Software Design Patterns in Theory

Yann-Gaël Guéhéneuc

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Some Theory and Practice on Patterns – In Theory

NII, Tokyo, Japan12/02/14

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Did you know that…

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Vision is our dominant sense?

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How does vision work?

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Outline

Visual systemMemory modelsMental models Schema theory Software patterns Empirical studies Conclusion

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Outline


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Visual System

Vision Science: Photons to Phenomenology by Stephen E. Palmer

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Visual SystemRetinalImage

Image-basedStage

Surface-basedStage

Item-basedStage

Category-basedStage

WorkingMemory

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Image-basedStage

Surface-basedStage

Item-basedStage

Category-basedStage

WorkingMemory

RegionAnalysis

Figure/GroupDistinction

VisualInterpolation

ItemsGrouping

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Image-basedStage

Surface-basedStage

Item-basedStage

Category-basedStage

WorkingMemory

RegionAnalysis


VisualInterpolation

ItemsGrouping

Comparison Decision

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Image-basedStage

Surface-basedStage

Item-basedStage

Category-basedStage

WorkingMemory

RegionAnalysis


VisualInterpolation

ItemsGrouping

Comparison Decision

Items(Visuo-spatial scratchpad)

ArticulatoryLoop

CentralExecutive

Long-termMemory

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Image-basedStage

Surface-basedStage

Item-basedStage

Category-basedStage

WorkingMemory

RegionAnalysis


VisualInterpolation

ItemsGrouping

Comparison Decision


ArticulatoryLoop

CentralExecutive

Long-termMemory

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Image-basedStage

Surface-basedStage

Item-basedStage

Category-basedStage

WorkingMemory

RegionAnalysis


VisualInterpolation

ItemsGrouping

Comparison Decision


ArticulatoryLoop

CentralExecutive

Long-termMemory

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Visual System

Retinal image

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Visual System

Retinal image

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Visual System

Region analysis– Distinguish items based on their regions

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Visual System

Region analysis– Distinguish items based on their regions

Zhuolin Jiang and Larry S. Davis ; Submodular Salient Region Detection ;Conference on Computer Vision and Pattern Recognition, IEEE, 2013

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Visual System

Items grouping– Gestalt theory

• Gestalten: to put in form, to give structure

Fritz Perls*Berlin, July 8, 1893

†Chicago, March 14, 1970

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Visual System

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Visual System

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Visual System

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Visual System

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Visual System

Items grouping– Laws of the Gestalt

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Visual System


• Good form

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Visual System


• Good form

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Visual System


• Good form

• Continuity

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Visual System


• Good form

• Continuity

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Visual System


• Good form

• Continuity

• Proximity

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Visual System


• Good form

• Continuity

• Proximity

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Visual System


• Good form

• Continuity

• Proximity

• Similitude

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Visual System


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Visual System


• Common destiny

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Visual System


• Common destiny

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Visual System


• Common destiny

• Closure

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Visual System


• Common destiny

• Closure

Completion

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Visual System

Items grouping– Involvement of the memory

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Visual System

Items grouping– Involvement of the memory

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Visual System

Comparison– Involvement of the memory

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Visual System


• Spatial

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Visual System


• Spatial• Temporal

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Outline


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Memory Models

One modelItems

(Visuo-spatial scratchpad)Articulatory

Loop

CentralExecutive

Long-termMemory

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Memory Models

One modelItems


Loop

CentralExecutive

Long-termMemory

EpisodicMemory

ProceduralMemory

SemanticMemory

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Memory Models

One modelItems


Loop

CentralExecutive

Long-termMemory

EpisodicMemory

ProceduralMemory

SemanticMemory

ObjectsRepresentations

CategoriesRepresentations

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Memory Models

One model

EpisodicMemory

ProceduralMemory

SemanticMemory

ObjectsRepresentations

CategoriesRepresentations

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Memory Models

Another model

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Memory Models

Yet another model

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Memory Models

Yet another model

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Memory Models

Yet, yet another model

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Memory Models

Miller, 1956

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Memory Models

Miller, 1956

M R B X Q V L W Q K

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Memory Models

Miller, 1956

?

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Memory Models

Miller, 1956

?

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Memory Models

Miller, 1956

The Magical Number Seven, Plus or Minus Two:Some Limits on Our Capacity for Processing Information

?

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Memory Models

Brooks, 1978

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Memory Models

Brooks, 1978– Problem domain

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Memory Models

Brooks, 1978– Problem domain– Executing program

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Memory Models


– Knowledge domains• Hypothesis-and-verify process• Importance of documentation

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Memory Models


– Knowledge domains• Hypothesis-and-verify process• Importance of documentation

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Memory Models

Soloway, 1983– Experts’ knowledge that novices do not have

• Programming plans– RUNNING TOTAL LOOP PLAN– ITEM SEARCH LOOP PLAN– …

• Rules of programming discourse– An IF should be used when a statement body is guaranteed

to be executed only once and a WHILE used when a statement body may need to be repeatedly executed

– …

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Memory Models

Soloway, 1983

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Memory Models

Soloway, 1983An IF should be used when a statement body is guaranteed to be executed only once and a WHILE used when a statement body may need to be repeatedly executed

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Memory Models


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Memory Models


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Memory Models


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Memory Models

Pennington, 1987– Multiple abstractions for computer programs

(COBOL but may be true for other languages)• Abstraction of function• Abstraction of data-flow• Abstraction of control-flow• Abstraction of conditionalised actions

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Memory Models

Pennington, 1987

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Abstraction of function

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Abstraction of data-flow

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Abstraction of control-flow

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Abstraction of conditionalised actions

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Memory Models

Pennington, 1987– Programming knowledge

• Text structure knowledge– Sequences– Iterations– Conditionals

• Plan knowledgePlans are intermediate-level programming concepts

– Summing– Hashing– Counting– …

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Memory Models

Pennington, 1987– Which knowledge and what abstraction?

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Memory Models

Pennington, 1987– Which knowledge and what abstraction?

Text structure

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Abstraction of control-flow

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Memory Models

Van Mayrhauser, 1995– From previous works by

• Pennington• Soloway et al.• Rist• Van Mayhauser and Vans• Letovsky• Brooks• Schneiderman and Mayer

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Memory Models

Van Mayrhauser, 1995

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Memory Models

Van Mayrhauser, 1995

Integrated model

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Outline


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Mental Models

“The image of the world around us, which we carry in our head, is just a model. Nobody in his head imagines all the world, government or country. He has only selected concepts, and relationships between them, and uses those to represent the real system.”

—Jay Wright Forrester, 1971

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Mental Models

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Mental Models

Mental models

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Mental Models

Mental models Formal rules of inference

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Mental Models

Mental models Formal rules of inference Domain-specific rules of inference

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Mental Models

Mental models Formal rules of inference Domain-specific rules of inference Probabilities

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Mental Models

Mental models Formal rules of inference Domain-specific rules of inference Probabilities…

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Mental Models

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Memory Models

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Mental Models

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Mental Models

Context matters!

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Mental Models

Context matters!

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Mental Models

Context matters!

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Mental Models

Context matters!

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Mental Models

Context matters!

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Mental Models

Minsky, 1974– Frames

• “data-structure for representing a stereotyped situation”• “network of nodes and relations” and “slots”

– Frame-systems• Important actions are transformations between the

frames of a system • Different frames of a system share the same terminals

(and slots)– Matching process

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Mental Models

Minsky, 1974– Vision– Speech– Knowledge– Control

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Mental Models


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Mental Models

Minsky, 1974– Vision

• A frame, once evoked on the basis of partial evidence or expectation, would first direct a test to confirm its own appropriateness

• It would request information needed to assign values to those terminals that cannot retain their default assignments

• If informed about a transformation (e.g., an impending motion), it would transfer control to the appropriate other frame of that system

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Mental Models


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Mental Models

Minsky, 1974– Knowledge

• Similarity networks

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Mental Models

Minsky, 1974– Knowledge

• Similarity networks

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Mental Models


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Mental Models

Minsky, 1974– Control

• TOP-DOWN or LATERAL: Should one make a pass over all the terminals first or should one attempt a complete, detailed instantiation of some supposedly most critical one?

• CENTRAL CONTROL: Should a frame, once activated, "take over" and control its instantiation, or should a central process organize the operation

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Mental Models

Soloway, 1986– In the context of analyzing problems and

constructing programs– Goals

• Requirements• Bugs

– Plans• “Canned” solutions• With “meaning”

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Mental Models

Soloway, 1986“Master and novice chess players were shown a meaningful chess board, and asked to recall the pieces […]. The masters recalled more of the pieces than did the novices. Next, the masters and novices were shown a board in which the chess pieces were placed randomly on the board. […] The performance of the masters was the same as that of the novices.”

—Chase and Simon, 1973

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Mental Models

Soloway, 1986– Micro-strategies

• Ask questions• Seek answers• RepeatDifficult with delocalised plans

– Macro-strategies• Systematic (scalability?)• As-needed (correctness?)

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Mental Models

Rich and Waters, 1990(IBM’s Harlan Mills idea of “chief programmer teams”)

“[T]o provide software engineers with intelligent assistance.” (p. 2)

“The intended interaction between a software engineer […] is modeled after interaction with a human assistant.” (p. 2)

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Mental Models

Rich and Waters, 1990

“Between the engineer and the Apprentice […], the key to effective cooperation is shared knowledge.” (p. 4)

– Shared knowledge• About the system being worked on• About concepts of software engineering

Clichés

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Mental Models

Rich and Waters, 1990“[An algorithmic] cliché contains both fixed parts and parts that vary from one occurrence of the cliché to the next […], [it] may also include constraints […].” (p. 12)

“Non-algorithmic clichés are represented […] using standard frame-based knowledge representation techniques […].” (p. 21)

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Mental Models

Rich and Waters, 1990– Key properties of algorithmic clichés

• Canonical form• Language independence• Convenient manipulation• Expressiveness

– A representation of clichés The Plan Calculus

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Mental Models

Rich and Waters, 1990“The Plan Calculus is intended to be a blueprint language for software.” (p. 29)

• Formal representation for– Programs– Algorithmic clichés

Subroutines Program generators

MacrosFlowcharts Program schemas

Flowchart schemas Logic

Program transformation Data abstractionFormal grammars

Plan calculus

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Mental Models


if:negative

T F

then:negate

end:join

T F

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Mental Models


if:negative

T F

then:negate

end:join

T F

absolute-value

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Mental Models


next:apply-function

next:

input:

input:continue:

generation

generation

generate

output:*

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(On Gaming…)

Visual system Memory models Mental models

http://arstechnica.com/science/2014/02/how-action-games-can-improve-our-visual-skills/


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(On Gaming…)




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(On Gaming…)




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(On Gaming…)


“[G]amers [were] better at picking out details in a cluttered scene”



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(On Gaming…)


“[G]amers [were] better at picking out details in a cluttered scene”“[G]amers were able to produce accurate estimates [of relative counts]”



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(On Gaming…)


“[G]amers [were] better at picking out details in a cluttered scene”“[G]amers were able to produce accurate estimates [of relative counts]”“Gamers found it easier to perform mental rotations of geometric shapes”



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Outline


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Schema Theory

“The captain asked the passengers to fasten the seat belts. They were ready to take off.”

—Kohls and Scheiter, 2008

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Schema Theory

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Schema Theory

“This comprehensive situation is an interrelation of events and entities, and is stored in an internal data structure that can be activated by recognizing its typical features. Such data structures, or schemas, are mental representations in an individual’s mind.”


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Schema Theory

“This comprehensive situation is an interrelation of events and entities, and is stored in an internal data structure that can be activated by recognizing its typical features. Such data structures, or schemas, are mental representations in an individual’s mind.”


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Schema Theory

“Human brains operate fundamentally in terms of pattern recognition rather than of logic. They are highly constructive in settling on given schema and at the same time are constantly open to error.”

—Edelman, 2006(With minor adaptation)

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Schema Theory

Piaget, 1969– Child development theory– Schema and associated processes

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Schema Theory

Piaget, 1969– Child development theory– Schema and associated processes

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Schema Theory

Piaget, 1969– Schema and associated processes

• From Plato and Aristotle: essential commonalities, basic properties that are distinctive of an object

To Kant: link from stimuli to “pure” concepts– Perceived chair vs. “ideal” chair– No a-priori knowledge

• Gick and Holyoak: learning by examples and problem solving (like in mathematics)

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Schema Theory


• Abstract representation of multiple instances of the same kinds of

– Concept– Situation– Plan– Behaviour– …

to recognise similar / discriminate dissimilar experiences, access common concepts, draw inferences, create goals, develop plans, use skills

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Schema Theory


• Variables (or slots or attributes)

• (Constrained) Ranges of values– People’s experience– Constants – Optional or mandatory

• Constraints among variables and their values

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Schema Theory





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Schema Theory





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Schema Theory





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Schema Theory


• Prototypical object

• Object space and (mental) object generator

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Schema Theory




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Schema Theory




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Schema Theory




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Schema Theory




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Schema Theory


• Part-of

• Coupling

• Is-a

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Schema Theory


• Part-of

• Coupling

• Is-a

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Schema Theory


• Part-of

• Coupling

• Is-a

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Schema Theory


• Part-of

• Coupling

• Is-a

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Schema Theory


• Hierarchy– Contexts– Forces– Probabilities

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Schema Theory



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Schema Theory



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Schema Theory


• Use

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(Schema Theory Programming)

Papert worked with Piaget from 1958 to 1963 and afterwards– Constructionism

• Learning as a reconstruction rather than as a transmission of knowledge

• Learning is most effective when part of learner’s activity to build a meaningful product

http://www.lispcast.com/programming-language-stages-of-development

http://www.lispcast.com/programming-language-stages-of-development

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Papert developed the Logo programming language within the constructionism theory circa. 1967

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Explanations of Logo programming using a simplified cognitive development modelCorporal Visual Symbolic

– The child learns to see her own perspective from the outside in the turtle

– The child sees the results of her commands immediately (cf. chick sexing)

– The child could think of the result of her commands before their execution

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Explanations of object-oriented program-ming using the same simplified modelCorporal Visual Symbolic

– The ability to program from the perspective of a single object at a time

– The ability to think in terms of visual, archetypal interactions (client-server, MVC, etc.)

– The ability to build abstractions with simple yet powerful rules and meta-programming

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Schema Theory

Rumelhart and Norman, 1978– Models of learning

• Comprehension: pattern matching of memorised schema that cooperates and competes

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Schema Theory



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Schema Theory



• Animal face• human face• Bob’s face

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Schema Theory




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Schema Theory




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Schema Theory




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Schema Theory




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Schema Theory




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Schema Theory


• Accretion: specific situation or experience stored in schemas used to reconstruct original experience

– Episodic memory– Specific details

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Schema Theory




곰세마리가한집에있어아빠곰엄마곰애기곰아빠곰은뚱뚱해엄마곰은날씬해애기곰은너무귀여워

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Schema Theory




Why/How is specific information forgotten/replaced by generalised knowledge?

곰세마리가한집에있어아빠곰엄마곰애기곰아빠곰은뚱뚱해엄마곰은날씬해애기곰은너무귀여워

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Schema Theory


• Tuning: modifications to existing schemas– Variables– Ranges– Probabilities

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Schema Theory


• Tuning: modifications to existing schemas– Variables– Ranges– Probabilities

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Schema Theory


• Restructuring: ex nihilo / copy of existing schemas– Schema generation by analogies with existing schema, is-a– Schema induction from existing schema, has-a

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Schema Theory


• Restructuring: ex nihilo / copy of existing schemas– Schema generation by analogies with existing schema, is-a– Schema induction from existing schema, has-a

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Outline


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Software Patterns

Schemas– Variables

– Ranges of values• Forces

– Constraints among variables and their values

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Software Patterns




What class plays this role?

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Software Patterns




Possible classes playing this roleplus their relations, implementation…

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Software Patterns




Expected relations, interactions…

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Software Patterns

Schema theory

“The pattern is an attempt to discover some invariant features, which distinguishes good places from bad places with respect to some particular system of forces.”

—Christopher Alexander, 1979

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Software Patterns

Knowledge and–or procedure

“The solution part of a good pattern describes both a process and a thing: the ‘thing’ is created by the ‘process’.”


“Furthermore, a pattern tells about a form not only what it is but also what it does.”


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Software Patterns

Space and generation

“A pattern describes a coherent yet infinite design space, not a finite set of implementations in that space.”

—Frank Buschmann, Kevlin Henney, and Douglas C. Schmidt, 2007

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Software Patterns

Use design patterns– Composite– Decorator– Observer– …

to generate the architecture of the program

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Software Patterns

Wholeness– Quality Without a Name

• Forces

“Having an ideal concept of a thing lets one judge the beauty of it”


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Software Patterns

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Software Patterns

“Important assumptions– That patterns can be codified in such a way that

they can be shared between different designers– That reuse will lead to “better” designs. There is

an obvious question here of what constitutes “better”, but a key measure is maintainability”

—Zhang and Budgen, 2012 (With minor adaptations)

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Outline


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Empirical Studies

“Eye movements are uniquely poised between perception and cognition. They are central to the function of the visual system, but for such scanning to be efficient, it cannot be simply a random sample of the visual world. To be useful, eye movements must be related to an organism’s memories, expectations and goals. Consequently, eye movements are driven equally by bottom-up perceptual properties of the world and top-down cognitive processes.”

—Richardson, Dale, and Spivey, 2013

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Empirical Studies

“Eye movements are uniquely poised between perception and cognition. They are central to the function of the visual system, but for such scanning to be efficient, it cannot be simply a random sample of the visual world. To be useful, eye movements must be related to an organism’s memories, expectations and goals. Consequently, eye movements are driven equally by bottom-up perceptual properties of the world and top-down cognitive processes.”


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Empirical Studies

“Eye movements are uniquely poised between perception and cognition. They are central to the function of the visual system, but for such scanning to be efficient, it cannot be simply a randomsample of the visual world. To be useful, eye movements must be related to an organism’s memories, expectations and goals. Consequently, eye movements are driven equally by bottom-up perceptual properties of the world and top-down cognitive processes.”


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Empirical Studies

“Eye movements are uniquely poised between perception and cognition. They are central to the function of the visual system, but for such scanning to be efficient, it cannot be simply a randomsample of the visual world. To be useful, eye movements must be related to an organism’s memories, expectations and goals. Consequent, eye movements are driven equally by bottom-up perceptual properties of the world and top-down cognitive processes.”


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Empirical Studies

“Eye movements are uniquely poised between perception and cognition. They are central to the function of the visual system, but for such scanning to be efficient, it cannot be simply a randomsample of the visual world. To be useful, eye movements must be related to an organism’s memories, expectations and goals. Consequent, eye movements are driven equally by bottom-upperceptual properties of the world and top-downcognitive processes.”


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http://web-tan.forum.impressrd.jp/e/2009/04/02/5280

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http://another-voice.jp/jp/katsu/professional_view/01/index.shtml

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http://another-voice.jp/jp/katsu/professional_view/01/index.shtml

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Empirical Studies

Data– Fixations– Saccades– Scan path

Analyses– Centres of interests– Effort– Duration– …

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Empirical Studies

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Empirical Studies

SR Research Eye-link II– www.sr-research.com– Intrusive– Two infra-red cameras and one sensor– Error rate < 0.5º– Sampling rate of 500Hz– Access eye position < 3.0 ms.– 0.01º RMS resolution (tilt)

EyeLink Data Viewer

http://www.sr-research.com

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Empirical Studies

Tobii 1750 eye-tracker – www.tobii.se– Non-intrusive (no head mount)– Two cameras built into a 17 in flat screen– Records audio and video of a session– Error rate < 0.5º– Sampling rate of 50Hz

ClearView software

http://www.tobii.se

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Empirical Studies

Seeing Machines FaceLab 5– www.seeingmachines.com– Non-intrusive– Two infra-red cameras– Error rate < 1º– Sampling rate of 60Hz– Complete head-tracking ±90º (y), ±45º (x) – Complete eye-tracking ±45º (y), ±22º (x)

GazeTracker

http://www.seeingmachines.com

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Outline


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Conclusion

“That practices can be codified in such a way that they can be shared between different designers”

—Zhang and Budgen, 2012

What format? How memorised? How acquired?

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Conclusion



What format? Schema theory How memorised? How acquired?

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Conclusion



What format? Schema theory How memorised? Long-term memory How acquired?

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Conclusion



What format? Schema theory How memorised? Long-term memory How acquired? Gestalt theory

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Conclusion

Software patterns– Schema theory– Knowledge and–or procedure– Space and generation– Wholeness

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Conclusion

Empirical studies– Patterns use and usefulness

• Faults• Changes• Comprehension• …

– Many opportunities to understand program comprehension better!

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Conclusion

Empirical studies– Patterns use and usefulness

• Faults• Changes• Comprehension• …

– Many opportunities to understand program comprehension better!

Software Design Patterns in Theory

Technology

Transcript of Software Design Patterns in Theory