This document discusses software design complexity, including its types (essential, incidental, accidental), ways to measure it, and factors that contribute to it such as system size and scope, number of components, levels of abstraction, concurrency needs, and non-functional requirements. Understanding software design complexity is important because it affects time, cost, and quality. Techniques for managing complexity include modularization, design patterns, formal methods, visualization tools, agile development, and automated testing.

1. Complexity
Software Design
Guide towards Software Design

2. Introduction
Contents
01
Types
02
Techniques
03
Examples
04

3. What is
Software Design
Complexity??

4. Software Design
Complexity
Software design complexity refers to the inherent difficulty of designing software
systems due to factors such as size, scope of the system, number of components,
level of abstraction required for different components, degree of concurrency and
synchronization needed, level of uncertainty and variability in system
requirements and environment, and presence of non-functional requirements such
as performance or security (Freeman).

5. Types of
COMPLEXITY

6. A
Essential
Complexity
B
Incidental
Complexity
C
Accidental
Complexity

7. A
Every system will have a certain degree
of complexity. There's nothing that can
be done to reduce this, which is okay as
long as the complexity is recognized and
appreciated
Essential
Complexity

8. B
Sometimes external factors will be lead
to extra complexity, such as hardware
or software limitations.
Incidental
Complexity

9. C
This is the type of complexity you
want to watch out for it. It can be
avoided with planning and precision.
Accidental
Complexity Accidental complexity this is the
biggest issue when creating code is.
Whenever possible, developers
should be able to pinpoint and deal
with this form when it appears.

10. Different ways
on measuring
Software Design
COMPLEXITY

11. Cyclomatic Complexity
Halstead Complexity
Maintainability Complexity
Object-Oriented Design Matrix
Chapin metric (Data Complexity)
Cognitive Complexity
Rework Ratio

12. Factors
Contributing to
Software Design
Complexity

13. FACTORS:
Size and Scope of the System
Number of Components and Interaction
between them
Level of abstraction required for different
components and modules
Degree of concurrency and synchronization
needed in system design
Level of uncertainty and variability in
system requirements and environment
Presence of non-functional requirements such as
performance, reliability, and security

14. A
Size and Scope
of the System
The larger the system, the more
complex it becomes due to the
increased number of components,
interaction between them,
and the need for more extensive
documentation and testing (Freeman).

15. B
Number of
Components and
Interaction
between them
The more components a system has,
the more complex it becomes due to
the increased number of
interfaces and interactions
between them (Freeman).

16. C
Level of abstraction
required for different
components and
modules
Different components and modules of
a system may require different
levels of abstraction, which can
result in complexity due to the need
to manage multiple levels of
abstraction simultaneously (Freeman).

17. D
Degree of concurrency
and synchronization
needed in system
design
Concurrent systems with multiple
threads of execution can be more
complex due to the need to
manage synchronization and avoid race
conditions (Freeman).

18. E
Level of uncertainty
and variability in
system requirements
and environment
Systems with high levels of uncertainty
and variability in requirements and
environment can be more complex due to
the need to design for flexibility and
adaptability (Freeman).

19. F
Presence of
non-functional
requirements such as
performance, reliability,
and security
Non-functional requirements such as
performance, reliability, and security
can add complexity to system design
due to the need to optimize system
performance, ensure system reliability, and
provide adequate security measures
(Freeman).

20. Why is it
Important to
UNDERSTAND?

21. Importance of
Understanding
Software design complexity is crucial for software designers and developers
because it affects various aspects of software development such as time, cost,
and quality of the software system. Understanding software design complexity
helps designers to make informed decisions about system architecture,
component design, and testing strategies, which can result in more efficient,
reliable, and maintainable software systems (Hamilton).

22. Techniques for Managing
Software Design Complexity

23. Modularization and decomposition of a system into
smaller, more manageable components

24. Use of design patterns to reuse
proven solutions for common
problems

25. Application of formal methods such as
mathematical modeling or theorem proving
to ensure correctness

26. Use of visualization tools to aid in understanding
complex system architectures
Employment of agile development methodologies to
enable rapid prototyping and iterative refinement of
designs
Incorporation of automated testing and verification
techniques to ensure system reliability and
maintainability

27. Case Studies & Examples

28. A
B
C
Discussion of real-world
systems with high design
complexity, such as air
traffic control systems
or financial trading
platforms
Analysis of successful
design approaches used
in these systems
Examination of common
design challenges and
pitfalls encountered in
such systems

29. Benefits of Understanding
Software Design Complexity

30. Better code quality
Improve Maintainability
Reduced Bugs
Faster Development
Improve Collaboration
Better Code Documentation

31. Thank you
Software Design