Canary Testing
A deployment strategy where a new version is released to a small subset of users to detect any issues before a full rollout. Crucial for minimizing risk and ensuring the stability of digital products during updates and deployments.
135 topics found for:
“reliability”
Extension Neglect
A cognitive bias where people ignore the relevance of sample size in making judgments, often leading to erroneous conclusions. Crucial for designers to account for appropriate sample sizes in research and analysis.
Structured Programming
A programming paradigm aimed at improving the clarity, quality, and development time of software by using structured control flow constructs. Essential for writing clear, maintainable, and efficient code in digital product development.
Build Server
A server dedicated to automating the process of building and compiling code, running tests, and generating software artifacts. Crucial for ensuring continuous integration and maintaining the integrity of the codebase in digital product development.
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.
Standard Deviation
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.
Black Box Testing
A testing method where the internal structure of the system is not known to the tester, focusing solely on input and output. Essential for validating the functionality of digital products from an end-user perspective.
Berkson’s Paradox
A statistical phenomenon where two independent events appear to be correlated due to a selection bias. Important for accurately interpreting data and avoiding misleading conclusions.
Base Rate Fallacy
A cognitive bias where people ignore general statistical information in favor of specific information. Critical for designers to use general statistical information to improve decision-making accuracy and avoid bias.
Mura
A Japanese word meaning inconsistency or variability in processes. Helps in recognizing and addressing workflow imbalances to improve efficiency.
Courtesy Bias
The tendency for individuals to give positive responses or feedback out of politeness, regardless of their true feelings. Crucial for obtaining honest and accurate user feedback.
Server-Side
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.
White Box Testing
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.
Release Management
The process of overseeing and coordinating the development, testing, and deployment of software releases to ensure they are delivered efficiently and effectively. Essential for managing software development cycles and ensuring successful product releases.
Hotfix
A quick and often temporary fix applied to a software product to address an urgent issue without going through the full development cycle. Essential for maintaining the stability and functionality of digital products in the face of critical issues.
Release
The distribution of a new or updated software product to users. Important for delivering new features, improvements, and fixes to users, ensuring continuous enhancement of the product.
Hofstadter’s Law
A principle that states tasks always take longer than expected, even when considering Hofstadter's Law itself. Important for setting realistic project timelines and managing expectations in digital product development.
Clustering Illusion
A cognitive bias where people see patterns in random data. Important for designers to improve data interpretation and avoid false conclusions based on perceived random patterns.
TDD
Test-Driven Development (TDD) is a software development methodology where tests are written before the code that needs to pass them. Essential for ensuring high code quality and reducing bugs.
Hidden Costs
A dark pattern where additional costs are only revealed at the last step of the checkout process. It's essential to avoid this tactic and promote transparent pricing to build user trust.
Quantitative Research
A research method that focuses on collecting and analyzing numerical data to identify patterns, relationships, and trends, often using surveys or experiments. Essential for making data-driven decisions and validating hypotheses with statistical evidence.
Fallacy of Composition
A logical fallacy that occurs when one assumes that what is true for a part is also true for the whole. Important for avoiding incorrect assumptions in design and decision-making.
Campbell’s Law
The principle that the more a metric is used to make decisions, the more it will be subject to corruption and distort the processes it is intended to monitor. Important for understanding the limitations and potential distortions of metrics in design and evaluation.
Promptframe
A structure or framework used to create effective prompts for AI systems, ensuring clarity and context. Important for standardizing and improving AI prompt design.
Business Viability
The potential for a project or solution to be economically sustainable and profitable. Important for ensuring that design and development efforts align with business goals and market demands.
Suffix Effect
The phenomenon where people have a reduced ability to recall the last items in a list when additional, unrelated information is added at the end. Crucial for designing information presentation to optimize memory retention.
Business Logic
The part of an application that encodes the real-world business rules that determine how data is created, stored, and modified. Crucial for ensuring that digital products align with business processes and deliver value to users.
Prompt Engineering
The process of designing and refining prompts to elicit accurate and relevant responses from AI models. Crucial for optimizing the performance of AI applications.
Expectation Bias
A cognitive bias where individuals' expectations influence their perceptions and judgments. Relevant for understanding how expectations skew perceptions and decisions among users.
Subadditivity Effect
A cognitive bias where the total probability assigned to a set of events is less than the sum of the probabilities assigned to each event individually. Important for understanding how users estimate probabilities and make decisions under uncertainty.
Error Prevention
Design strategies aimed at preventing user errors before they occur. Crucial for enhancing usability and ensuring a smooth user experience.
Progressive Enhancement
A design approach that focuses on building a robust core experience first, then adding more advanced features and capabilities for users with more capable browsers or devices. Essential for ensuring a consistent and accessible user experience across different devices and browsers.
Static Testing
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.
BPA
Business Process Automation (BPA) refers to the use of technology to automate complex business processes. Essential for streamlining operations, reducing manual effort, and increasing efficiency in recurring tasks.
POUR
Perceivable, Operable, Understandable, and Robust (POUR) are the four main principles of web accessibility. These principles are essential for creating inclusive digital experiences that can be accessed and used by people with a wide range of abilities and disabilities.
DevOps
A set of practices that combines software development (Dev) and IT operations (Ops) to shorten the development lifecycle and deliver high-quality software continuously. Crucial for improving the speed, efficiency, and quality of software development and deployment.
Staging Environment
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.
Biometric Inputs
The use of biological data (e.g., fingerprints, facial recognition) for user authentication and interaction with digital systems. Crucial for enhancing security and user experience through advanced authentication methods.
Dev Environment
A development environment where software is created and modified. Crucial for allowing developers to build and experiment with new features.
Platform Team
A team responsible for developing and maintaining the foundational systems and services that support other teams and products. Crucial for ensuring scalability and efficiency across the organization.
Design Canon
A set of fundamental principles and guidelines that inform and shape design practices. Crucial for maintaining design consistency and ensuring high-quality outcomes.
SOAP
Simple Object Access Protoco (SOAPl) is a protocol for exchanging structured information in web services. Crucial for enabling communication between applications over a network.
AWS
Amazon Web Services (AWS) is a comprehensive cloud computing platform provided by Amazon that offers a wide range of services including computing power, storage, and databases. Crucial for enabling scalable, cost-effective, and flexible IT infrastructure solutions for businesses of all sizes.
Delphi Method
A structured communication technique originally developed as a systematic, interactive forecasting method which relies on a panel of experts. Important for gathering expert opinions and making informed decisions.
Smoke Testing
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.
Negative Prompt
In AI and machine learning, a prompt that specifies what should be avoided or excluded in the generated output, guiding the system to produce more accurate and relevant results. Crucial for refining AI-generated content by providing clear instructions on undesired elements, improving output quality and relevance.
Data Distribution
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.
Native
Content or functionality that is built into a platform or device rather than being provided by an external application. Important for ensuring seamless integration and optimal performance.
CSAT
CSAT (Customer Satisfaction) measures how products or services provided by a company meet or exceed customer expectations. Essential for understanding customer needs and improving product offerings.
Cruft
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.
MRR
Monthly Recurring Revenue (MRR) is a metric that quantifies the predictable revenue generated each month from customers. This metric is crucial for SaaS companies to track financial health and growth.
Cross Validation
A statistical method used to assess the generalizability of a model to unseen data, involving partitioning a dataset into subsets for training and validation. Essential for evaluating model performance and preventing overfitting in digital product analytics.
Monte Carlo Simulation
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.
Control Framework
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.
Alpha Test
A preliminary testing phase conducted by internal staff to identify bugs before releasing the product to external testers or customers. Crucial for ensuring product quality and functionality before broader release.
Continuous Reinforcement
A schedule of reinforcement where a desired behavior is reinforced every time it occurs, promoting quick learning and behavior maintenance. Important for designing systems that encourage consistent user behavior.
Scaling Fallacy
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.
12-Factor App
A methodology for building software-as-a-service apps that emphasizes best practices for development, deployment, and scalability. Important for creating scalable, maintainable, and efficient digital products.
RLHF
Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that uses human input to guide the training of AI models. Essential for improving the alignment and performance of AI systems in real-world applications.
Longitudinal Study
A research method that involves repeated observations of the same variables over a period of time. Crucial for understanding changes and developments over time.