TAILIEUCHUNG - Lecture Software engineering: Lecture 15 - Ivan Marsic

Lecture 15: Software complexity metrics. The topics discussed in this chapter are: Measuring software complexity, desirable properties of complexity metrics, cyclomatic complexity, converting code to graph, unit testing: path coverage,. | Ivan Marsic Rutgers University LECTURE 15: Software Complexity Metrics Topics Measuring Software Complexity Cyclomatic Complexity Measuring Software Complexity Software complexity is difficult to operationalize complexity so that it can be measured Computational complexity measure big O (or big Oh), O(n) Measures software complexity from the machine’s viewpoint in terms of how the size of the input data affects an algorithm’s usage of computational resources (usually running time or memory) Complexity measure in software engineering should measure complexity from the viewpoint of human developers Computer time is cheap; human time is expensive Desirable Properties of Complexity Metrics Monotonicity: adding responsibilities to a module cannot decrease its complexity If a responsibility is added to a module, the modified module will exhibit a complexity value that is the same as or higher than the complexity value of the original module Ordering (“representation condition” .

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