Function point analysis (FPA) method decomposes the system into functional units. The total numbers of functional units are

Related MCQs

• Match the following A- Functional requirements: B- Functional scope : C- Function-point count: D- Function-related measures: 1- It describe the functionality or services that system is expected to provide. 2- Range to which a system component is capable of being applied. 3- These are language independent productive measure.. 4- It is related to the overall functionality of the delivered software.
• Match the following: A- Formal mathematical transformation: B- Formal process model: C-Formal Specifications: D-Formal System development: 1- Here the formal mathema- tical representation of the system takes place. 2- It is a starting point for process analysis. It is abstract and only defines the principal process activities and deliverables. 3-Specifications expressed in a language whose vocabulary, syntax and semantics are formally defined. 4-It is more common to waterfall model, but here the development process is based on formal mathematical transformation of a system specification to an exactable program.
• In function point analysis, number of Complexity adjustment factor is
• In system modeling : A-Model; B-Prototype;; 1- it’s an abstract view of a system that ignores system details; 2-It’s an initial version of system software which givers end-users a concrete impression of the system capacities
• Total numbers of maturing levels in CMM are
• In software system requirements, the functional requirement for the system describes
• Function-oriented design techniques starts with functional requirements specified in
• In system modeling: A-Architectural model: B-Stimulus-response model: C-Behavioral models: 1-Used to describe the overall behavior of the system: 2-State transition diagram show how the system reacts to internal and external events: 3-Shows principal sub-systems which makes the system
• For a function of n variables, boundary value analysis yields:
• For a function of n variables robustness testing of boundary value analysis yields: