Software can be …

• complex
• "has many parts"
• complicated
• "has a high level of difficulty"
• Need design approaches to deal with complexity and complicated code

Decomposition

Breaking a complex problem or system into a collection of smaller parts

• Start with the initial problem or system and apply decomposition recursively
• With good design, the smaller parts improve modularity which improves maintainability and reusability
• Design answers the question: What parts do I need to solve this problem, and how do these parts relate to each other?
• Possible tradeoffs: efficiency

Decomposition Advantages

When performed correctly, the smaller parts are easier to:

• Design
• Implement
• Comprehend
• Test
• Maintain
• Reuse

Algorithmic Decomposition

Breaking a complex algorithm into a collection of smaller algorithms

• Start with the initial algorithm and apply algorithm decomposition recursively
• With good design, the smaller algorithms improve modularity which improves maintainability and reusability
• Design answers the question: What algorithms do I need to solve this problem, and how do these algorithms relate to each other?
• Possible tradeoffs: efficiency

Rainfall: Algorithmic Decomposition

1. Input rainfall data
2. Calculate maximum rainfall
3. Calculate average rainfall
4. Output the rainfall report

Modeling Decomposed Structure

• Data-Flow Diagram (DFD)
• Shows data exchanged between elements
• Hierarchy Chart or Organization Chart
• Shows levels of elements
• Structure Chart
• Shows levels of elements and the data exchanged between the elements

Structure Chart

Rainfall: Structure Chart

Function Decomposition

Breaking a function down into a collection of smaller functions

• Start with the main() function and apply function decomposition recursively
• With good design, the smaller functions improve modularity which improves maintainability and reusability
• Design answers the question: What functions do I need to solve this problem, and how do these functions relate to each other?
• Possible tradeoffs: efficiency

What Functions Care About and Algorithms Don't

• Input source and format
• Where did the array data come from?
• Output source and format
• Where is the data going?
• Exact syntax used
• What language features do we use?
• Interface
• What name, parameters, and return type do the functions have?
• Options and exceptional cases

Structure Chart

Rainfall: Structure Chart

Information Hiding

Hide the internal details of a part, algorithm, or function, and only expose the minimal interface

• details can be specific values, complex operations, complex series of operations, knowledge, etc.
• interface includes what we pass and the direction, i.e., IN, OUT, and IN/OUT
• This is what gives decomposition its advantages

Relation to functions

• Functions created by algorithmic decomposition work only on the data in the parameters given (IN, OUT, and IN/OUT)
• These functions are operations, actions, etc., on some data

Interface and Functions

• Name
• Parameters
• Return Type

Direction and C++ Parameter Types

C++ Parameter Types and Direction

functions and State

• In general, free functions do not save state between calls; they do not have any internal "memory" between calls
• Parameters and local variables are created when the function is called and destroyed when the function call returns
• Mostly exhibit consistent behavior, i.e., if passed same data, produces the same result
• There are ways around this but use object-oriented approaches instead

Approaches to Decomposition

• Top-Down Design
• Start with the root of the tree and work down decomposing at each level
• Bottom-Up Design
• Start with the leaves of the tree and combine them level-by-level
• Experts use a combination of the two and often switch during the design process

Top-Down Design

• 1) { Generate Payroll }
• 2) { Get Payroll Record, Calculate Net Pay, Print Check }
• 3) { { Read Payroll Record, Validate Payroll Record }, { Calculate Gross Pay, Calculate Deductions, Update Employee Record } }
• 4) { Calculate Tax Withholding, Calculate Social Security Withholding }

Bottom-Up Design

• 1) { Calculate Tax Withholding, Calculate Social Security Withholding }
• 2) { { Read Payroll Record, Validate Payroll Record }, { Calculate Gross Pay, Calculate Deductions, Update Employee Record } }
• 3) { Get Payroll Record, Calculate Net Pay, Print Check }
• 4) { Generate Payroll }

Algorithmic Decomposition and OOP/OOD

• A lower-level approach is needed for OOP/OOD
• Algorithmic decomposition only scales so far
• The primary challenge of modern applications is not algorithmic complexity but the sheer number of things to keep track of
• Core algorithms for a particular problem often do not change over time, but surrounding code does, e.g., input formats, output formats