A testing methodology that verifies the complete workflow of an application from start to finish, ensuring all components work together as expected. Important for ensuring the reliability and performance of digital products, leading to better user satisfaction and fewer post-launch issues.
A quick and cost-effective usability testing method where feedback is gathered from users in informal settings, often in public places. Useful for gaining rapid insights into user behavior and improving designs iteratively.
A usability testing method where users interact with a system they believe to be autonomous, but which is actually operated by a human. Essential for testing concepts and interactions before full development.
User Acceptance Testing (UAT) is the final phase of the software testing process where actual users test the software to ensure it meets their requirements. Crucial for validating that the software functions correctly in real-world scenarios before its release.
An environment that replicates the production environment, used for final testing before deployment. Crucial for ensuring that digital products are thoroughly tested and perform as expected before going live.
The process of running a system for an extended period to detect early failures and ensure reliability. Important for ensuring the stability and performance of digital products before full-scale deployment.
A testing method that examines the internal structure, design, and coding of a software application to verify its functionality. Essential for ensuring the correctness and efficiency of the code in digital product development.
A preliminary testing method to check whether the most crucial functions of a software application work, without going into finer details. Important for identifying major issues early in the development process and ensuring the stability of digital products.
A performance testing method that evaluates the system's behavior and stability over an extended period under a high load. Essential for identifying memory leaks and ensuring the reliability and performance of digital products under prolonged use.
The use of software tools to run tests on code automatically, ensuring functionality and identifying defects without manual intervention. Crucial for maintaining high code quality and efficiency in the development process.
A type of usability testing conducted at the end of the design process to evaluate the effectiveness and overall user experience. Important for assessing the final design's usability and identifying any remaining issues.
A practice of performing testing activities in the production environment to monitor and validate the behavior and performance of software in real-world conditions. Crucial for ensuring the stability, reliability, and user satisfaction of digital products in a live environment.
A usability test to see what impression users get within the first 10 seconds of interacting with a product or page. Important for designers to quickly gauge initial user impressions and improve immediate engagement.
A non-production environment used for development and testing before deployment to production. Important for ensuring that changes are thoroughly tested before going live.
The process of testing and evaluating a design to ensure it meets user needs and business goals before final implementation. Crucial for ensuring that designs are effective and meet intended objectives.
The process of creating an early model of a product to test and validate ideas, features, and design choices before full-scale production. Essential for validating design choices and gathering user feedback early in the development process.
A test proposed by Alan Turing to determine if a machine's behavior is indistinguishable from that of a human. Important for evaluating the intelligence of AI systems.
A testing method that examines the code, documentation, and requirements without executing the program. Important for identifying defects early in the development lifecycle, improving the quality and reducing the cost of digital products.
Model-View-Controller (MVC) is an architectural pattern that separates an application into three main logical components: the Model (data), the View (user interface), and the Controller (processes that handle input). Essential for creating modular, maintainable, and scalable software applications by promoting separation of concerns.
Application Lifecycle Management (ALM) is the process of managing an application's development, maintenance, and eventual retirement throughout its lifecycle. Important for ensuring the sustainability and effectiveness of digital products over time.
An environment closer to production where final testing and validation occur. Crucial for ensuring that products are ready for production deployment.
A strategic approach where multiple potential solutions are tested to identify the most promising one. Crucial for innovation and reducing risk in decision-making.
A time-constrained, intensive process that helps teams quickly design, prototype, and test ideas. Important for rapidly developing and validating design solutions.
A development environment where software is created and modified. Crucial for allowing developers to build and experiment with new features.
A user-centered approach to problem-solving that involves empathy, ideation, prototyping, and testing. Crucial for developing innovative and effective solutions that meet user needs.
A research approach that starts with a theory or hypothesis and uses data to test it, often moving from general to specific. Essential for validating theories and making informed decisions based on data.
The process of testing product ideas and assumptions with real customers to ensure they meet market needs. Essential for reducing risk and ensuring product-market fit.
A research method in which participants interact with a series of potential product concepts in quick succession, providing rapid feedback on multiple ideas. Useful for quickly gathering user feedback on various concepts and iterating based on their preferences.
A statistical theory that states that the distribution of sample means approximates a normal distribution as the sample size becomes larger, regardless of the population's distribution. Important for making inferences about population parameters and ensuring the validity of statistical tests in digital product design.
A framework for discovering and validating the right market for a product, building the right product features, and validating the business model. Important for ensuring that products meet market needs and customer expectations.
A technology and research method that measures where and how long a person looks at various areas on a screen or interface. Crucial for understanding user attention and improving interface design.
A method of splitting a dataset into two subsets: one for training a model and another for testing its performance. Fundamental for developing and evaluating machine learning models in digital product design.
Behavior-Driven Development (BDD) is a software development approach where applications are specified and designed by describing their behavior. Important for ensuring clear communication and shared understanding between developers and stakeholders.
3-Tiered Architecture is a software design pattern that separates an application into three layers: presentation, logic, and data. Crucial for improving scalability, maintainability, and flexibility in software development.
The practice of quickly testing and iterating on ideas to validate assumptions and learn from user feedback in a short time frame. Essential for agile development and making data-driven decisions efficiently.
ARIA attributes that notify assistive technologies about updates to parts of the web page that can change dynamically. Important for improving the accessibility of live or frequently updated content.
Numeronym for the word "Compatibility" (C + 11 letters + Y), ensuring that systems, devices, or applications can operate together without conflict or need for modification. Crucial for ensuring seamless integration and functionality across different platforms.
A symmetrical, bell-shaped distribution of data where most observations cluster around the mean. Fundamental in statistics and crucial for many analytical techniques used in digital product design and data-driven decision making.
A user experience design methodology focused on rapid iteration, collaboration, and learning through experimentation. Essential for creating user-centered designs efficiently and effectively.
Also known as the 68-95-99.7 Rule, it states that for a normal distribution, nearly all data will fall within three standard deviations of the mean. Important for understanding the distribution of data and making predictions about data behavior in digital product design.
Artificially generated data that mimics real data, used for training machine learning models. Crucial for training models when real data is scarce or sensitive.
The process of turning potential customers into paying customers, often measured by the conversion rate. Essential for understanding and optimizing the customer journey.
The extent to which a measure represents all facets of a given construct, ensuring the content covers all relevant aspects. Important for ensuring that assessments and content accurately reflect the intended subject matter.
A user research technique where participants organize information into categories to inform information architecture and design. Essential for creating intuitive information architectures and improving user experience.
A set of ten general principles for user interface design created by Jakob Nielsen to improve usability. Essential for evaluating and improving user interface designs.
An experimental design where subjects are paired based on certain characteristics, and then one is assigned to the treatment and the other to the control group. Important for reducing variability and improving the accuracy of experimental results.
Numeronym for the word "Modularization" (M + 12 letters + N), dividing a system into separate, interchangeable modules that can be developed, tested, and maintained independently. Important for improving maintainability and scalability of systems.
Large Language Model (LLM) is an advanced artificial intelligence system trained on vast amounts of text data to understand and generate human-like text. Essential for natural language processing tasks, content generation, and enhancing human-computer interactions across various applications in product design and development.
User-Centered Design (UCD) is an iterative design approach that focuses on understanding users' needs, preferences, and limitations throughout the design process. Crucial for creating products that are intuitive, efficient, and satisfying for the intended users.
The process of designing, developing, and managing tools and techniques for measuring performance and collecting data. Essential for monitoring and improving system performance and user experience.
A tree-like model of decisions and their possible consequences, used in data mining and machine learning for both classification and regression tasks. Valuable for creating interpretable models in digital product design and user behavior analysis.
A statistical measure that quantifies the amount of variation or dispersion of a set of data values. Essential for understanding data spread and variability, which helps in making informed decisions in product design and analysis.
The spread and pattern of data values in a dataset, often visualized through graphs or statistical measures. Critical for understanding the characteristics of data and informing appropriate analysis techniques in digital product development.
Ensuring that color choices in design are inclusive and usable by people with color vision deficiencies. Crucial for creating accessible and inclusive designs.
Rapid Application Development (RAD) is a software development methodology that emphasizes quick prototyping and iterative delivery. Essential for reducing development time and adapting to changing requirements.
Plan-Do-Check-Act (PDCA) is an iterative four-step management method used for continuous improvement of processes and products. Essential for quality control and operational efficiency.
A statistical distribution where most occurrences take place near the mean, and fewer occurrences happen as you move further from the mean, forming a bell curve. Crucial for data analysis and understanding variability in user behavior and responses.
The ratio of interactive elements (links, buttons) to the number of goals on a landing page. Important for optimizing landing page design to improve conversion rates.
The practice of using data analytics and metrics to make informed decisions, focusing on measurable outcomes and efficiency rather than intuition or traditional methods. Important for optimizing design processes, improving product performance, and making data-driven decisions that enhance user experience and business success.
eXtreme Programming (XP) is an agile software development methodology focused on customer satisfaction and continuous improvement. It enhances software quality and responsiveness to changing requirements through frequent releases of functional software.