Answer:
Incremental method.
Explanation:
Software development life cycle (SDLC) can be defined as a strategic process or methodology that defines the key steps or stages for creating and implementing high quality software applications.
An incremental model refers to the process in which the requirements or criteria of the software development is divided into many standalone modules until the program is completed.
Hence, an incremental method typically involves developing a system through repeated cycles and smaller portions at a time, enhancing and evolving the system over time.
In SDLC, a waterfall model can be defined as a process which involves sequentially breaking the software development into linear phases. Thus, the development phase takes a downward flow like a waterfall and as such each phase must be completed before starting another without any overlap in the process.
Also, a spiral model can be defined as an evolutionary SDLC that is risk-driven in nature and typically comprises of both an iterative and a waterfall model. Spiral model of SDLC consist of these phases; planning, risk analysis, engineering and evaluation.
A. Biofeedback
Its where your body is read by a machine and you read the machine
Answer:
Data redundancy.
Explanation:
A database management system (DBMS) can be defined as a collection of software applications that typically enables computer users to create, store, modify, retrieve and manage data or informations in a database. Generally, it allows computer users to efficiently retrieve and manage their data with an appropriate level of security.
A data dictionary can be defined as a centralized collection of information on a specific data such as attributes, names, fields and definitions that are being used in a computer database system.
In a data dictionary, data elements are combined into records, which are meaningful combinations of data elements that are included in data flows or retained in data stores.
Data redundancy is the name of situation where the same data is stored unnecessarily at different places.
Simply stated, data redundancy can be defined as a condition which typically involves storing the same data in multiple storage locations. Thus, data redundancy connotes the unnecessary repetition of the same piece of data (informations) either deliberately or for some specific reasons.
