October 2023 Summaries

Recent updates have been introduced to enhance test case management tools, specifically for Xray and Zephyr. Xray users now have the capability to utilize non-text Jira custom fields within their Xray integration, accessible through the integration settings. Meanwhile, Zephyr Data Center users can now integrate with testRigor, enabling the linking and unlinking of test cases between testRigor and Zephyr, as well as updating the status in Zephyr after a test run in testRigor.

Test automation can often be a cumbersome and inefficient process, as illustrated by a company that hired numerous QA automation engineers only to produce a minimal number of test cases due to the persistent changes in the product and the high maintenance required for their test automation framework. Traditional methods like the Page Object Model can lead to excessive coding and maintenance challenges, often resulting in frustration and inefficiency as engineers are forced to constantly update their test scripts to accommodate changes in the application's interface. A more effective approach, as suggested, involves using generative AI tools such as testRigor, which allow test cases to be written in plain English, eliminating the need for complex coding and maintenance by adapting to changes in user actions and application functions rather than page elements. This innovative method not only saves time and costs but also aligns with modern DevOps and Agile practices, enhancing product quality and accelerating time-to-market.

In 2023, Android OS is used by over 3 billion people globally, highlighting the necessity for businesses to ensure their digital platforms function well on Android devices. The complexity of developing and testing apps across diverse devices and systems can be mitigated by using Android emulators, which simulate Android devices on a computer, allowing developers to test apps without needing multiple physical devices. These emulators provide a cost-effective and versatile solution for testing app functionality, performance, cross-platform compatibility, and usability, making them essential tools in the app development process. Automation testing, which can be efficiently executed using emulators, further enhances testing accuracy and speed by reducing manual testing efforts, supporting continuous integration/continuous deployment (CI/CD), and enabling parallel testing. The text also highlights testRigor, a cloud-based test automation tool that simplifies testing by using AI to write test cases in plain English, offering significant reductions in test maintenance time. However, it acknowledges that while emulators are beneficial, they have limitations and should be used alongside real devices for comprehensive testing.

Automation testing significantly enhances the quality assurance (QA) process by enabling faster, more consistent testing, reducing human error, and handling repetitive tasks efficiently. However, the selection of appropriate tools and frameworks is crucial to maximizing these benefits, as the market is saturated with various options that may not all meet specific needs. Key considerations in choosing a test automation framework include understanding project requirements, technology stack, testing objectives, team expertise, and budget constraints. Automation is particularly beneficial for projects requiring extensive test coverage and integration with continuous integration/continuous deployment (CI/CD) practices. The text emphasizes the importance of combining manual and automated testing for optimal results, with manual testing being ideal for exploratory and usability testing, while automation excels in repetitive and data-driven scenarios. It also highlights the advanced capabilities of tools like testRigor, which uses AI to simplify test creation and maintenance, allowing teams to write tests in plain English without needing specialized coding skills. This approach can significantly streamline the QA process, making it more reliable and efficient by reducing the maintenance burden and adapting swiftly to changes in the application under test.

Customer Relationship Management (CRM) has evolved from traditional sales and marketing practices into sophisticated software systems designed to enhance customer interactions and improve business profitability. These systems centralize customer data, enabling businesses to tailor their marketing, sales, and customer service efforts more effectively. The CRM market is projected to grow significantly, highlighting the increasing importance of these systems in managing customer relationships. However, CRM solutions present testing challenges due to complex workflows, the need for multi-platform support, and high testing costs, which can be mitigated through automation testing. Tools like testRigor offer automation capabilities by using AI to simplify test case creation, execution, and maintenance, allowing even non-experts to automate testing processes. TestRigor's flexibility in handling system updates and cross-platform testing, along with its integration capabilities, make it a popular choice for CRM testing, reducing maintenance efforts and enhancing collaboration among team members. As CRM systems continue to advance, selecting a robust automation testing tool becomes crucial for adapting to evolving business needs.

Testing in production, often perceived as risky, is being increasingly adopted by major companies as part of their quality assurance processes to enhance software reliability in real-world conditions. This approach involves deploying validated code into live environments using controlled strategies like A/B testing, canary releases, feature toggles, blue-green deployments, shadow traffic testing, and chaos engineering, all aimed at identifying issues that may not be apparent in pre-production testing. These methods help in gaining faster feedback, improving test coverage, and facilitating user-centric testing, ultimately leading to more robust and fault-tolerant systems. The benefits include a realistic testing environment, cost-effectiveness, and early issue detection, but it requires careful implementation with feature flags and other techniques to mitigate risks. Additionally, the use of automation tools like testRigor can streamline testing in production by simplifying test case creation and reducing maintenance, further ensuring a seamless user experience and compliance with necessary regulations.

Cypress, a popular testing tool, often encounters cross-origin errors due to the Same-Origin Policy, which prevents web pages from engaging in interactions across different domains for security reasons. These errors arise in various scenarios, such as direct cross-origin requests, opening new tabs or windows, interacting with iframes, or loading scripts from different domains. To resolve these issues, solutions include mocking requests, modifying application code, or configuring CORS headers. Despite its capabilities, Cypress faces challenges with error-proneness and limitations, leading to a decline in popularity. In contrast, testRigor emerges as a modern alternative, leveraging AI for test automation with features like automatic waits, cloud-based setup, and user-friendly script creation in plain English. TestRigor's advanced capabilities, including intelligent element detection and self-healing features, offer significant maintenance and cost benefits, positioning it as a compelling choice for contemporary web testing needs.

In today's technology-driven business environment, the Chief Technology Officer (CTO) plays a critical role in aligning technology strategies with business goals, enhancing customer satisfaction through innovative solutions, and promoting a strong quality assurance (QA) culture within the organization. The CTO is responsible for identifying emerging technologies, providing technical leadership, and ensuring projects adhere to best practices, which includes prioritizing QA to maintain high software quality and reliability. Effective QA processes are crucial for scaling technology infrastructure, minimizing bugs, improving customer trust, and ensuring regulatory compliance. The use of advanced tools like testRigor, an AI-driven, cloud-based platform, is highlighted as a means to enhance QA efficiency by simplifying test creation, migration, and maintenance, while promoting collaboration among teams and achieving cost-effective testing solutions. TestRigor facilitates easy creation and management of test cases in plain English, supports automation across multiple platforms, and integrates with various tools to create a comprehensive testing ecosystem, ultimately helping CTOs make informed decisions that positively impact business outcomes.

Cypress, a tool used for testing web applications, often encounters the error "CypressError: Timed out retrying: Expected to find element," which typically arises when the tool cannot locate a specific HTML element within a given timeframe due to issues such as timing, incorrect selectors, flaky tests, or race conditions. To resolve this, testers can check element existence, adjust timeouts, correct selectors, and use Cypress's built-in commands for waiting, among other strategies. However, the text suggests that modern tools like testRigor offer advanced features that address these issues more efficiently. TestRigor uses AI-powered algorithms to handle synchronization problems automatically, eliminating the need for explicit wait times, and offers user-friendly script creation in simple English, making test automation accessible even for non-technical team members. It is cloud-hosted, supports multiple browsers and platforms, and features self-healing capabilities that update test scripts as UI changes, reducing maintenance efforts significantly. The text emphasizes testRigor as a superior alternative to Cypress, encouraging users to consider it for more efficient and modern test automation.

Cypress users frequently encounter the error message "The test has finished, but Cypress still has commands in its queue," which indicates unexecuted asynchronous commands remain after a test script concludes. This issue can arise from asynchronous operations exceeding timeouts, unexpected errors, failed assertions, or incorrect command sequencing. Resolving it involves adjusting Cypress configurations, debugging scripts, and ensuring assertions are correctly written. Despite Cypress's capabilities, it is often seen as less advanced compared to modern tools like testRigor, which leverages AI for automatic wait handling and test generation, allowing for codeless and user-friendly test script creation. TestRigor's features, including self-healing capabilities and cloud-hosting, cater to contemporary automation needs by minimizing maintenance and offering universal compatibility, positioning it as a superior alternative for efficient software testing.

Cypress, a popular tool for end-to-end testing of web applications, enforces a single-origin policy that often results in the error "cy.visit() failed because you are attempting to visit a second unique domain" when tests inadvertently navigate to multiple domains. This limitation can be mitigated by organizing tests to focus on a single domain, using hooks like beforeEach for setup, employing cy.request() for cross-domain interactions, and managing domain transitions carefully. While Cypress is valued for its testing capabilities, its limitations have prompted the exploration of alternative tools like testRigor, which offers AI-driven automation features such as automatic test generation, cloud integration, and no-code test script creation. TestRigor's innovative approach, including smart element locators and broad compatibility, positions it as a strong contender in the automation testing landscape, appealing to those seeking efficient and modern solutions for test automation.

The "Cypress cannot execute commands outside a running test" error is a common issue encountered in the Cypress testing framework, arising when commands are run outside a specific test context, such as in the global scope or through incorrectly used custom commands and asynchronous code. To avoid this error, it is crucial to place Cypress commands within test cases (it blocks) or appropriate hooks, use .then() for asynchronous operations, and ensure proper test file structure and configuration. As the field of test automation evolves, tools like testRigor offer advanced solutions with AI-driven algorithms for automatic test generation, cross-browser support, and intuitive script creation using plain English, presenting a more modern and efficient alternative to Cypress. TestRigor's cloud-hosted platform simplifies setup and maintenance, allowing users to quickly develop automated test scripts without deep programming knowledge, thereby reducing time spent on debugging and maintenance.

The text discusses the common causes and solutions for the "Support file missing or invalid" error in Cypress, a popular testing framework, which typically arises due to issues like incorrect file paths, syntax errors, missing files, or dependency conflicts. It outlines steps to resolve these issues, such as verifying file paths, checking for syntax errors, ensuring the presence of the support file, updating dependencies, and configuring environment-specific settings properly. In contrast, the text introduces testRigor as an alternative automation tool that leverages AI for automatic test generation, easy test script creation in plain English, and cross-browser/platform support, highlighting its advantages such as reduced maintenance time and ease of use compared to traditional frameworks like Cypress. TestRigor is presented as a modern, cloud-based solution that simplifies automation testing with features like self-healing test scripts, AI-driven locators, and a codeless scripting approach, making it a compelling choice for Agile development environments focused on rapid releases.

Encountering the "cy...() failed because the element cannot be interacted with" error in Cypress often indicates issues with interacting with web page elements during testing, which can stem from problems like incorrect selectors, element visibility, or timing discrepancies. Addressing these issues typically involves using Cypress commands such as cy.get(), cy.wait(), and cy.log() to ensure elements are present and interactable, along with debugging practices like console logging and Cypress Playground mode. However, Cypress's approach may demand significant troubleshooting, which can detract from expanding test coverage. As a modern alternative, testRigor offers AI-driven automation that simplifies testing through features like automatic wait handling, auto-generated test scripts, and an intuitive, codeless interface, while also supporting cross-browser and cross-platform testing. TestRigor's self-healing capabilities and unique element locator methods further streamline test maintenance and creation, positioning it as a cutting-edge solution in the rapidly evolving landscape of web automation tools.

The "No tests found" error in Cypress arises when the testing framework fails to locate any test files, often due to issues like incorrect file paths, misconfigurations, empty test files, or naming conventions not being followed. Solutions include verifying file paths, ensuring correct test file extensions, checking file encoding, clearing caches, updating dependencies, and using debugging tools. Additionally, the text highlights the benefits of using modern automation tools like testRigor, which offers AI-powered features such as automatic test generation, cloud hosting, and self-healing capabilities for test scripts, making it a robust alternative to older testing frameworks. By adopting testRigor, users can enjoy streamlined test creation in plain English, cross-browser support, and reduced maintenance, thus enhancing overall testing efficiency.

Encountering the error message "We Found an Error Preparing Your Test File" in Cypress often results from issues in the setup or configuration of Cypress test files, such as syntax errors, missing plugins, incorrect file locations, or circular dependencies, and can be resolved by careful debugging and configuration checks. The document suggests that while Cypress is a useful tool, modern alternatives like testRigor offer significant advantages, including AI-driven test script generation, codeless automation, and enhanced stability without flaky tests, making them suitable for today's dynamic DevOps and Agile environments. testRigor's features, such as automatic test case generation, cross-browser support, and flexibility in element identification, aim to streamline the testing process and reduce maintenance time, providing a compelling argument for teams to consider transitioning to this cutting-edge tool as a more efficient solution for automation testing.

Governments worldwide are increasingly leveraging technology to enhance efficiency and address complex challenges, such as climate change, corruption, and economic disruptions, through innovations in cybersecurity, data analytics, and artificial intelligence. This digital transformation includes the use of online portals for taxes and licenses, smart city initiatives, enhanced crime control measures, and improved citizen communication. As technology becomes integral to government operations, software testing is crucial to ensure the reliability and security of applications, with methods like end-to-end and security testing playing vital roles. Test automation tools such as testRigor offer solutions by using AI-driven test creation to maintain software quality without the need for extensive technical expertise, thereby allowing governments to effectively manage evolving technological landscapes while maintaining high standards of data security and user accessibility. This approach facilitates collaboration among government entities and enhances the delivery of public services, despite the inherent challenges like cybersecurity threats, diverse user bases, and the integration with legacy systems.

DevTestOps represents an evolution of the DevOps framework by incorporating continuous testing into the software development lifecycle, ensuring faster and higher-quality product delivery. It emphasizes collaboration among development, testing, and operations teams to enable early and frequent testing, often referred to as "shift left" testing, which aims to catch defects early in the development process. This approach integrates continuous integration, continuous deployment, and continuous monitoring practices, while also encouraging the use of tools like testRigor to simplify and automate testing processes. Although adopting DevTestOps offers significant benefits in streamlining software delivery and improving quality, it also presents challenges such as toolchain complexity, skill gaps, and the need for seamless integration into existing workflows. The shift to DevTestOps requires not only technological changes but also a cultural transformation to foster collaboration and open communication, ultimately enhancing an organization's ability to adapt to market demands and customer feedback.

The text explores the complementary roles of manual and automated testing in software quality assurance, emphasizing the strengths of each method and the potential enhancements brought by artificial intelligence (AI) in testing processes. Manual testing is highlighted for its human judgment, creativity, and ability to handle complex, user-centric, and early-stage testing scenarios, while automation testing is praised for its efficiency, reproducibility, and capacity to handle large test suites and perform tasks like regression and performance testing. AI-driven tools, such as testRigor, are noted for their ability to simplify automation without requiring programming skills, offering features like text-based locators and self-healing capabilities that drastically reduce maintenance efforts and costs. The integration of AI into testing workflows promises to revolutionize the software testing landscape by enhancing both manual and automated testing, ultimately contributing to the development of high-quality software products.

TestOps is an emerging framework within the software development ecosystem, emphasizing scalable test automation to enhance testing efficiency and integration within the DevOps pipeline. It comprises four key components: test planning, control, management, and insights, each playing a vital role in optimizing the software testing process. TestOps focuses on seamless collaboration and communication among teams, integrating continuous monitoring and feedback loops to ensure software quality and compliance. By leveraging test automation tools like testRigor, TestOps aims to streamline the testing phase, reduce manual efforts, and support dynamic, fast-paced development environments. TestOps is a crucial subset of DevOps, focusing specifically on testing efficiency while maintaining alignment with DevOps principles to deliver high-quality software.

In 2018, approximately 12.6% of the U.S. civilian population had some form of disability, highlighting the importance of the Americans with Disabilities Act (ADA), which mandates equal access to digital platforms. Ensuring ADA compliance in app development is crucial, as non-compliance can lead to legal challenges and lost business opportunities. Developers are advised to incorporate accessibility from the start by understanding ADA guidelines, using semantic HTML, providing alternative text, and enabling keyboard navigation. AI and automation tools, like testRigor and Deque axe DevTools, can significantly aid in ADA compliance by performing automated accessibility testing, offering remediation suggestions, and integrating with development workflows. These tools enhance the inclusivity of digital content, reduce support costs, and ensure legal compliance. While AI offers efficiencies, manual testing and real user feedback remain essential to verifying accessibility, contributing to a more inclusive digital experience and opening new market opportunities.

Software testing is a significant part of the software development lifecycle, often consuming 20-30% of the IT budget, and involves various costs influenced by the project's complexity, testing scale, tools, team size, and methodologies. The concept of Cost of Quality (COQ) in software testing encompasses prevention, appraisal, internal failure, and external failure costs, with prevention focusing on activities to avoid defects, appraisal on detecting defects early, internal on addressing defects found during development, and external on issues discovered post-release. To optimize testing costs without sacrificing quality, strategies such as test automation, early shift-left testing, minimizing test maintenance, and efficient test data management are recommended. Tools like testRigor enable automation, allowing non-programmers to write test cases, while other approaches include optimizing test environments, leveraging crowdsourced testing, prioritizing test cases based on risk, and fostering continuous improvement in testing processes. Ultimately, the goal is to deliver high-quality software efficiently while minimizing unnecessary expenses and maximizing resource utilization.

Scalable test automation is crucial in modern software development, particularly in Agile and DevOps environments, where rapid release cycles are common. This approach allows the testing framework to adapt to increasing complexity and functionality without significantly increasing resources or effort. Key strategies for achieving scalability include modular test design, parameterization, parallel execution, continuous integration, and effective test data management. The use of cloud-based infrastructure and tools like testRigor further enhances scalability by providing flexible environments and reducing maintenance overhead through features like AI-powered self-healing capabilities and plain English test automation. Test scalability is essential due to the growing complexity of software, the need for quick testing updates, and maintaining consistency and competitive advantage. While challenges such as initial investment and maintenance overhead exist, solutions like no-code automation tools and cloud-based services can mitigate these issues, making scalable test automation an effective strategy for ensuring software quality and reliability as applications evolve.

Automation testing tools are essential in the fast-paced software development landscape, offering efficiency, reduced costs, and enhanced productivity by replacing manual testing processes. The text discusses several popular tools, highlighting their unique features and functionalities. JUnit, an open-source framework, is ideal for unit testing in Java applications with its annotations, parameterized tests, and integration with build tools. Postman excels in API testing without needing code, supporting collections, environment variables, and CI/CD integration. LambdaTest offers cloud-based cross-browser testing with real device support and comprehensive integrations. Apache JMeter is renowned for performance testing, supporting load and stress testing across various protocols. testRigor leverages AI for quick, codeless test creation and maintenance, supporting cross-platform and API testing. OWASP ZAP focuses on security testing, offering automated scanning and CI/CD integration. Datadog provides real-time analytics and monitoring capabilities, seamlessly integrating into CI/CD pipelines for comprehensive application performance insights. The choice of testing tool ultimately depends on factors such as testing objectives, budget, and team skills, with AI-powered tools like testRigor significantly enhancing software quality and testing efficiency.

Test automation is essential for overcoming the limitations of manual testing, which include excessive resource requirements, limited test coverage, monotony, scalability issues, and inconsistency, making it unsuitable for Agile and DevOps environments. Automation testing offers numerous advantages such as accuracy, speed, broader coverage, reusability, and compatibility with continuous integration/continuous deployment (CI/CD) pipelines, which enhance testing efficiency and cost-effectiveness. Common types of automation tests include unit, integration, functional, regression, and security tests, each serving specific purposes in the software development lifecycle. Automation tools like Selenium, Appium, testRigor, and Postman facilitate various testing needs, from UI to API testing, while intelligent test automation platforms help maximize return on investment (ROI) through features like self-healing tests and data-driven testing. While automation is not suitable for exploratory or usability testing, the right balance between automated and manual testing can be achieved through strategic planning and tool selection, ensuring comprehensive test coverage and reliability.

The software testing industry in the United States is valued at $6.8 billion as of 2022, with a significant proportion of QA testers being self-taught, indicating substantial growth potential and accessibility for aspiring testers. A successful career in software testing involves understanding the role of a QA tester, which includes testing software, identifying bugs, and ensuring product quality, often requiring a background in computer science or related fields, although self-learning through online resources is also viable. Familiarity with testing methodologies and tools, such as Selenium and testRigor, is crucial, along with gaining hands-on experience through practice and building a portfolio. Networking, obtaining certifications like ISTQB, and continuous learning are essential for career advancement, with potential specialization areas including automation, performance, and security testing. Career progression can lead from entry-level positions to roles such as QA Manager or Director of Quality Assurance, with the industry offering a dynamic landscape where persistence, skill development, and proactive engagement are key to success.

First impressions are crucial in user interface (UI) design, as an intuitive and attractive system UI can significantly impact user satisfaction and business success. System UI refers to elements on a screen, aside from apps, provided by the operating system to control the system, and it can be customized without updates. A well-designed system UI enhances user experience, boosts productivity, reduces support queries, and promotes branding by establishing a distinctive visual identity. It is essential to test system UI across various aspects such as usability, functionality, accessibility, and performance to ensure it meets user needs and compliance standards. Automation tools like testRigor facilitate this process by simplifying test creation and maintenance through AI and plain-English commands, making it accessible for a wide range of team members. TestRigor's capabilities extend across platforms and integrate with various tools, reducing the challenges of test maintenance while supporting comprehensive testing of system UIs.

Technological advancements are significantly impacting the healthcare sector, with various technologies such as AI, ML, NLP, big data, and cloud computing being utilized to enhance patient care, improve operational efficiency, and support medical research. The need for thorough healthcare software testing is emphasized due to the critical nature of the industry and stringent regulatory requirements like HIPAA and GDPR. Key testing areas include electronic health records, telemedicine platforms, and medical administrative systems, focusing on functional, usability, compliance, and security aspects. Automation tools like testRigor, which use AI-driven methodologies, are transforming healthcare testing by offering features such as negligible test maintenance, no-code test creation, cross-platform testing, and data-driven testing, thus ensuring high-quality applications and reducing the burden of manual testing. TestRigor's ability to adapt to changes through self-healing capabilities and its compliance with security standards make it an effective solution for maintaining robust healthcare applications.

This week, a new feature was released that allows API calls to use multiple body parameters, enhancing the ability to validate API call requests with either text or JSON paths. Users can add new body parameters using the "and" command, and the parameter type can be defined as either text or JSON path. By default, text is used when no type is specified, and testRigor will compare the value directly. JSON, on the other hand, requires a key-value pair separated by a colon and is only used when specified. JSON path is a more advanced option that allows for greater flexibility and power in specifying parameters. It is possible to mix different parameter types in a single API call, providing a robust approach to API validation.

In automated testing with Cypress, the error "cy.visit() failed trying to upload" typically arises when Cypress encounters issues visiting a webpage during a test run, particularly when dealing with file uploads. Common causes include incorrect URLs, page load issues, missing file input elements, incorrect file paths, network problems, and authentication errors. To address these, testers should verify the accuracy of URLs, ensure robust network connections, handle authentication properly, and confirm file paths and input elements are correct. Debugging tools such as Cypress’s interactive test runner and logging features can aid in diagnosing issues. While Cypress is a widely used tool, newer automation tools like testRigor offer advanced features such as simplified file uploads and codeless test script creation, positioning themselves as innovative solutions in the rapidly evolving landscape of web automation testing.

The article explores the advantages of test automation over manual testing, highlighting its ability to enhance application quality, reduce costs, and increase efficiency by minimizing human error and expediting the testing process. Test automation, exemplified by tools like testRigor, enables rapid and consistent testing through predefined scripts, offering benefits such as improved accuracy, faster feedback in CI/CD pipelines, and comprehensive test coverage across multiple platforms. Various industries, including telecom, banking, ERP, cybersecurity, healthcare, e-commerce, automotive, gaming, aerospace, and energy, leverage test automation to ensure functionality, security, and compliance, ultimately supporting innovation and quality assurance. The article emphasizes the transformative potential of AI-powered test automation tools, which provide scalable, data-driven testing solutions that transcend industry boundaries, facilitating faster development and delivery while reducing maintenance efforts and costs.

Cypress is a widely-used end-to-end testing framework for web applications, allowing developers to execute tests in a real browser environment, but it can encounter timeout errors when actions or assertions exceed specified time limits. These timeouts, such as command, request, page load, and response timeouts, are essential for test stability but can occur due to factors like slow networks, element visibility issues, long-running commands, or heavy page loading. Debugging these errors involves inspecting detailed error messages, logging information, and assessing application performance. Cypress provides built-in waiting commands, retry mechanisms, and allows increasing default command timeouts to mitigate these issues. However, newer automation tools like testRigor, leveraging AI-powered algorithms, are emerging as alternatives to Cypress, offering features like custom element selectors, inbuilt waits, and parallel execution to efficiently handle timeout errors and align with modern technology trends.

This week's update introduces new features including if/else logic and a customizable time zone setting for test cases. The if/else logic allows for the creation of complex scenarios by enabling multiple conditions and commands per condition, facilitating actions based on the content found on a page. Users can implement single or multiple conditions with corresponding actions or defaults, as outlined in the documentation. Additionally, a new time zone setting has been added under Settings -> Advanced, with a default of PST, which affects the execution of test cases and the generation of times for built-in variables across all platforms. New built-in variables related to time, such as nowHourAmPm, nowHourTwoDigitsAmPm, and nowAmPm, have been introduced to enhance time-based functionality within test cases.