<span>A switch is a central network device that connects network nodes such as workstations and servers in a physical Star topology</span>
Answer:
If you want to learn coding than get a game and look at the code inside.
Explanation:
I sugest terraria
Answer: D) Identifying GUI's for a particular requirement
Explanation:
Traceability of requirements is helpful except identifying GUI's for a particular requirements as, traceability in project management describe the relationships between two or more element throughout in the development process and outline the relationship between the customer requirement by traceability matrix. And the requirement of traceability is so important because it creating a downstream flow of software and test cases in software requirement but not helpful in GUI identification.
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.
Data visualization
Data visualization is a good starting point for data mining. There are several approaches to data mining that supports smart decisions. Data visualization places data in a visual context. It extracts the data in a clear and understandable way without any form of reading or writing. Results are displayed in the form of pie charts, graphs, and any other statistical representation. Such multidimensional views of data aid in developing a preliminary understanding of the trends that are hidden in the data set.
