Software testing is the act of checking whether software satisfies expectations.
An embedded system is a specialized computer system—a combination of a computer processor, computer memory, and input/output peripheral devices—that has a dedicated function within a larger mechanical or electronic system. It is embedded as part of a complete device often including electrical or electronic hardware and mechanical parts. Because an embedded system typically controls physical operations of the machine that it is embedded within, it often has real-time computing constraints. Embedded systems control many devices in common use. In 2009, it was estimated that ninety-eight percent of all microprocessors manufactured were used in embedded systems.
A recommender system (RecSys), or a recommendation system (sometimes replacing system with terms such as platform, engine, or algorithm), is a subclass of information filtering system that provides suggestions for items that are most pertinent to a particular user. Recommender systems are particularly useful when an individual needs to choose an item from a potentially overwhelming number of items that a service may offer.
The following outline is provided as an overview of and topical guide to human–computer interaction:
Human-centered computing (HCC) studies the design, development, and deployment of mixed-initiative human-computer systems. It is emerged from the convergence of multiple disciplines that are concerned both with understanding human beings and with the design of computational artifacts. Human-centered computing is closely related to human-computer interaction and information science. Human-centered computing is usually concerned with systems and practices of technology use while human-computer interaction is more focused on ergonomics and the usability of computing artifacts and information science is focused on practices surrounding the collection, manipulation, and use of information.
Ambient intelligence (AmI) refers to environments with electronic devices that are aware of and can recognize the presence of human beings and adapt accordingly. This concept encompasses various technologies in consumer electronics, telecommunications, and computing. Its primary purpose is to enhance user interactions through context-aware systems.
A system architecture is the conceptual model that defines the structure, behavior, and views of a system. An architecture description is a formal description and representation of a system, organized in a way that supports reasoning about the structures and behaviors of the system.
In user interface design, an interface metaphor is a set of user interface visuals, actions and procedures that exploit specific knowledge that users already have of other domains. The purpose of the interface metaphor is to give the user instantaneous knowledge about how to interact with the user interface. They are designed to be similar to physical entities but also have their own properties. They can be based on an activity, an object (skeuomorph), or a combination of both and work with users' familiar knowledge to help them understand 'the unfamiliar', and placed in the terms so the user may better understand.
Affective design describes the design of products, services, and user interfaces that aim to evoke intended emotional responses from consumers, ultimately improving customer satisfaction. It is often regarded within the domain of technology interaction and computing, in which emotional information is communicated to the computer from the user in a natural and comfortable way. The computer processes the emotional information and adapts or responds to try to improve the interaction in some way. The notion of affective design emerged from the field of human–computer interaction (HCI), specifically from the developing area of affective computing. Affective design serves an important role in user experience (UX) as it contributes to the improvement of the user's personal condition in relation to the computing system. Decision-making, brand loyalty, and consumer connections have all been associated with the integration of affective design. The goals of affective design focus on providing users with an optimal, proactive experience. Amongst overlap with several fields, applications of affective design include ambient intelligence, human–robot interaction, and video games.
In software engineering, graphical user interface testing is the process of testing a product's graphical user interface (GUI) to ensure it meets its specifications. This is normally done through the use of a variety of test cases.
Adaptive hypermedia (AH) uses hypermedia which is adaptive according to a user model. In contrast to regular hypermedia, where all users are offered the same set of hyperlinks, adaptive hypermedia (AH) tailors what the user is offered based on a model of the user's goals, preferences and knowledge, thus providing links or content most appropriate to the current user.
User modeling is the subdivision of human–computer interaction which describes the process of building up and modifying a conceptual understanding of the user. The main goal of user modeling is customization and adaptation of systems to the user's specific needs. The system needs to "say the 'right' thing at the 'right' time in the 'right' way". To do so it needs an internal representation of the user. Another common purpose is modeling specific kinds of users, including modeling of their skills and declarative knowledge, for use in automatic software-tests. User-models can thus serve as a cheaper alternative to user testing but should not replace user testing.
In science, computing, and engineering, a black box is a system which can be viewed in terms of its inputs and outputs, without any knowledge of its internal workings. Its implementation is "opaque" (black). The term can be used to refer to many inner workings, such as those of a transistor, an engine, an algorithm, the human brain, or an institution or government.
Responsibility-driven design is a design technique in object-oriented programming, which improves encapsulation by using the client–server model. It focuses on the contract by considering the actions that the object is responsible for and the information that the object shares. It was proposed by Rebecca Wirfs-Brock and Brian Wilkerson.
CL-HTTP is a web server, client and proxy written in Common Lisp. It is based on its own web application framework. It was written by John C. Mallery "in about 10 days" starting in 1994 on a Symbolics Lisp Machine. In the same year a port to Macintosh Common Lisp was done. In 1996 CL-HTTP became the first web server to support the HTTP 1.1 protocol. It runs on Unix, Linux, BSD variants, Mac OS X, Solaris, Symbolics Genera and Microsoft Windows.
The Center for Neurotechnology (CNT) is an Engineering Research Center funded by the National Science Foundation, develops devices to restore the body's capabilities for sensation and movement. The center is based at the University of Washington. Its core partner organizations are the Massachusetts Institute of Technology and San Diego State University.
Peter Brusilovsky is a professor of information science and intelligent systems at the University of Pittsburgh. He is known as one of the pioneers of adaptive hypermedia, adaptive web design, and web-based adaptive learning. He has published numerous articles in user modeling, personalization, educational technology, intelligent tutoring systems, and information access. As of February 2015 Brusilovsky was ranked as #1 in the world in the area of computer education and #21 in the world in the area of World Wide Web by Microsoft Academic Search. According to Google Scholar as of April 2018, he has over 33,000 citations and h-index of 77. Brusilovsky's group has been awarded best paper awards at Adaptive Hypermedia, User Modeling, Hypertext, IUI, ICALT, and EC-TEL conference series, including five James Chen Best Student paper awards.
Social navigation is a form of social computing introduced by Paul Dourish and Matthew Chalmers in 1994, who defined it as when "movement from one item to another is provoked as an artifact of the activity of another or a group of others". According to later research in 2002, "social navigation exploits the knowledge and experience of peer users of information resources" to guide users in the information space, and that it is becoming more difficult to navigate and search efficiently with all the digital information available from the World Wide Web and other sources. Studying others' navigational trails and understanding their behavior can help improve one's own search strategy by guiding them to make more informed decisions based on the actions of others.
Explainable AI (XAI), often overlapping with interpretable AI, or explainable machine learning (XML), is a field of research within artificial intelligence (AI) that explores methods that provide humans with the ability of intellectual oversight over AI algorithms. The main focus is on the reasoning behind the decisions or predictions made by the AI algorithms, to make them more understandable and transparent. This addresses users' requirement to assess safety and scrutinize the automated decision making in applications. XAI counters the "black box" tendency of machine learning, where even the AI's designers cannot explain why it arrived at a specific decision.
The International Conference on User Modeling, Adaptation, and Personalization (UMAP) is the oldest international conference for researchers and practitioners working on various kinds of user-adaptive computer systems such as Adaptive hypermedia systems, Recommender systems, Adaptive websites, Adaptive learning, Personalized learning and Intelligent tutoring systems and Personalized search systems. All of these systems adapt to their individual users, or to groups of users. To achieve this goal, they collect and represent information about users or groups.
