teams with mobile app testing tools, you can boost testing pace and reachability.

All mobile app testing projects come with some challenges exclusive to the mobile environment. These comprise complexities of device fragmentation, testing tools, and resources in hand.

AI in Software Testing assists in safeguarding an application against latent application failures, which may be damaging to the app and the involved stakeholders. As Artificial Intelligence becomes a part of our lives, the demand for testing with Artificial Intelligence will increase.

Selecting a programming language for test automation is probably one of the most difficult choices you'll have to make

The first step in creating a successful app is understanding what makes a good one.

Have you wondered how companies like Netflix and Amazon deploy quality products very frequently with minimal to zero production defects?

In the past few years, there's been a lot of buzz about cloud-based services, and rightfully so.

Even though performance is an important aspect of ensuring that the software’s quality is up to the mark, many businesses give it a stepmotherly treatment. Let's look at the performance testing trends for 2023.

The year 2022 will be witness to a lot of changes in technology and digital transformation, and software testing practices will see major overhauls too.

In a post-pandemic world, the quality of healthcare disbursal is something that needs more focus.

Automated testing has completely changed the way businesses operate, especially in terms of delivery and GTM. Let's look at some of the top test automation trends for 2025.

Selenium supports a number of programming languages for performing test automation, but two of the most popular ones are Java and Python.

Ensuring that you test thoroughly is critical to your business product’s success. Without proper testing, your product will be rife with issues that will take a lot of time to solve, and not to mention that there will be a bunch of disgruntled customers.

Shift-left testing is an approach where testing starts earlier in the product development lifecycle. It means “Test early and test often.”

Regression testing is a type of software testing that validates existing parts of the software, could be functional, non-functional, or look and feel

Every QA would have come across Selenium, it is undoubtedly the most popular tool for automation testing today.

If you’re a tester or part of the product quality team, you would have come across this question – “How did QA miss this” at least once during the release.

Whether you employ an in-house engineer or partner with an outside vendor, the success of the test automation exercise will depend on the automated testing tools you choose and skilled personnel to get the best out of it.

From ordering groceries to booking cabs, mobile apps offer us a world of convenience. The world of mobile app testing is fraught with a lot of pressure as everyone expects them to be thorough with what they do, despite the challenges they face.

In this article, we are going to learn about test cases and bug reports and how to write really good ones so that it helps the testers and developers involved in the process.

To build high quality software products, you need to know when and what kind of techniques to use. Functional tests help organizations meet the code requirements of digital products throughout the process.

While you cannot expect test automation to perform all the tasks done by a tester, automated testing is still the best option out there.

Taking into the consideration the needs of the application can help in alleviating the challenges experienced by quality leaders in organizations and Zuci’s CARE(Check, Act, Refine and Evolve) has been carefully built precisely based on problems we repeatedly encountered working with out clients.

The CI/CD tools that are there in the market provide developers the necessary features to deploy the code continuously.

They are also adept at detecting bugs early, and thanks to frequent committing of source code, the CI/CD tools help avoid integration problems too. Let us look at some of the most popular CI/CD tools that are used by programmers in 2021.

Before you release the product, you want most of the major bugs fixed and any errors erased, without testing, it isn’t possible. In this article, we are going to discuss functional testing

Automated testing metrics quantify the performance of the automated test process. You need to have clearly defined goals to measure the progress of your automated testing efforts. When you follow certain KPIs and metrics, you will be able to efficiently evaluate the success rate of the deployment, error rates, etc.

While automated testing saves you a lot of time, there is no underestimating the power of manual testing. In this article, we are going to look at the different types of manual testing and the kind of difference which each of them make when conducted efficiently

The software testing process involves a lot of planning and preparation. This article is a small guide on the essential software product testing checklist that will help with your testing process.

Software testing is a complex process and establishing the right metrics to measure its success is a challenging task in itself. In addition, the sheer number of available software testing metrics can make it hard for testers to select the most suitable ones.

Choosing to outsource your performance testing with the right partner can help organizations avoid spending high efforts, costs and build a robust “continuous performance testing” strategy for the application. However, the question is, when should you consider outsourcing your performance testing efforts?

At this moment, each of the businesses is at a digital war, trying to create the highest degree of software product development much faster than their competitors to reach the market first and grow their business.

Users' chance of abandoning a mobile app is as quick as the app is being developed—the foremost reason being issues in the "quality" of the application.

Fundamentally, testing in DevOps aims to strike the right balance within the overlap of goals, feedback cycles, skills among the development, QA and the operations team.

If API's working is at fault and error isn't detected, it is highly probable to break an entire application and network of business processes anchored on it.

As you can see, testers do not get involved in the early stages of software development such as requirement gathering or the design or the development.

As more and more companies across industries begin to realize the importance of the need for software to keep their businesses going, it goes without saying the need to test such software that is being created.

Software testing can prevent errors that can prove costly to fix, resulting in avoidable and exorbitant expenses later

Functional Testing looks at the behaviour of an application, whereas non functional Testing looks at its performance. To make an analogy, if you think of an application as a child, then Functional Testing evaluates its manners whereas non functional Testing evaluates its grades in exams.

There are separate software testing tools for every requirement and purpose. Lets examine each in this blog

Software testing is the investigation of the properties of a software system to determine its feasibility for a given task or purpose

Software testing is one of the most critical components of the Software Development Life Cycle (SDLC) and yet so little is known about it.

It is a shared secret that usability testing of your product is a crucial step to delivering flawless user experiences - that convert visitors to buyers.  

With new code deployment happening and high loads in user access, it is difficult to do thorough testing, especially with reduced staff and limited time.

Much of the migration to the world of microservices is taking place because, microservices, unlike a monolithic application, enable you to build services using diverse technologies..

Many software companies today have embarked on DevOps journey for continuous delivery of their products only to realize that automated testing is indispensable to achieve full agility.   

Customers today have multiple touchpoints to access like a website, mobile app, tablet, etc. and each of these touchpoints is expected to deliver truly great user experience, in order to convince your customer to make that final commitment and buy.

The manufacturing industry has been a forerunner in setting quality examples for others ever since the introduction of Lean, Kanban, Kaizen, Just-in-time manufacturing practices

The big challenge to performing the test is the test environment. QAs should carry the test on real or production-like environments

The most common and often repeated word of recent times is “Digital Transformation”. Companies that want to deliver software faster and better to customers take this route to stay ahead of the competition.

Applications are your Business; Secure your Business.

Production issues are a black swan. We classify them as unknown unknowns because we can’t guess what had gone wrong until it has happened, and they usually carry an extreme impact.

The 1-hour live session had 90+ attendees registered, and 25% of them watching it live.

According to Gartner, 95 percent of applications running in production today are not instrumented.

Effective testing helps in improving quality by identifying and removing defects early in the cycle and emerging tech like AI is expected to make a significant impact in performing better testing in the years to come.

At Zuci Systems, we apply Agile methodologies, cognitive quality automation and AI to offer comprehensive Quality Engineering without increasing costs or software release cycles.

Are you looking to explore BDD with Testcomplete in windows 10 using IntelliJ? Then, here is all that you need to know. We scrounged through the internet to find information on end-to-end implementation setup but barely found any. Hence, the inspiration comes from the lack of reliable and comprehensive documents or videos for reference.

Hurray! Jenkins shows code green. But is that enough to ensure software quality?

Exploratory testing is more of a skill-based testing than a role-based testing as people assume.

Testing everything through UI is complex, costly and time-consuming. With ever-growing need to support application on different devices and interconnected systems; a bare minimal three-tier architecture has become the de facto for application development in which the core business logic lies in the ‘Service Layer’.

In today’s technology trend, every software application we use is made available either as a web application or mobile app. But there are lots of desktop applications still in use in large enterprises. To test these windows based applications we still largely rely on commercial tools like TestComplete, HP Unified Functional Tester, Coded UI, etc.

In the previous post, we gave an overview of how ZUJYA helps in validating predictive models. While ZUJYA is built to validate machine learning based predictive models, it can also be used along with standard automation frameworks that are used for Functional/Non-Functional Testing.

Machine Learning is used applied when the scale of data is too large for rule-based systems to handle. For example, you might be able to manually predict purchasing pattern at a small roadside shop by going through the sales entries but it would be difficult to do the same for a large departmental store simply because the number of factors involved are very high.

Before we understand the approach to testing Machine Learning applications, let’s look at the steps involved in building them.

In the previous post, we gave an overview of how ZUJYA helps in validating predictive models. While ZUJYA is built to validate machine learning based predictive models, it can also be used along with standard automation frameworks that are used for Functional/Non-Functional Testing.

The often stated challenges in considering non-functional tests in any model (let alone continuous testing) are: Non-functional tests are inconsistently defined and poorly planned Non-functional tests are often treated as lower priority Lack of suitable skillset

During the past few years majority of the software projects use Continuous Delivery, a software engineering approach in which teams produce software in short cycles, ensuring that software can be reliably released at any time.

Non-functional testing is critical to ensuring any software's full functionality & to ensuring seamless business operations. Here's why...

It was 8 AM during one of the critical release regression times, our SDET came to office and found that 60% of his tests failed due to changes in UI (element IDs changed, new elements introduced, elements removed etc). It is a suite of about 2000 Tests, can we analyse all of these 1200 failed tests in the next few hours and find the reasons?

Those of you who happened to be at the Moscone center in San Francisco this year for the Google I/O conference know would have stood witness to Google CEO Sundar Pichai’s talk about Machine Learning, Artificial Intelligence,