105 topics found for:

“computational design”

Generative Design

An iterative design process that uses algorithms and computational tools to generate a wide range of design solutions based on defined constraints and goals. Crucial for exploring innovative and optimized design solutions.

UI Design

The design of user interfaces for machines and software, such as computers, mobile devices, and other electronic devices, with the focus on maximizing usability and the user experience. Essential for ensuring that digital products are intuitive and easy to use.

POLA

Principle of Least Astonishment (POLA) is a design guideline stating that interfaces should behave in a way that users expect to avoid confusion. Crucial for enhancing user experience and reducing the learning curve in digital products.

RWD

Responsive Web Design (RWD) is an approach to web design that makes web pages render well on a variety of devices and window or screen sizes. Essential for creating flexible, adaptive web experiences that maintain functionality and aesthetics across different platforms and devices.

Perceptual Set

The tendency to perceive and interpret information based on prior experiences and expectations, influencing how different users perceive design differently. Important for designing interfaces that meet user expectations, improving usability and intuitive navigation.

MVC

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.

Morphological Analysis

A problem-solving method that explores all possible solutions by examining the structure and relationships of different variables. Useful for generating innovative design solutions and exploring a wide range of possibilities in digital product development.

MBSE

Model-Based Systems Engineering (MBSE) is a methodology that uses visual modeling to support system requirements, design, analysis, and validation activities throughout the development lifecycle. Essential for managing complex systems, improving communication among stakeholders, and enhancing the overall quality and efficiency of systems engineering processes.

LLM

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.

Constancy

The perception of objects as unchanging despite changes in sensory input, such as changes in lighting, distance, or angle. Important for understanding user perception and designing stable visual experiences.

GIGO

Garbage In-Garbage Out (GIGO) is a principle stating that the quality of output is determined by the quality of the input, especially in computing and data processing. Crucial for ensuring accurate and reliable data inputs in design and decision-making processes.

Fault Tolerance

The capability of a system to continue operating properly in the event of the failure of some of its components, ensuring that user experience is not significantly affected by errors or issues, similar to Postel's Law. Essential for designing reliable and resilient systems, such as a form that normalizes user input for compatibility rather than returning an error (e.g., unconstrained phone number format).

Bucket Sort

A sorting algorithm that distributes elements into a number of buckets, sorts each bucket individually, and then combines the buckets to get the sorted list. Useful for understanding more advanced algorithmic techniques and their applications.

Bubble Sort

A simple sorting algorithm that repeatedly steps through the list, compares adjacent elements, and swaps them if they are in the wrong order. Important for understanding basic algorithmic principles and their applications.

Empirical Rule

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.

Outliers

Data points that differ significantly from other observations and may indicate variability in a measurement, experimental errors, or novelty. Crucial for identifying anomalies and ensuring the accuracy and reliability of data in digital product design.