Scientific Method How related to Computer Science? Modeling Theoretical Computer Science Experimental Computer Science Computer Simulation

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By :
Parinda Rajapaksha
Samudra Herath
Isuri Udayangi
Najini Harischandra

2. Roadmap
 Introduction
 Scientific Method
 How related to Computer Science?
 Modeling
 Theoretical Computer Science
 Experimental Computer Science
 Computer Simulation
 Pros & Cons
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3. What is Science ?
 A systematic and logical approach to discovering how
things in the universe work.
 It aims for measurable results through testing and analysis.
 It is not meant to prove theories, but rule out alternative
explanations until a likely conclusion is reached
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4. What is Science Cont…
 Science consists simply of the formulation and testing of
hypotheses based on observational evidence.
 Science is useful and ongoing.
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5. How related to Computer Science?
 Study of phenomena related to computers.
 Computing encompasses,
- Computer Science
- Computer Engineering
- Software Engineering
- Information Systems
 The purpose of Computing is the systematic study of
algorithmic processes that describe and transform
information their theory, analysis, design, efficiency and
implementation
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6. Scientific Method
 In 19th century.
 scientific method is the logical scheme used by scientists
searching for answers to the questions
 It is used to produce scientific theories..
 When conducting a research, scientists observe the scientific
method to collect measurable, empirical evidence in an
experiment related to a hypothesis.
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7. Scientific Method Cont…
The steps of the scientific method :
1. Pose the question in the context of existing knowledge
(theory & observations)
2. Formulate a hypothesis as a tentative answer
3. Deduce consequences and make predictions
4. Test the hypothesis in a specific experiment/theory field
•In case the hypothesis leads to contradictions and demands a
radical change in the existing theoretical background, it has to be
tested carefully
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8. Scientific Method Cont…
Rule:
• loop 2-3-4 is repeated with modifications of the hypothesis until
the agreement is obtained, which leads to 5.
• If major discrepancies are found the process must start from the
beginning, 1.
5. When consistency is obtained the hypothesis becomes a
theory and provides a coherent set of propositions that
define a new class of phenomena or a new theoretical
concept
6. A theory is then becoming a framework within which
observations/theoretical facts are explained and predictions
are made
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9. Scientific Method Cont…
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10. Scientific Method Cont…
Some key underpinnings to the scientific method:
 The hypothesis must be testable and falsifiable
 Deductive reasoning is the process of using true
premises to reach a logical true conclusion
 dependent variable and an independent variable
 experimental group and a control group.
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11. What is Computer Science?
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12. Many definitions
 Study of algorithmic processes that describe and transform
information
 Study of phenomena related to computers
 Study of information structures
 Study and management of complexity
 Mechanization of abstraction
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13. Mixture of
 Engineering
 Mathematics
 Logic
 Management
Generally CS is,
Information theory concerned on transformation and
interpretation of information
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14.  Computer science encompasses abstract mathematical
thinking and includes an element of engineering.
 Finding solutions
 Designing skills
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15. Sub-areas of Computer Science
1. Discrete Structures
2. Programming Fundamentals
3. Algorithms and Complexity
4. Programming Languages
5. Architecture and Organization
6. Operating Systems & etc..
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16. List expands as computer science
develops..
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17.  CS Objectives change with time
 Development of theories
 Practical experience in usage
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18. Scientific methods of computer science
Computer Science
Theoretical Experimental Simulation
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19. Common Method
Modeling
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20. Modeling
 Occur in Science
 Simplify a phenomenon
 Identify what is relevant
 Theoretical background
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21. Simplified model of a phenomenon
Description in
symbolic language
Observable/measurable
consequence of a given
change in a system
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22. Question that come in the process
 How to model?
 Is the model appropriate?
 In what way model differs from “reality”?
 Validation: are the results valid?
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23. Examples
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24.  Modeling process scheme follows the general scheme of
scientific method presented before
 Theory, experiment and simulation are all about models
of phenomena.
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25. What is theoretical computer
Science?
 Subset of general computer science and mathematics
 focus on more abstract or mathematical aspects of computing
 Includes the theory of computation
 Follows a very classical methodology of building theories with
rigid definitions of
 Objects
 operations
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26. Key recurring ideas of computing
 Conceptual and formal models
 Different levels of abstraction
 Efficiency
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27. Data models
 Use to formulate different mathematical concepts
 CS data model – two aspects
 Values they can assume
 Operations on data
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28. Typical data model examples
 Tree data model
 List data model
 Set data model
 Relational data model
 Graph data model
 Patterns, automata and regular expression
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29. Physical science and computer
science
 Do not compete with each other on which better explains
the fundamental nature of information
 No new theories develop to reconcile theory with
experimental results reveal unexpected phenomena
 No history of critical experiments that decide the validity
of various theories
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30. Design and analysis
 Methods are developed for algorithm design
 Measures are defined for computational resources
 Trade offs are explored
 Upper and lower resource bounds are proved
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31. Main methodological themes
 Iteration – performing sequence of operations repeatedly
 Iterative constructs such as for /while statements
 Recursion – call themselves directly or indirectly
 Induction – definitions and proofs use basis and inductive
step to encompass all possible cases.
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32. Experimental Computer Science
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33. What is experimental computer
science?
 Three components define experimental science
 Observation
 Hypothesis testing
 Reproducibility
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34.  Experimental computer science
 Mathematical modeling of the behavior of computer
systems
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35. Fields of computer science use
experiments
 Search
 Automatic theorem proving
 Planning
 NP complete problems
 Natural language
 Vision
 Games
 Machine learning
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36. Computer Simulation
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37.  computation which comprises computer - based modeling and
simulation, has become the third research methodology within
CS
 Computational Science has emerged, at the intersection of
Computer Science, applied mathematics, and science disciplines
in both theoretical investigation and experimentation
Computational Science
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38. Computational Science Cont…
Tools
 modeling with 3D visualization and computer simulation
 efficient handling of large data sets
 ability to access a variety of distributed resources
 collaborate with other experts over the Internet
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39. Computational Science Cont…
 Computational science involves the use of computers
(''supercomputers'') for visualization and simulation of
complex and large-scale phenomena.
 If Computer Science has its basis in computability theory,
then computational science has its basis in computer
simulation
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40. Computer Simulation
 Definition
simulation: (computer science) the
technique of representing the real world
by a computer program; "a simulation
should imitate the internal processes
and not merely the results of the thing
being simulated“
 Computer simulation makes it possible
to
 investigate regimes that are beyond
current experimental capabilities
 study phenomena that cannot be
replicated in laboratories, such as the
evolution of the universe and Nano
technology
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41. Simulations
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42. Key Areas
 Chaos and Complex Systems
 Virtual Reality
 Artificial Life
 Physically Based Modeling and Computer
Animation
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43. Advantages and Disadvantages
 Advantage
 You can test in many different ways, and the more times
you test, the more accurate your results will be
 Disadvantage
 You can come up with different results which can disprove
your hypothesis, and this leads to inconsistent conclusions
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44. Wrap-Up
 Introduction
 Scientific Method
 How related to Computer Science?
 Modeling
 Theoretical Computer Science
 Experimental Computer Science
 Computer Simulation
 Pros & Cons
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45. References
1. Some definitions of Science :
http://www.gly.uga.edu/railsback/1122sciencedefns.html
2. Computing as a Discipline, Denning, P.J. et al. Commun. ACM
32, 1 (January 1989), 9
3. What is computer science ? :
http://www.cs.mtu.edu/~john/whatiscs.html
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