EuroSTAR Conference

The Power of Live Demos: Why 6 Minutes Can Make a Difference

January 30, 2025 by Lauren Payne

At EuroSTAR, we know that engagement is everything. The EuroSTAR Conferences EXPO Hall is a hive of energy, networking, and innovation, making it the perfect place to connect exhibitors and sponsors with software testing and quality engineering professionals. But in a bustling conference environment, how do you ensure your brand stands out? The answer: A Live Demo.

The Impact of a 6-Minute Live Demo

Six minutes may not seem like a lot of time, but in the right hands, it can be a game-changer. A well-executed live demo captivates an audience, sparks meaningful discussions, and showcases your solution’s real-world impact. It’s not just about explaining your product—it’s about demonstrating its value in action.

Here’s why these six minutes can make a difference:

Instant Engagement: Live demos create an interactive experience that draws attendees in and keeps them invested in your product or service.
Showcase Thought Leadership: Demonstrating your expertise and innovation positions your brand as a leader in software testing and quality engineering.
Drive Booth Traffic: A compelling demo generates interest and directs attendees straight to your booth for deeper conversations.
Boost Brand Awareness: Stand out from the crowd with a dynamic, hands-on presentation that leaves a lasting impression.

Huge Interest from Attendees

We’ve seen an incredible response from attendees to these Live Demos, with over 150+ participants attending these sessions during the Lunchtime break of the conference. It’s a fantastic opportunity to engage with a highly interested audience in a relaxed, interactive setting.

To add even more excitement, at the end of each demo, we run an attendee prize giveaway organised by the EuroSTAR EXPO team. All you need to focus on is what you wish to present—leave the logistics and incentives to us!

Expanded Access in 2025

Last year, Live Demos were exclusively available with the Platinum packages. This year, we’ve expanded access, allowing all Gold Sponsors to purchase a Live Demo as an exclusive package add-on. This gives more brands the opportunity to leverage this impactful tool and enhance their presence at EuroSTAR.

Whether you’re launching a new product, demonstrating a cutting-edge feature, or showcasing an innovative testing solution, a Live Demo is your opportunity to make an impact. Don’t just tell your audience about your solution—show them why it matters.

Secure Your Slot

According to the Freeman Trends Report 75% of attendees want to make the most of in-person learning with hands-on demos and activities. Incorporating live demos into your event strategy can offer dynamic, interactive experiences that resonate with the EuroSTAR Conference attendees. By showcasing your solutions in action, you not only demonstrate value but also position your brand as a thought leader in the industry.

Live Demo slots are limited, and demand is high. If you’re looking to maximize your exposure at EuroSTAR, this is your chance to shine. Book your Live Demo today and make your six minutes count!

For more details on how to secure your slot, reach out to our team or visit the EuroSTAR Conferences EXPO website.

Let’s make innovation visible—one Live Demo at a time! To find out how you can achieve your marketing goals and more at a EuroSTAR Conferences EXPO, speak with Clare Burke.

Clare Burke

EXPO Team, EuroSTAR Conferences

With years of experience and a passion for all things EuroSTAR, Clare has been a driving force behind the success of our EXPO. She’s the wizard behind the EXPO scenes, connecting with exhibitors, soaking up the latest trends, and forging relationships that make the EuroSTAR EXPO a vibrant hub of knowledge and innovation.

t: +353 91 416 001
e: clare@eurostarconferences.com

How to Measure the Value of Software Testing EXPO Trade Show Participation

September 11, 2024 by Lauren Payne

Participating in trade shows like the EuroSTAR Software Testing EXPO can be a significant investment of time, money, and resources. However, the potential benefits, including increased brand visibility, lead generation, and networking opportunities, can be substantial. To ensure that your participation is worthwhile, it is crucial to measure the value derived from the event. This blog post outlines Clare’s recommended key metrics and strategies to help you evaluate the return on investment (ROI) from participating in the EuroSTAR Software Testing EXPO.

Set Clear Objectives

Before delving into metrics, it’s essential to define your goals for participating in the trade show. These goals should align with your overall marketing strategy. Common objectives include:

Lead Generation: Capturing contact information of potential clients.
Brand Awareness: Increasing visibility and recognition of your brand.
Networking: Building relationships with industry peers and potential partners.

Setting clear objectives when participating in an EXPO helps us ensure we are enabling you to focus efforts, measure success, allocate resources effectively, and enhance overall strategic alignment with business goals. Clear objectives are helpful when we are helping you pick an EXPO package that best suits your business goals.

Pre-Event Preparations

To measure the value effectively, start tracking metrics before the event:

Budget Allocation: Document all expenses related to the event, including booth costs, travel, accommodation, marketing materials, and promotional items.
Marketing Reach: Assess your pre-event marketing efforts, such as email campaigns, social media promotions, and blog posts. Depending on which EXPO package you have opted for there may be pre-conference marketing activations that will also help boost your brands attendance and visibility.

Lead Generation

One of the primary reasons for attending the EXPO is to generate leads. Collecting leads is a very important part of exhibiting as well ad forging connections and networking. Key metrics to track include:

Number of Leads Collected: Count the total number of leads gathered during the event.
Lead Quality: Evaluate the quality of leads based on criteria such as job titles, company size, and level of interest.
Lead Conversion Rate: Track how many leads convert into actual sales or follow-up meetings, this is dependant on the actions taken post event.

Brand Awareness & Engagement

Increasing brand awareness and engagement is another crucial objective. Things to consider:

Booth Traffic: Monitor the volume of visitors to your booth each day, try different initiatives to encourage footfall and get involved in the EuroSTAR EXPO Passport around the EXPO. Some other ideas include running a competition or have a testing challenge.
Social Media Engagement: Track mentions, shares, likes, and comments on your social media posts related to the event. Always be sure to share your participation in the event. This helps build awareness and visibility for your brand
Media Coverage: Monitor any press coverage or mentions in industry publications resulting from your participation.
Swag: Keep your brand at the forefront of attendee’s minds with a cool piece of conferences swag for them to take home. Our attendees love conference swag.

Market Research & Networking

Understanding the software testing industry trends and building relationships can be invaluable. Things to be conscious of:

Competitive Analysis: Mingle with other exhibitors in the EXPO. Having conversations helps gain insights about other companies products and services, challenges, successes, pricing, and strategies.
Partnership Opportunities: Count the number of potential partnership discussions initiated.
Feedback and Insights: Collect feedback from conversations with attendees and industry experts to identify trends and areas for improvement.

Post-Event Follow-Up

Effective follow-up is critical to maximising the value of EXPO participation:

Timely Follow-Up: Ensure that leads are contacted promptly after the event.
Nurturing Campaigns: Implement nurturing campaigns to keep leads engaged and move them through the sales funnel.
Feedback Surveys: Conduct surveys to gather feedback from attendees and improve future participation.

Conclusion

Measuring the value of your participation in the EuroSTAR Software Testing EXPO requires a systematic approach and a focus on relevant metrics. By setting clear objectives from the beginning, tracking key metrics, and continuously improving your strategy, you can ensure that your investment in the EuroSTAR Software Testing EXPO will deliver substantial returns. With diligent measurement and follow-up, you can leverage EXPO participation to boost your brand, generate quality leads, and drive business growth.

To find out how you can achieve your marketing goals and more at a EuroSTAR Conferences EXPO, speak with Clare.

Clare Burke

EXPO Team, EuroSTAR Conferences

t: +353 91 416 001
e: clare@eurostarconferences.com

7 Common Test Management Challenges AI Can Solve

June 5, 2024 by Lauren Payne

Test management is an integral part of software development that ensures that your software meets quality standards, is bug-free, and performs as expected. Unfortunately, there are some challenges in test management systems, causing significant issues while impacting application speed and quality. As software complexity grows, so do the difficulties in managing testing processes efficiently. To deal with the evolving challenges related to test management and software complexity, artificial intelligence (AI) plays a vital role. AI offers innovative solutions to many of these challenges. In this blog post, we’ll explore seven common test management challenges and how AI can solve them.

Navigating Key Challenges in Test Management

Efficient test management, improved productivity, increased ROI, and faster time to market are the things that every organization expects from its test management solutions. There are many aspects that stop companies from achieving the best results from their test management processes. They may experience inadequate test coverage, resulting from a lack of thorough testing across all possible scenarios, compromising the product’s quality and introducing the risk of undetected defects.

Similarly, inefficient test case prioritization leads to a misallocation of resources, with critical areas receiving insufficient attention. Thereby prolonging testing cycles and delaying time for the market. Moreover, insufficiently realistic test data fails to accurately simulate real-world scenarios, hindering the effectiveness of testing efforts and resulting in potential oversights. In case of having flaky test cases in test cycles, testers may experience inconsistency and uncertainty in the testing process. It can delay product release and affect ROI. These challenges collectively contribute to inefficient productivity, as valuable time and resources are wasted on ineffective testing methods. Efficiency suffers as testing cycles become prolonged and repetitive due to the need for rework and debugging. Consequently, ROI is impacted negatively as the cost of rectifying defects increases. Plus, the time to market is delayed, leading to missed opportunities and potential revenue loss. It is crucial to address these challenges effectively to optimize productivity, efficiency, ROI, and time to market in the software development lifecycle. Let’s learn how AI-powered solutions can address test management challenges.

1. Difficulty in Test Case Prioritization

In simple words, test case prioritization (TCP) refers to arranging test cases based on their significance, functionality, and potential impacts on the software and running them in the correct order. However, prioritizing test cases effectively is a challenging task in test management. With limited time and resources, it’s essential to focus your testing efforts on the most critical areas of an application.

Test Case Prioritization can help in efficient test management

Integration of AI in your test management solutions can help you with efficient test case prioritization. It analyzes factors like code changes, historical defect data, and business impact to automatically prioritize test cases. Machine learning algorithms can adapt over time, continuously improving prioritization based on past results and changing project requirements. By leveraging AI for test case prioritization, teams can optimize testing efforts and identify high-risk areas early in the development cycle.

It helps to Improve efficiency and reduce time to market as resources are allocated more effectively, ensuring that high-risk areas are thoroughly tested early in the development cycle.

2. Incomplete Test Coverage

Achieving comprehensive test coverage is essential for identifying potential defects and ensuring the overall quality of the software. In a traditional test management system, when test creation is a manual aspect, you may not have complete test coverage, leaving critical areas untested. This incomplete test coverage is a common challenge in software testing, leaving potential defects undetected. Besides manual issues, many other factors can lead to incomplete test coverage, such as time constraints, resource limitations, or oversight in test case creation. Incomplete test coverage increases the risk of releasing software with undiscovered bugs, which can lead to customer dissatisfaction, costly rework, and damage to the organization’s reputation.

Comprehensive test coverage can make test management better and improve productivity

To address the issue of incomplete test coverage, organizations can leverage artificial intelligence (AI) solutions that offer innovative approaches to test case generation, prioritization, and optimization. AI-powered test management tools can analyze application requirements and usage patterns to generate test cases automatically, ensuring comprehensive coverage across various scenarios and edge cases. By using AI for test case generation, teams can enhance the effectiveness of their testing efforts and minimize the risk of overlooking critical functionalities.

3. Availability of effective Test Data

Realistic and diverse test data plays a crucial role in effective software testing. It allows testers to simulate real-world scenarios and ensure comprehensive coverage of the application under test. However, generating and managing test data manually can be time-consuming and error prone. Plus, manually generated data may not always represent the diversity of data encountered in production environments. This can lead to insufficient test coverage and potentially overlook critical edge cases and scenarios.

Availability of effective Test Data improves productivity and reduces time to market

AI offers innovative solutions to address the challenge of test data availability by automating test data generation, management, and optimization. AI-driven test data generation tools can analyze application requirements and usage patterns to generate synthetic test data automatically. These tools use machine learning algorithms to simulate real-world scenarios, enabling thorough testing without compromising data privacy or security. Apart from synthetic test data generation, AI- AI tools can analyze existing data sources to profile and identify patterns, correlations, and anomalies within the data. Plus, AI-driven test data solutions can easily be integrated with existing testing workflows and tools, allowing testers to easily access and utilize generated test data within their testing environments. As a result, testers can conduct thorough testing without delays caused by manual data generation, improving productivity and time to market.

4. Bottlenecks Caused by Flaky Test Cases

A flaky test case is one that exhibits non-deterministic behavior when executed repeatedly within the same environment, resulting in intermittent results. Flaky test cases can cause delays and inconsistencies in test results and reduce the testing process’s reliability.

Flaky test case detection can help with efficiency and reduced time to market

AI-powered tools can analyze test scripts and execution logs to identify and address flakiness automatically. With machine learning algorithms, these testing tools can identify patterns indicative of flaky behavior and suggest corrective actions to ensure consistent and reliable test results. For instance, QMetry’s test management platform allows testers to gain control over flaky tests is identifying them using a “Flaky Score” derived from its execution history. With AI-powered flaky test detection and mitigation processes, testers can minimize disruptions in the testing process and improve the overall reliability of their testing efforts.

Flaky test detection not only increases efficiency and reduces time to market but also allows testers to focus on productive tasks without being hindered by inconsistent test results.

5. Unidentified Defects passing on final product

Detecting and resolving defects early in the development process is critical for delivering high-quality software. However, identifying potential defects among thousands of lines of code can be challenging, even for experienced testers.

Efficient defect detection helps with better test management, faster time to market, and improves ROI

AI-driven defect detection models can analyze code changes and historical defect data to identify patterns indicative of potential defects. Machine learning algorithms can predict which code changes are most likely to introduce defects, allowing developers and testers to focus their efforts on high-risk areas. By incorporating an AI-powered defect prediction system into their test management processes, testers can proactively address quality issues and minimize the impact of defects on the final product.

Therefore, AI-powered defect detection can help with better test management, faster time to market, and improved ROI as defects are detected and resolved before they impact the final product.

6. Managing Test Environment

Managing test environments with diverse configurations, dependencies, and constraints is a huge challenge for many development testing teams. When testers try to deploy and configure test environments manually, it can lead to inconsistencies, delays, and resource contention.

Better test environment management can Increase productivity and reduce time to market

AI-driven test environment management solutions can help testers to manage test environments in a better way. Using infrastructure as code (IaC) and configuration management tools, AI-powered solutions can automate test environment provisioning, configuration, and maintenance. Using machine learning algorithms, AI-driven solutions can optimize resource utilization, predict capacity requirements, and proactively identify potential bottlenecks or failures. By incorporating AI-driven test environment management into workflows, testers can ensure reliable and consistent test environments throughout the software development lifecycle. It influences increased productivity and reduced time to market as testers can focus on testing activities rather than dealing with manual deployment and configuration of test environments.

7. Test Result Analysis:

Test results analysis to identify trends or patterns plays a significant role in improving test coverage and reliability. In case of traditional test management systems, manually reviewing test results and logs is time-consuming and error-prone, especially in large-scale testing environments.

Efficient test result analysis can improve the efficiency and reliability of testing efforts

With AI integration, test result analysis becomes easy and more efficient. AI-powered test result analysis tools can aggregate and analyze test results from multiple sources, such as automated tests, manual tests, and performance tests. The application of machine learning algorithms enables these tools to identify correlations between test outcomes, code changes, and environmental factors. These tools can also perform root cause analysis and trend prediction. AI-driven test management tools allow testers to gain valuable insights into their testing processes and make data-driven decisions to improve quality and efficiency.

Key Takeaway

Test management can be complex and challenging with traditional methods and tools. However, AI offers innovative solutions to many of its inherent difficulties. AI-powered test management solutions offer technologies like machine learning, predictive analytics, and natural language processing to overcome common test management challenges and improve the efficiency, effectiveness, and reliability of their testing processes.

From test case prioritization to test environment management, AI-driven solutions have the potential to revolutionize the way software is tested and validated. AI can lead to faster release cycles, higher-quality products, and improved customer satisfaction. As AI continues to advance, its role in test management will only become more significant, empowering organizations to meet the demands of their users and sustain in a competitive software landscape.

Modern AI-powered tools like QMetry Test Management for Jira by QMetry can help you to manage all your testing activities through integrated tracking tools (e.g. Jira) and automation frameworks.

QMetry’s second-offering QMetry Test Management is designed for Agile and DevOps teams. These products are fully integrated into CI/CD pipelines giving testing teams and leaders full control over testing projects. These tools also manage manual testing seamlessly.

Both QMetry Test Management and QMetry Test Management for Jira offer scalable, compliant, and secured test management that allows you to deal with different testing challenges. Gen AI offerings of these tools have features like smart search, auto test case generation, and flaky test case detection making your testing super-efficient. These tools have potential of reducing time to market, improving ROI, and increasing efficiency.

Want to learn more about these test management products and how they can improve your test management experience? Schedule a call now!

Author

Deepak Parmar, Global Product Marketing Leader at Qmetry

QMetry is an innovative leader in AI enabled test management and automation products for Agile and DevOps teams that empower enterprises to build, manage, and deploy quality software at speed with confidence. QMetry is revolutionizing testing through AI-driven test authoring, test execution, and quality analytics for agile teams globally. Experience QMetry’s AI – enabled Test Management powered by QMetry Intelligence (Gen AI) delivering quality at speed and scale. It is a powerful, scalable, compliance driven quality orchestration platform that enables quality at speed with improved ROI.”

QMetry is an exhibitor at EuroSTAR 2024, join us in Stockholm.

Improving Test Planning by leveraging Quality Intelligence

June 3, 2024 by Lauren Payne

Test planning suffers due to poor requirements

Test planning is a critical part of an in-depth test strategy and includes the definition of the test objectives, scope, and the means and the schedule for achieving them, among other things.

Determining the extent of test coverage and prioritizing test cases are essential elements of a robust testing strategy, serving a crucial role in assuring the comprehensive validation of the software under test.

Unfortunately, testing teams face challenges due to ambiguous, changing, or incomplete requirements, making it difficult to establish a robust foundation for the test planning process.

This creates a cascading impact on the prioritization of testing efforts, resulting in resources being allocated to less critical test scenarios, potentially overlooking important issues, and ultimately leading to inadequate test coverage.

Approaches to address gaps in test coverage

As we discussed before, coverage gaps commonly occur when requirements are misunderstood, specifications are poorly defined or ambiguous and changes in the software are not appropriately incorporated into the test planning.

To tackle these challenges, test teams should embrace formal test design methods to guarantee comprehensive coverage of all aspects outlined in the requirements. Implementing a traceability matrix, linking requirements to test cases, further ensures comprehensive coverage.

Additionally, encouraging collaboration among development, testing, and business teams early in the process to clarify requirements helps mitigate the risks associated with poor requirements.

Yet, coverage gaps can arise when the requirements fail to adequately capture real-world user behaviors and preferences. Anticipating and comprehensively accounting for all user interactions and behaviors in written requirements proves to be a challenging task for product owners and business analysts.

Finding the needle in multiple disconnected tools

To boost test coverage and align the test prioritization with real-world usage, testing teams can analyze logs from both production and test environments, uncovering valuable insights and quality analytics.

Testing teams need to implement tools and processes to actively monitor, measure, and analyze user behavior when interacting with the live application. Additionally, it’s essential to observe how tests interact with the application during test runs to reveal disparities between how the application is used by real-world users and how it is tested.

In the market, tools like Google Analytics, Amplitude, SmartLook, Datadog, and others assist in collecting and analyzing telemetry from any environment. Designed with different purposes in mind, these tools serve various teams, such as Product and Marketing Analytics, Observability, and Application Performance Management. Despite their versatility, they may not be the optimal fit for testing purposes.

Considering this, a major challenge is that these tools aren’t designed to meet the specific needs of testing teams. This limits their ability to get the most out of the tools and stops them from seeing both how the software is used in the real world and during test runs and extract meaning from it.

Enhancing Test Planning with Quality Intelligence

Gravity is a unified platform designed to help testing teams monitor and leverage insights from both production and testing environments, enhancing the efficiency of the test strategy. It consolidates key data and insights into a single solution for easy access and analysis.

Its primary function is to produce “Quality Intelligence” by processing the ingested data through machine learning algorithms. This involves translating raw data into meaningful insights using techniques such as pattern recognition, trend and correlation analysis, anomaly and outlier detection, and more.

Gravity’s ability to monitor production and testing environments allows it to conduct a comprehensive test gap analysis. By comparing the paths taken by real user interactions in live production with the tests executed in testing environments, Gravity generates insights to enable testing teams to spot gaps in coverage, identify features that are either over-tested or under-tested, and recognize redundant testing efforts in less critical areas.

Gravity utilizes pattern recognition and AI (Artificial Intelligence) to automatically generate test cases for areas lacking test coverage, whether they are manual tests or automated scripts for test automation tools like Cypress, Playwright, and others. This feature not only reduces the burden of test case creation but also leads to a decrease in maintenance overhead.

Since it relies on real usage data collected from production environments, this enables data-driven test case prioritization, focusing test coverage on high-impact areas that directly affect the end user experience. By bridging assumptions from requirements with real-world usage insights, Gravity helps in optimizing test planning for improved efficiency and agility.

Conclusion

Understanding user behaviors in production not only elevates test coverage and prioritization by focusing on genuine user experiences but also acts as a powerful antidote to the limitations of the traditional requirement-based testing approaches.

It ensures that testing efforts are not confined to the rigid boundaries of documented requirements but rather extend to the dynamic and evolving landscape of user interactions, contributing to a more comprehensive and user-centric testing paradigm.

Gravity represents a remarkable advancement in the field of Quality Engineering, empowered by cutting-edge AI (Artificial Intelligence), with the aim of enabling testing teams to deliver higher-quality software products.

Author

Cristiano Caetano, Head Of Growth at Smartesting

Software testing authority with two decades of expertise in the field. Brazilian native who has called London home for the past six years. I am the proud founder of Zephyr Scale, the leading Test Management application in the Atlassian ecosystem. Over the last ten years, my role has been pivotal in guiding testing companies to build and launch innovative testing tools into the market. Currently, I hold the position of Head of Growth at Smartesting, a testing company committed to the development of AI-Powered testing tools.

Smartesting is an exhibitor at EuroSTAR 2024, join us in Stockholm.

Innovating quality: strategic approaches to complex software testing

May 31, 2024 by Lauren Payne

As the complexity of modern solutions increases, not only does the challenge for software developers grow, but so do the expectations for software testers. Although values such as ‘lines of code’ are not universally meaningful metrics, the following graph shows well where the journey is heading.

In the early days of computer technology, programs were relatively simple and straightforward. However, as technology advanced and software applications became more powerful, the size of code bases increased significantly. This is nothing wrong, of course, but it does provide new challenges.

Increased complexity – more bugs

As software has evolved, so has its complexity. Software systems now encompass complex architectures, sophisticated algorithms, and diverse integrations with various platforms and technologies. The demand for advanced functionalities, seamless user experiences, and robust security measures has led to the development of complex software applications. Managing this complexity requires careful design, modularization, and the adoption of architectural patterns to ensure maintainability and scalability.

While software has become more sophisticated and powerful, the presence of bugs remains a challenge. As software grows in size and complexity, the potential for defects and errors also increases. The sheer volume of code, coupled with interdependencies between modules and integration with external components, introduces a higher likelihood of bugs.

The need for faster product delivery can impact product quality

Companies are increasingly under fire to deliver software with new functionalities and improvements to stay ahead of the competition. This puts pressure on all involved roles to deploy new code rapidly, which often results in reduced testing efforts and even more bugs in production.

In today’s competitive business environment, a company’s reputation is also closely tied to the perceived and experienced reliability of its services. Even the smallest of bugs can have a significant negative impact on a company. In conclusion, testing is a crucial discipline to identify bugs before they are discovered by the end-users to secure the company’s reputation.

The crucial role of testers in product quality assurance

In this game, testers play a crucial role in safeguarding product quality by ensuring that the product meets the required standards in terms of functionality, reliability, usability, and more. This can’t be achieved just by clicking around in an application and reporting some “strange behaviors”. Testing should be a comprehensible activity based on specification, proven methods, and an overall understanding of the business context.

To ensure product functionality and quality, you need skilled people with a quality-focused mindset, who understand business processes as well as the implemented technologies and solutions. This work cannot be a “last minute” task that can be skipped in case of tight deadlines or done by any person “just available”.

Shift testing to the left and involve testers from the beginning

So, how is it possible to implement quality assurance in such a way that it does not delay the delivery date and still has an actual effect?

This requires involving experienced testers who have the capability to analyze the use cases and IT solution design. Even more crucially, they should be involved from the very beginning of the process. By challenging business ideas and identifying missed elements or flows early on and even without code, testers can help avoid wasting unnecessary resources on functionalities that may need to be changed later. This calls for close collaboration between business, testers, and developers as one team.

Starting testing early in the software development life cycle (SDLC) is known as the “Shift left” approach, and it comes from the idea of shifting test activities to the “left” in the development process timeline to ensure problems are detected as early as possible. Involving testers right away, starting with the requirements gathering stage, brings numerous benefits, such as early defect detection, faster feedback to developers, better collaboration between teams, and reduced business risk.

Efficient testing without excessive costs

In the realm of rapid code deployment, financial investments alone won’t solve quality issues. In addition to “Shift left” there are different methods that can ensure successful testing efforts without increasing the testing budget.

Testing isn’t just about speed; it’s a strategic blend of prioritization and disciplined collaboration. At Sixsentix, we advocate a disciplined testing approach centered on business-facing testing and business risk coverage.

With our risk-based methodology, we can clearly identify the processes and features with the greatest business impact, based on the frequency of use and potential damage that can occur as a result of failure. We perform a thorough analysis of the business, accurately determine specific business risks thanks to the combination of expertise and domain knowledge, and then prioritize testing of sensitive components.

This way, we make sure that key functionalities are swiftly checked and validated, and that the most pressing business risks are ruled out. Sixsentix combines this approach with the “Shift left”, which allows continuous testing and deployment after every change. This means that the latest updates are always released as soon as possible, without critical failures that could damage your reputation and business long-term.

Enhancing software quality through team dynamics

It’s also crucial to have a cohesive team composition, backed by a time-tested method. Our testing teams have been using our well-refined SWAT methodology, which enables them to use a systemic approach to testing.

Simultaneously, we abide by the “Tres Amigos” principle. It highlights the participation of three key roles: the product owner, the developer, and the tester, and emphasizes that these three roles are, in fact, one team, pursuing the same goals and priorities, which significantly boost the delivery of high-quality software.

Finally, in order to orchestrate and automate testing activities efficiently, we also designate a test architect for each project to define the overall testing strategy and framework and ensure they resonate with business objectives. This orchestrated effort significantly enhances the testing process, elevating software quality and ensuring a successful, reliable product.

Moving forward

Transforming quality assurance involves continuous improvement, robust collaboration, and the embrace of automation, propelling organizations towards a mature QA level where testing adapts to evolving requirements and aligns with changing organizational needs.

Let’s embrace efficient testing strategies and disciplined collaboration, striving for a future where software isn’t just fast and functional but also robust, reliable, and aligned with both user needs and business goals.

Author

Sixsentix

Sixsentix is a leading provider of Software Testing Services, QA Visual Analytics and Reporting, helping enterprises to accelerate their Software Delivery. Our unique risk-based Testing and QACube ALM Reporting and Dashboards, provide business with unprecedented quality and transparency across Software Delivery projects for faster time-to-market. Sixsentix customers include the largest banks, financial services, insurance, telecom providers and others. Sixsentix Onsite, and Nearshore (SWAT) services deliver optimized testing outcomes at significantly lower costs and help customers with scalability to keep pace with digitalization.

Sixsentix is an EXPO Exhibitor at EuroSTAR 2024, join us in Stockholm.

Business Process Automation for Software Customers – Needs and Challenges

May 29, 2024 by Lauren Payne

Often automated testing is seen as an act by the team that is creating the software. It is a task to ensure quality of the software before it is shipped. However there is an important usage of test automation that can take place AFTER the software is shipped. And it is done BY the CUSTOMER!

The Need:

Customer organizations which buy software don’t just use one particular software. For different aspects of their business, they use different software applications. These applications are integrated together in various workflows, so that they work in tandem to improve employee productivity. Teams in such organizations use these applications on a daily basis and their productivity would falter if any of the software applications fail to function as expected. It is a reality of the current times that each of these applications may be updated 2 to 3 times if not more times a year. And each software application may have its own release cycle/cadence. Any software update may disrupt the employee workflow and cause significant damage in terms of time and money for the company. Hence, organizations need to ensure that their workflows continue to work after any update to these software applications. Such task may be carried out by a business team or a QA team at the customer org.

Can this verification be automated? What are the challenges?

We regularly work with customers in the Automotive industry. These are the challenges faced by them.

Challenges Faced:

1) Software applications in business workflows may be built on different technology stacks. A desktop application may be used for designing automotive parts while a web based PLM application may be used for managing those designs. The interplay between these two applications would be important for the customer teams. Most automation tools do not support automation of multiple technologies.

2) Applications once shipped behave mostly as a black box. They need to be exercised mostly via the Graphical User Interface (GUI). Importantly, we need to mimic the end user’s usage pattern, so GUI becomes significant.

3) Teams that verify such functional continuity will be small and more focused on the business aspects than the automation aspects. They may not have technical know-how (or time) to automate such third party applications using traditional programmatic tools.

So teams look for an automation tool that:

1) Can work across technologies like desktop, web, java, SAP etc.

2) Is easy to use – preferably low or no code

3) Has good support. Since the team may not be very technical, a good support team ensures any edge cases can be handled correctly and quickly

Over the past few years, Sahi Pro has helped a lot of customers achieve such business process automation, especially in the Automotive industry. With the upcoming Sahi Pro v11, automation becomes even more easy because of the no code flowcharts interface. The Flowcharts interface makes visualizing and managing automation very accessible to non-technical testers and business users. Sahi Pro 11 Beta is currently available. Reach out to us to play with Sahi Pro 11 Beta to get a POC done on your automation needs.

Author

Narayan Raman, CEO

Narayan is the CEO and founder of Tyto Software. He is the author of open source Sahi and the architect of Sahi Pro.

Sahi Pro is an exhibitor at EuroSTAR 2024, join us in Stockholm.

Autoethnographic research made me look at testing from a new angle

May 27, 2024 by Lauren Payne

Explore how autoethnographic research techniques overlap with testing behaviors and download a free template to try it yourself.

One of my favorite things about being a tester is the way testers find inspiration and techniques from outside of the testing world and integrate them into their work. In my graduate work I’ve been discovering the many ways that traditional research techniques overlap with testing behaviors, my favorite of which is autoethnographic research.

What in the world is autoethnographic research you ask? Let’s start by looking at ethnography, the research methodology this technique grew out of. Ethnography or ethnographic research is a research method typically used in the social sciences in which the researcher embeds and immerses themselves in a group, community, or culture. In ethnography we acknowledge that researchers will always have a personal slant or bias and instead of attempting to remove bias, instead seeks to learn and empathize with the subjects of the study. Some of the ways we document our findings using this method include journaling, field notes, and narratives of our experiences and observations.

Autoethnography takes ethnographic research one step further and uses the researcher themselves as a subject in the study. Often used in the social sciences, the researcher interrogates their own feelings and experiences in a group, community, or culture. This technique is often used when a researcher is studying their own culture or community, or when they are conducting research on a study of only themselves. Autoethnographic research also uses journaling, field notes, and narratives to document observations during the study.

A couple of real life examples of this technique used in action are:

In James Osben’s A day in the life of a NHS nurse in 21st Century Britain: An auto-ethnography: James wrote a narrative of his day as it happened. He then used critical analysis to find the overarching themes of feelings, tasks, and behaviors in the narrative of his shift. Osben’s aim in his research was to use “reflective practice.” Reflective practice is one of the ways a researcher reflects on, contextualizes, and reframes their experiences for their research.
Jay Johnson Theil explored her place in academia using ethnographic methods in her research Working-class women in academic spaces: finding our muchness: Theil used photography, reflective journaling, movie quotes, and storytelling as research methods, then applied critical analysis to better understand how she really feels about her role in academia.

Autoethnographic research works a lot like exploratory testing

If I’ve explained this well enough you may already see what I saw when first learning about this technique — autoethnographic research sounds like exploratory testing! I’ve long advocated for paying close attention to your thoughts and feelings as you work your way through an exploratory testing session. With this research method, you can take your exploratory testing even further. Here are a few ways to apply this method to your testing.

Journal your feelings while testing. As you work your way through whatever you’re testing, focus on how you feel and what you think. Do you feel frustrated, delighted, or confused? Whatever feelings the application elicit from you, write them down as you feel them. You may also consider other types of journaling using methods like color coded or face sentiment trackers.

Use voice narration. Narrate your thoughts and feelings to a voice app or Zoom session. To make sharing the narrated session easier for your team, you can use a transcription app or speech to text.

Reflect at the end of testing sessions. If you’re more interested in overall sentiment as opposed to thoughts and feelings in the moment, consider writing or narrating a reflection of thoughts and feelings from the testing session.

Debrief with your peers. Many teams hold debriefing sessions on a regular basis after exploratory testing. These sessions are the perfect time to share your thoughts and feelings documented in the session.

I will be the first to admit that I can’t remember what I did yesterday. Over time, I tend to forget my feelings towards the application I’m testing, which can hinder quality because my brain isn’t attune to looking for trends. Starting to use these autoethnographic techniques on an individual level will help you uncover trends in your reactions, thoughts, and feelings related to the application while you test.

You’ll have an even more impactful and beneficial experience if you use these techniques with your team and track over time. Some ways to do so are:

Bug summary journal: Keeping a log of bugs you’ve found and experienced in your application along with sentiment tracking towards each bug helps demonstrate the impact on quality that you feel each bug has. This will also help you see if there are periods when you feel bugs are related to sloppy code or a lack of understanding of the problem the team is trying to solve.

Daily journaling: Tracking your thoughts and feelings about the application on a daily basis will give you a timeline of your sentiment toward the application. This ongoing log gives you an opportunity to identify trends and track confidence in quality in your application over time.
Daily reflections: Similar to reflections at the end of a testing session, a daily reflection gives you a summary of the day. Over time, these reflections will expose trends and when compared with peers, may expose shared thoughts and feelings about the application that haven’t been identified previously.
Daily sentiment tracking: A lighter lift than some of the other options that can still expose trends. Each team member tracks their sentiment towards the application each day using either faces, color codes, or other tracking methods. This simplified tracking can help demonstrate changes in confidence in quality over time.

Integrating these techniques is a great way to help your team shift from testing to quality advocacy and demonstrate your ability to identify the quality indicators that have the biggest impact on the overall health and usability of your application.

Give these techniques a try with a free downloadable template from our Github resources.

Author

Jenna Charlton, QA and Developer Advocate

Jenna is a QA and Developer Advocate. They’ve spoken at a number of dev and test conferences and are passionate about testing, agile, teams, and developing the next generation of testers

Qase is an exhibitor at EuroSTAR 2024, join us in Stockholm.

Leveraging Effective Test Management to Mitigate Economic Uncertainty

May 24, 2024 by Lauren Payne

Economic uncertainty looms like a dark cloud over businesses, casting a shadow of unpredictability and challenges. From sudden market fluctuations to geopolitical events and policy changes, the business landscape is filled with obstacles that can cause budgets to shrink, timelines to shorten, and resources to become scarce. And it’s a global thing. The economic uncertainty that accompanies 2023 affects organizations all over the world and across different industries.

Effective test management can be a key strategy here, providing a solid foundation to reduce economic uncertainty and enable rapid adaptation to market changes. In this blog, we delve into the realm of test management and its remarkable potential to counter the adverse effects of economic uncertainty.

Understanding Economic Uncertainty

Economic uncertainty refers to a condition in which the future state of the economy, including factors such as growth, inflation, employment, and overall financial stability, becomes uncertain or unpredictable. Let’s break down the sources of uncertainty and the potential consequences following it.

Sources of Economic Uncertainty

Market fluctuations: rapid shifts in supply and demand, changes in consumer behavior, or economic downturns can create a volatile and uncertain market environment.
Geopolitical factors: political instability, trade conflicts, or regulatory changes can interrupt economic cycles and introduce uncertainty.
Policy changes: changes in fiscal policies, tax regulations, or government interventions can impact business operations and investment decisions, leading to increased uncertainty.
Global events: natural disasters and global economic or health crises (such as the COVID-19 pandemic) can significantly affect businesses worldwide.

Consequences of Economic Uncertainty on Businesses

Lower consumer confidence: economic uncertainty can harm consumer confidence, leading to cautious spending patterns and a decline in demand for products and services. Companies might see lower revenue as customers are more likely to cut expenses.
Financial instability: fluctuating market conditions and uncertain economic outlooks can pose financial challenges, including cash flow constraints, difficulty securing financing, or increased borrowing costs.
Investment hesitation: economic uncertainty often makes businesses more risk-averse, causing delays in capital investments, expansion plans, or research and development initiatives.
Supply chain disruptions: uncertainty can impact supply chains, causing disruptions in sourcing materials, increased costs, or delays in production and delivery.

The Value of Effective Test Management

Efficient software testing management can fulfill a vital role in mitigating economic uncertainty by providing businesses with structured approaches for quality assurance. The testing process is comprehensive and includes test planning, creation, execution, and defect management that are crucial to deliver high-quality software to the end-users.

Risk Management & Early Bugs Detection

When implemented effectively, test management plays a pivotal role in risk management and the early detection of bugs, benefiting companies in numerous ways.

By conducting thorough software testing, organizations can manage product-related risks by identifying and addressing them in the early stages of development. This proactive approach prevents these defects from escaping into production – when they are more costly to fix – and impacting the end-user’s experience. The end result is a reliable software product that meets business requirements and customer expectations.

High Flexibility & Adaptability

During uncertain times, project requirements may frequently change due to evolving market conditions or business priorities. Combining Agile practices in your software testing management enhances the organization’s ability to quickly respond to evolving requirements or changes in customer demands. Test managers collaborate with other stakeholders to understand the updated requirements, adjust test plans and strategies accordingly, and communicate any necessary changes to the testing team.

This way, companies can optimize software functionality and align it with shifting economic landscapes.

Combining Automation Testing

Automation plays a significant role in reducing costs and improving efficiency in software testing. Test managers leverage automation tools to perform tests that are prone to human error or extremely time-consuming. Businesses can significantly increase productivity and complete complex tests in a shorter time frame with high confidence, knowing the results are reliable. As automation eliminates the need for manual intervention, it minimizes the risk of human error and enables testers to focus on other critical aspects of the testing process.

Enhance Efficiency with a Test Management Platform

A great way to further improve the software testing management is using a dedicated test management tool. These comprehensive platforms offer a centralized solution for managing all types of testing activities such as planning, executing, tracking, and reporting. This helps to better manage test cases and defects, categorize them by status, prioritize them, and assign them effectively between staff that are on the same page.

One of the main benefits of these platforms is the reusability of tests. Rather than reworking and creating tests from scratch, QA testers can save precious time by reusing existing tests in other relevant projects or sprints. The tests that are designed for automated testing can be also managed through a test management platform. With powerful integration with automation frameworks and tools, QA managers can manage all types of tests within one platform and gain full transparency over the testing process.

Test management platforms provide comprehensive reporting capabilities, enabling test managers to generate meaningful reports of different testing artifacts. These reports help identify bottlenecks, track important QA metrics, and enable data-driven decision-making for process improvement.

With a test management platform, test managers and teams can streamline and optimize their testing efforts, resulting in improved efficiency, enhanced collaboration, and higher-quality software.

3 Tips for Effective Test Management

Here are three tips to help you navigate through these challenges and ensure effective test management:

Understanding & Adjusting Objectives

As customer and business needs rapidly change during economic uncertainty, it is essential for QA managers to closely collaborate with stakeholders. By working together, they can gain a deep understanding of the evolving needs and align internal QA objectives accordingly.

Transparent communication and increased collaboration are key elements of aligning testing assignments with the dynamic requirements. Prioritizing testing tasks according to these needs ensures that limited resources are utilized effectively, optimizing efficiency and customer satisfaction.

Embracing Modern Agile Practices

Agile methodologies offer numerous benefits in uncertain times. With Agile principles, such as flexibility, collaboration, and shifting left, organizations can respond quickly to changing needs and adapt their testing processes accordingly.

Incorporating concepts like Continuous Integration and Continuous Delivery (CI/CD) enables automated and frequent software releases, allowing for quick feedback and efficient bug fixes. Agile testing techniques such as exploratory testing, BDD, and automation further enhance adaptability and speed in a rapidly changing environment.

Embracing Modern Agile Practices

The final tip for effective test management is using a variety of testing tools. Utilizing multiple test automation and CI/CD tools covers diverse testing tasks, allowing for comprehensive and automated testing processes to be completed faster than ever. In addition, implementing a robust test management platform centralizes testing activities, streamlines collaboration, and provides a clear visibility into the testing progress from an end-to-end. The combination of testing tools will result in optimizing testing efforts and higher quality deliverables.

Summary

In the face of economic uncertainty, effective test management becomes essential for businesses to navigate challenges, mitigate risks, and deliver high-quality software products. In uncertain times, understanding dynamic customer needs, embracing modern Agile practices, and leveraging testing tools can help test managers better align with evolving customer requirements and enhance testing efficiency.

Additionally, leveraging testing automation tools and a robust test management platform such as PractiTest can increase productivity and ensure effective team collaboration. By implementing these strategies and adopting a proactive approach, organizations can navigate economic uncertainty with confidence, delivering reliable software that meets customer expectations.

Author

Practitest

Practitest is an end-to-end SaaS test management platform that centralizes all your QA work, processes, teams, and tools into one platform to bridge silos, unify communication, and enable one source of truth across your organization.

With Practitest you can make informed data-driven decisions based on end-to-end visibility provided by customizable reports, real-time dashboards, and dynamic filter views. Improve team productivity; reuse testing elements to eliminate repetitive tasks, plan work based on AI-generated insights, and enable your team to focus on what really matters.

Practitest helps you align your testing operation with business goals, and deliver better products faster.

Practitest is an exhibitor at EuroSTAR 2024, join us in Stockholm.