James Malinchak: Crafting Success Through 5 Core Business Beliefs

Portland News Staff on January 23, 2024

James Malinchak, a stalwart in the speaking and coaching arena, has etched his name in the industry not by chance but by adhering to five fundamental business beliefs. These principles are the bedrock of his success, elevating him to a leadership position in the competitive world of motivational speaking and coaching.

1. Purpose Driven: Making a Difference

For James, success goes beyond financial gains; it’s about making a difference. Being purpose-driven is not just a tagline but a guiding principle that shapes every decision he makes. By prioritizing purpose, James sets a standard that emphasizes the impact a business can make in the world, fostering a sense of fulfillment that transcends mere profitability.

2. Integrity Based: Earning Trust, Serving Others

Integrity is not just a buzzword for James; it’s a way of doing business. His second core belief revolves around doing what he says and, in turn, earning trust. This commitment to integrity extends beyond business transactions, creating genuine connections. By prioritizing service, James builds relationships that stand the test of time, fostering a network of connections that goes beyond the professional realm.

3. Serving Others: Creating Lifetime Friendships

For James, business is about more than transactions; it’s about serving others. This core belief places the well-being of others at the forefront, resulting in lasting connections and friendships. James has not only built a successful business but also a community of individuals sharing a common goal of positive impact and growth.

4. Student First: Taking Excellent Care of Our Students

As a renowned speaker marketing coach, James’s commitment to his students is unwavering. Placing them at the forefront of his business philosophy, he ensures that each student receives exceptional care. This dedication has created a global community of learners spanning over 100 countries. James’s focus on putting his students first sets a standard for excellence in coaching and mentorship.

5. Amazing Content: Over-delivering and REALLY Teaching

The final core belief, ‘Amazing Content,’ underscores James’s commitment to excellence. By over-delivering and truly teaching, he ensures that every interaction, every piece of advice, adds significant value. This dedication to providing exceptional content has not only set James apart in the speaking industry but has also solidified his position as a leading authority in coaching and training.

James Malinchak: A Multifaceted Approach to Success

Beyond these core beliefs, what sets James apart is his multifaceted approach to the industry. As a behind-the-scenes marketing advisor, philanthropist, and speaker, he is not just a speaker but a catalyst for positive change. His guiding principles encapsulated in the ‘5 Core Business Beliefs’ have positioned him as the world’s leading speaker trainer and coach.

Impact and Aspirations

James’s impact extends beyond the stage. He envisions impacting one billion lives, a mission he pursues through teaching others to become speakers, authors, and coaches. For James, success is not just about personal achievement but about leaving a lasting legacy of positivity, inspiration, and service.

Final Thoughts

In a world where success stories often feel distant, James Malinchak’s journey stands as a beacon of hope and inspiration. His 5 Core Business Beliefs offer a blueprint not just for entrepreneurial success but for making a meaningful difference in the lives of others. As James continues his mission to impact a billion lives, we can all learn from his principles – a set of beliefs that began as a personal code but has now become a universal guide for success. James Malinchak’s message is clear: Now is your time to share your voice, your story, your message – because the world needs you.

Published by: Nelly Chavez

How Can Testers Collaborate and Communicate with AI and ML Developers and Stakeholders?

Portland News Staff on January 23, 2024

Image Commercially Licensed from: Unsplash

Artificial intelligence (AI) and machine learning (ML) transform software development and testing. As these technologies become more prevalent, testers must adapt how they work with AI/ML developers and stakeholders. Effective collaboration, communication, and automation testing ensure that AI/ML systems are thoroughly and adequately tested.

This article will discuss how testers can collaborate and communicate with AI and ML developers and stakeholders.

Understand the basics

Start by understanding that AI and ML rely on data – and lots of it – to detect meaningful patterns that can then guide automated decisions and predictions.

Developers train machine learning models on large datasets, providing many examples that enable an algorithm to learn how to map different inputs to desired outputs over time. Testing data is used to validate the models are working as expected before being put into production.

It’s also crucial to know that while AI promises business value via insights and automation, the technology has blindspots. Machine learning models can perpetuate biases that exist in training data. They also lack human context and judgment, making explainability and transparency around AI decision-making crucial.

Defining Expectations for AI/ML Testing

Start by facilitating focused sessions with technical and business stakeholders to align on core objectives, requirements, and success criteria. Document these diligently. Seek to identify high-risk areas like security, fairness, safety, and unintended outcomes that require rigorous testing.

Define quantitative success metrics and thresholds for performance, accuracy, error rates, and other key parameters. Outline how models will be evaluated pre and post-deployment through cross-validation, A/B testing, and monitoring.

Develop clear processes for reporting issues found during testing, including severity levels and escalation protocols. Create feedback loops to capture insights that can rapidly improve models.

Choose the Right Tools

Testing machine learning systems necessitates an evolved toolkit for evaluating dynamic, data-fueled software that continues learning after deployment. Rather than testing static code logic, QA analysts must verify customized AI algorithms and models that extract insights from new data flowing through production systems.

While coding fluency isn’t essential, become conversant in popular ML programming frameworks like TensorFlow, PyTorch, or Keras to understand how engineers build and iterate on neural networks.

In addition to open-source frameworks, leveraging a cloud-based test automation platform like LambdaTest can be extremely beneficial for testing ML applications. LambdaTest offers scale, speed, and advanced automation capabilities specifically designed for AI/ML testing needs

Adopting an Exploratory Mindset

Artificial intelligence and machine learning systems pose unique challenges for testing due to their non-deterministic and constantly evolving nature. Adopting an exploratory mindset is essential for testers to address AI/ML complexity.

With exploratory testing, testers take an investigative approach focused on learning versus pass/fail assessments. Exploratory testing emphasizes curiosity, creativity, and flexibility to uncover insights about a system’s capabilities and flaws.

For AI/ML, this means crafting dynamic test charters focused on high-risk areas versus pre-defined test cases. Rather than scripts, utilize checklists and heuristics to guide deep interactive sessions with models.

Collaborate with the AI/ML Developers

Testing machine learning systems requires a highly collaborative approach between QA and the engineers building the product. To be effective, testers should initiate open lines of communication and seek to comprehend both the human and technical parts of the systems being developed.

Start by asking developers plenty of questions – don’t assume all AI/ML application aspects will be intuitive or familiar. Request architects walk you through the data pipelines, model training processes, underlying algorithms, and how predictions are made.

As testing progresses, maintain an open line of communication to provide visibility and reassurance. Convey what tests you are running and their limitations in surface area and environments covered. Forewarn technology leaders that early results may reveal gaps between stakeholder expectations and current model capabilities.

Conclusion

Testing artificial intelligence and machine learning systems demands teamwork and constant communication between those building the technology and those tasked with assessing it.

By embracing a collaborative spirit and aligning on shared objectives, testers can maximize their positive impact and bolster the adoption of AI that users can trust.

Rather than be intimidated by the complexity, they should candidly talk with developers to demystify unfamiliar concepts. Equipped with basic literacy around data, algorithms, and training processes, they can design pragmatic test plans that evaluate real-world viability.

Published by: Nelly Chavez

How do developers and product owners collaborate to define acceptance criteria for user stories?

Portland News Staff on January 23, 2024

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User stories aim to describe what the user wants the application to do. It provides a high-level understanding of a feature from the end user’s perspective.

Whereas the acceptance criteria are essentially mobile app testing, an application must pass to demonstrate that it has met all the user requirements.

User stories describe the desired outcome; acceptance criteria outline the steps to achieve that outcome by offering a checklist ensuring the feature behaves as intended from an end-user perspective.

This article will explore how developers and product owners can collaborate to define acceptance criteria for user stories to drive their testing process.

What are the acceptance criteria?

Acceptance criteria are a set of several prerequisites and conditions to validate an application meets its requirements to be accepted by end users to consider a user story to be finished.

They aim to define a product’s expected behaviors, functionalities, and outcomes, but they do not delve into finding out the specific steps to achieve these outcomes or implement a specific functionality. This is because the purpose of acceptance criteria is to state the aim, not the solution.

What are user stories?

A user story is essential and the first step to excellent application development. It helps to clearly define what users want. This encourages collaboration among developers, testers, and stakeholders to work together and create an application that meets their needs and provides a more satisfying user experience.

Importance of acceptance criteria for user stories

The criteria reflect what the users want instead of what the developers think they want. More often, user stories can be vague and open to interpretation if not defined correctly. In that case, it is possible for functional requirements to match with user stories but not reflect their intent.

When should acceptance criteria be created?

Before the beginning of development, acceptance criteria must be created. Their use marks the point of development where the user story is finished satisfactorily. Well-written acceptance criteria prevent unexpected results at the end of a development stage and help ensure that all stakeholders and users are satisfied with the final result.

Tips to collaborate and write user stories

Acceptance criteria are needed for a user story to be considered done and ready for testing.

Understanding the user story

In application development, understanding the users’ needs is crucial. Therefore, the first step in collaborating with developers and product owners on acceptance criteria is understanding the user story from an end-user perspective.

Defining the scope and boundaries

The next step in establishing smooth collaboration is to define the scope and boundaries of the user story. The most effective way to do this is by describing the main features, functions, processes, and interactions the user story covers.

Considering the definition of “done”

Another step to build collaboration with developers and product owners is to align the acceptance criteria with the definition of done (DoD). The DoD is a checklist that applies to all user stories and ensures they are consistent, complete, and ready for delivery.

Contributing to writing acceptance criteria

Usually, the product owner or product manager gets this responsibility because they better understand the users’ needs and hold the vision for the final product outcome to ensure that acceptance criteria are written from the end user’s perspective.

To streamline acceptance testing and accelerate the application release, running acceptance tests using best-automated tools compatible with the testing needs is essential.

LambdaTest is an AI-powered test orchestration and execution platform to run both manual and automated tests at scale and meet testing demands. Testers can use this platform to test their application’s performance under varying conditions, ensuring it meets end users’ expectations.

Conclusion

Acceptance criteria are an important aspect of every user story the team works on. It clearly defines the scope, desired result, and testing criteria functionalities the delivery team is working on.

A user story can only be interpreted when the acceptance criteria are defined, provide complete clarity on the expected outcomes, and allow both the users and the developer to sync with the functionality that a user story will provide.

Published by: Nelly Chavez

How to Handle Dynamic Web Elements and Locators in the Page Object Model Framework?

Portland News Staff on January 23, 2024

Image commercially licensed from: Unsplash

Identifying the web elements using locators like ID, Name, XPath, or CSS from the HTML snippets seems straightforward.

But it isn’t always that simple. Sometimes, IDs and classes of web elements keep changing. Such elements are called Dynamic Web Elements. These are database-driven elements whose values refresh when the database updates.

This article will discuss how to handle dynamic web elements and locators in the page object model framework.

What is the Page Object Model (POM)?

The Page Object Model (POM) is a design pattern used in Selenium test automation to create an object repository for web elements.

POM encapsulates the web elements of each page in the application into separate “page object” classes. These classes act as repositories that contain the locators and methods for interacting with the UI components on that page.

The page object classes are typically stored under a separate package like “pages.” The test classes use the methods encapsulated in these page objects to interact with the application under test.

Why Page Object Model?

The below-mentioned points depict the need for a Page Object Model in Selenium.

Page Object Model centralizes the element locators and access methods in one place, avoiding duplication.
Without Page Objects, testers need to individually update every test script accessing that element if an element changes. With Page Objects, only the central Page Object definition requires updates to propagate to all tests.
If elements change, only the single Page Object class needs alteration rather than potentially thousands of test case scripts. This simplification enables maintenance.
If primary UI revamps occur, like relocating menu buttons without Page Objects, the effort to update affected tests is proportional to usage volume. However, Page Objects localize the required changes to just the Page Object mapping the impacted elements, minimizing overall update effort.

Handling Dynamic Web Elements in Selenium

There are many ways to handle dynamic web elements; here are some examples:

Explicit Waits

Explicit waits are among the most common and practical methods for handling dynamic elements that take time to load or frequently change state.

Fluent Waits

Fluent waits are an extension of explicit waits that provide further configurability and flexibility when dealing with dynamic elements. It allows setting variable polling intervals that adjust how often a check occurs.

CSS Selectors and XPath

When website elements lack reliable or static IDs and attributes that Selenium can latch onto, CSS selectors and XPath expressions become invaluable for consistently locating the desired elements.

These advanced locator strategies have enough flexibility to model some of the dynamic aspects of web pages.

Frames

Selenium provides browser frame management with commands like switchTo().frame() to lock onto a frame before querying nested elements within. The script clarifies where the focus lies at any moment rather than relying on the ambient state. This prevents confusion if underlying UI layers suddenly reload or redirect.

Multi-Attribute Locators

When singular attributes like IDs or class names lose reliability on dynamic pages, multi-attribute locators help recover uniqueness by combining several changing attributes.

Refreshing Page

Sometimes simplicity is best. When dynamic elements fail consistently despite best efforts, restarting the browser or navigating away from and back to the page can reset enough state to reload troublesome elements.

Retrying Search

Like refreshing pages, retry loops take an external control approach to dynamically appearing elements; rather than fine-tuning internal locators, we wrap searches in repetition logic to cover uncertain emergence.

Use Page Factory and Annotations

Page factory is a class provided by Selenium WebDriver that helps initialize web elements in Page Object Model (POM) classes using annotations.

Cloud-based testing platforms like LambdaTest can simplify handling dynamic elements in test automation. LambdaTest offers features like visual AI-based debugging and screenshot comparisons to instantly detect and debug discrepancies in dynamic UI components.

Conclusion

Dynamic web applications require test automation frameworks that accommodate frequent UI elements and locator changes. A well-structured Page Object Model provides a robust foundation to manage these evolving frontends.

Using LambdaTest’s online Selenium grid, tests can run against dynamic web pages loaded in the latest versions of all major browsers like Chrome, Firefox, Edge, and Safari. Cross-browser testing helps catch inconsistencies in how dynamic content renders across different environments.

Published by: Aly Cinco