Control coupling:Control coupling is one module controlling the flow of another, by passing it information on what to do (e.g., passing a what-to-do flag)
Data coupling:Data coupling is when modules share data through, for example, parameters. Each datum is an elementary piece, and these are the only data shared (e.g., passing an integer to a function that computes a square root)
control coupling content coupling common coupling data coupling external coupling message coupling
Coupling is a measure of the relationship or dependency between two modules. Data Coupling occurs between two modules when data is passed by parameters using a simple argument list and every item in the list is used.
Coupling is a measure of the relationship or dependency between two modules. Data Coupling occurs between two modules when data is passed by parameters using a simple argument list and every item in the list is used.
Yes we can differentiate the control character from frame delimiters, as there is need to distinguish between data being send and control information so frame delimiters arrange for sending side to change the data slightly before it is sent
Q: differentiate between group and ungroup data
Q: differentiate between group and ungroup data
In design concepts, coupling refers to the degree of interdependence between software modules or components. The main types of coupling are: tight coupling, where components are highly dependent on each other, making changes difficult; loose coupling, which allows components to interact with minimal dependencies, enhancing flexibility and maintainability; content coupling, where one module directly accesses the data of another; and control coupling, where one module controls the behavior of another through parameters. Favoring loose coupling is generally recommended for modular design, as it promotes scalability and easier updates.
Differentiate between Data Mining and Data Warehousing
Numeric data are data that can be quantify. i.e age, e.t.c While Non-numeric data are data that cannot be quantify but can be categorise. Such as colour, name e.t.c
Secondary data is collected by someone other than the researcher, such as census information. Primary data is collected first hand, such as interviews.
C is statically typed. There is no need for dollar or percentage symbols to differentiate between character/string data and numeric data.
You can use different colors or symbols to differentiate between the different plots.