Complexity Theory
The study of complex systems and how interactions within these systems give rise to collective behaviors. Useful for understanding and managing the complexity in design processes and systems.
The study of complex systems and how interactions within these systems give rise to collective behaviors. Useful for understanding and managing the complexity in design processes and systems.
An interdisciplinary study of systems, examining the complex interactions and relationships between components within a whole. Crucial for understanding and designing complex, interconnected systems.
A holistic approach to analysis that focuses on the way that a system's constituent parts interrelate and how systems work over time and within the context of larger systems. Essential for solving complex problems and designing systems that account for interdependencies and dynamics.
The study of dynamic systems that are highly sensitive to initial conditions, leading to unpredictable behavior. Important for recognizing and managing unpredictable elements in design and development processes.
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.
A risk management model that illustrates how multiple layers of defense (like slices of Swiss cheese) can prevent failures, despite each layer having its own weaknesses. Crucial for understanding and mitigating risks in complex systems.
The process of integrating knowledge into computer systems to solve complex problems, often used in AI development. Important for developing intelligent systems that can perform complex tasks and support decision-making in digital products.
The principle stating that there is a limit to the amount of complexity that users can handle, and if designers don't manage complexity, users will. Crucial for designing user-friendly systems that manage complexity effectively.
An inference method used in AI and expert systems where reasoning starts from the goal and works backward to determine the necessary conditions. Important for developing intelligent systems that can solve complex problems by working from desired outcomes.
Site Reliability Engineering (SRE) is a discipline that incorporates aspects of software engineering and applies them to infrastructure and operations problems to create scalable and highly reliable software systems. Crucial for maintaining the reliability and efficiency of complex software systems.
Numeronym for the word "Observability" (O + 11 letters + N), the ability to observe the internal states of a system based on its external outputs, facilitating troubleshooting and performance optimization. Crucial for monitoring and understanding system performance and behavior.
The process of combining different systems or components in a way that ensures they work together smoothly and efficiently without disruptions. Essential for providing a cohesive user experience and ensuring the reliability of complex systems.
An inference method used in AI and expert systems where reasoning starts from known facts and applies rules to derive new facts. Important for developing intelligent systems that can build knowledge and solve problems incrementally in digital products.
Software that acts as an intermediary between different systems or applications, enabling them to communicate and function together. Crucial for integrating various components and ensuring seamless interaction within digital products.
A principle stating that a system should be liberal in what it accepts and conservative in what it sends, meaning it should handle user input flexibly while providing clear, consistent output, similar to the principle of fault tolerance. Essential for designing robust and user-friendly interfaces that accommodate a wide range of user inputs and behaviors while maintaining reliability and clarity in responses.
A cognitive bias where people underestimate the complexity and challenges involved in scaling systems, processes, or businesses. Important for understanding the difficulties of scaling and designing systems that address these challenges.
Domain-Driven Design (DDD) is an approach to software development that focuses on modeling the business domain and its logic. Essential for aligning software development with business needs and creating maintainable systems.
A design principle that ensures a system continues to function at a reduced level rather than completely failing when some part of it goes wrong. Crucial for enhancing system reliability and user experience in adverse conditions.
Redundant, outdated, or unnecessary code or design elements that accumulate over time in a system. Important for identifying and removing to maintain clean, efficient, and maintainable systems and interfaces.
Numeronym for the word "Documentation" (D + 11 letters + N), creating detailed records and instructions to support the development, use, and maintenance of systems or products. Crucial for ensuring users and developers understand and properly use the system or product.
AI systems that can dynamically adjust their behavior based on new data or changes in the environment. Important for developing systems that can respond to real-time changes and improve over time.
The study of the relationships between people, practices, values, and technologies within an information environment. Helps in understanding and designing systems that are sustainable and adaptive to human and environmental changes.
Numeronym for the word "Interoperability" (I + 14 letters + Y), the ability of different systems, devices, or applications to work together and exchange information effectively without compatibility issues. Crucial for ensuring compatibility and integration between systems.
Operations and processes that occur on a server rather than on the user's computer. Important for handling data processing, storage, and complex computations efficiently.
A stimulus that gains reinforcing properties through association with a primary reinforcer, such as money or tokens, which are associated with basic needs. Essential for understanding complex behavior reinforcement strategies and designing effective reward systems.
A team structure within an organization focused on managing and integrating complex subsystems. Important for ensuring seamless integration and functionality of complex projects.
A mode of thinking, derived from Dual Process Theory, that is slow, deliberate, and analytical, requiring more cognitive effort and conscious reasoning. Crucial for designing complex tasks and interfaces that require thoughtful decision-making and problem-solving, ensuring they are clear and logical for users.
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.
A high-level description of a system's structure and interactions, focusing on its market-facing aspects rather than technical details. Useful for communicating the value and structure of a digital product to non-technical stakeholders and aligning with market needs.
The degree to which a system's components may be separated and recombined, often used in the context of software or hardware design. Important for enhancing flexibility, reusability, and ease of maintenance in design.
Enterprise Resource Planning (ERP) are integrated software systems that manage business processes across various departments, such as finance, HR, and supply chain. Essential for improving operational efficiency and providing a unified view of business operations.
A methodology for creating design systems by breaking down interfaces into their basic components (atoms, molecules, organisms, templates, and pages). Essential for creating scalable and maintainable design systems.
Simple Knowledge Organization System (SKOS) is a standard for representing knowledge organization systems such as thesauri, classification schemes, and taxonomies. Essential for enabling interoperability and sharing of structured knowledge across different systems.
A key aspect of Gestalt psychology where complex patterns arise out of relatively simple interactions. Crucial for understanding how users perceive complex designs and patterns.
Human in the Loop (HITL) integrates human judgment into the decision-making process of AI systems. Crucial for ensuring AI reliability and alignment with human values.
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 process of handling changes to software, hardware, or documentation in a systematic way. Critical for maintaining consistency and ensuring system integrity.
A system of design variables used to maintain consistency in a design system, such as colors, fonts, and spacing. Crucial for ensuring uniformity and scalability in design across different platforms and products.
A principle stating that as the flexibility of a system increases, its usability often decreases, and vice versa. Crucial for balancing versatility and ease of use in design.
A type of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. Crucial for developing intelligent systems that can make data-driven decisions.
The structural design of a product, defining its components, their relationships, and how they interact to fulfill the product's purpose. Important for ensuring that a product is well-organized, scalable, and maintainable.
Application Programming Interface (API) is a set of tools and protocols that allow different software applications to communicate and interact with each other. Essential for integrating different systems and enabling functionality in digital products.
Case-Based Reasoning (CBR) is an AI method that solves new problems based on the solutions of similar past problems. This approach is essential for developing intelligent systems that learn from past experiences to improve problem-solving capabilities.
A strategy where a team plays the role of an adversary to identify vulnerabilities and improve the security and robustness of a system. Crucial for testing the resilience of digital products and identifying areas for improvement.
The practice and science of classification, often used to organize content and information. Essential for improving findability and usability in information systems.
A professional who designs, builds, and maintains systems for processing large-scale data sets. Essential for enabling data-driven decision-making and supporting advanced analytics in organizations.
The Principle of Choices is an information architecture guideline that emphasizes providing users with meaningful options to navigate and interact with a system. Crucial for enhancing user experience by ensuring users can easily find what they need without being overwhelmed.
The process of anticipating, detecting, and resolving errors in software or systems to ensure smooth operation. Important for creating reliable and user-friendly software applications.
A principle stating that productivity increases when the computer and its user interact at a pace that ensures neither has to wait on the other. Important for designing responsive systems that enhance user productivity.
The visual images, symbols, or modes of representation collectively associated with a subject, often used in design to communicate ideas quickly and effectively. Important for creating cohesive and meaningful visual systems.
A set of algorithms, modeled loosely after the human brain, designed to recognize patterns and perform complex tasks. Essential for developing advanced AI applications in various fields.
A statistical technique that uses random sampling and statistical modeling to estimate mathematical functions and simulate systems. Useful for risk assessment, decision-making, and performance optimization in digital product design.
A decision-making strategy where individuals allocate resources proportionally to the probability of an outcome occurring, rather than optimizing the most likely outcome. Important for understanding decision-making behaviors and designing systems that guide better resource allocation.
A search system that allows users to narrow down search results by applying multiple filters based on different attributes or categories. Essential for improving user search experience and efficiency.
The mathematical study of waiting lines or queues. Useful for optimizing user flow and reducing wait times in user interfaces.
The high-level structure of a software application, defining its components and their interactions. Essential for designing robust, scalable, and maintainable digital products.
A set of standards and guidelines used to ensure the integrity, security, and compliance of business processes and IT systems. Important for establishing robust governance and control mechanisms in digital product design and development.
A comprehensive list of all content within a system, used to manage and optimize content. Essential for organizing, auditing, and improving content strategy.
The dynamic system of content creation, distribution, and interaction within an environment. Important for understanding how content flows and interacts within a system.
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.