model-driven programming education michael e. caspersen department of computer science and centre...

Model-DrivenProgramming Education

Michael E. CaspersenDepartment of Computer Scienceand Centre for Science Education

Aarhus University, [email protected]

Workshop @ ACE 2013

ACE 2013, Adelaide, AUS Model-Driven Programming Education 2

Three Perspectives on Programming

• Instructing the computer (coding)– the purpose of programming is to instruct the computer– focus is on aspects of program execution such as storage

layout, control flow, parameter passing, etc.

• Managing the program description– the purpose of programming is to create a software architecture

that provides overview and understanding of the entire program– focus is on aspects such as visibility, scope, encapsulation,

modularity, software design etc.

• Conceptual modeling– the purpose of programming is to express concepts, structure

and relations– focus is on constructs for describing concepts, phenomena and

relations between these


Characterization and Expectations

• Characterise the introductory programming course at your home institution– other views on programming?– how are the views balanced in the intro course?– what defines the progression in your intro course?

• What are your expectations for this workshop?


Contents and Progression• Traditional approach

– typical textbooks only address the first and to some extend the second perspective

– topics are organized according to the syntactical structures in the programming language (bottom-up)

– tendency to completeness in coverage of topics– syntax-driven progression

• Our approach– a balanced coverage of all three views– conceptual modeling is leading the way– systematic programming (no more pulling rabbits out of the hat)– early bird & spiral approach– model-driven progression

5

Sample Exam Assignment

PlaylistString playlistNamevoid addTrack(Track t)void removeTrack(Track t)Track findShortestTrack()List<Track> find(String s)void printSortedTracks()

*

TrackString artistString songNameint minint secString toString()

Drivervoid exam()

1. Create a simple class Track ... with constructor and a toString method…

2. Create a test method exam…3. Create two instancies…4. Create a new class Playlist ...5. Implement the methods addTrack

and removeTrack6. Modify the test method to create a

Playlist object…7. Implement and test method

findShortestTrack8. Implement and test method

findTracksByArtist …9. Let the Track class implement

interface Comparable …10. Implement the method

printSortedTracks and modify ...

ACE 2013, Adelaide, AUS Model-Driven Programming Education

6

The ”Complete” Model

PlaylistString playlistNamevoid addTrack(Track t)void removeTrack(Track t)Track findShortestTrack()List<Track> find(String s)void printSortedTracks()

TrackString artistString songNameint minint secString toString()

Drivervoid exam()

Collectionsvoid sort(List l)

Comparableint compareTo(T e)

Java’s Collections Framework

*


<<implements>>

Learning Goals and Examination Form

• By the end of the course the students must be able to– apply fundamental constructs in an ordinary PL– explain the architecture of simple programs– explain the semantics of simple specification models– implement simple specification models in an ordinary PL– apply selected classes from a standard class library


Oral Exam

Written Exam

Multiple Choice

Practical Exam

Alignment

Weekly mandatory assignments prepare the students for the exambut don’t count in the final grading


Course Context and Structure

A Quarter (7 weeks)

1

2

3

4

5

6

7

Q2

Q3

Q4

An Academic Year

Q1

Progression

Complexity of class models (language stuff added by need)

9

Course Phases (week numbers)(1) Getting started

Overview of fundamental concepts. Learning the IDEs and other tools.

(2) Introduction to the basicsClass, object, state, behaviour, control structures.

(3-4) Conceptual framework and structural patterns Control structures, data structures (collections),

class relationship, patterns for implementingstructure (association).

(4-5) Programming methodSTREAM, patterns for implementing functionality

(algorithmic patterns).

(6) Subject specific assignmentPractice on harder problems.

(7 (+ 8-9)) PracticeAchieve routine in solving standard tasks (prep for exam).



Key Points (and Agenda)• Conceptual modelling

– Conceptual modelling is the defining characteristic of OO

• Progression– Progression in terms of complexity of class models (not

syntax of a programming language)

• Systematic programming– Systematic programming revealed through basic (structural and

algorithmic) patterns and STREAM (a programming method for novices)

• Learning-theoretic foundation– A learning-theoretic foundation (Cognitive Load Theory,

Cognitive Apprenticeship, and Worked Examples)


References1. O.L. Madsen, B. Møller-Pedersen and K. Nygaard (1993): Object-Oriented

Programming in the BETA Programming Language, Addison-Wesley. [ Link ]

2. M.E. Caspersen (2007), Educating Novices in the Skills of Programming, DAIMI PhD Dissertation PD-07-4, ISSN 1602-0448 (paper), 1602-0456 (online). [ Link ]

3. M.E. Caspersen and J.B. Bennedsen (2007), Instructional Design of a Programming Course: A Learning-Theoretic Approach, Proceedings of the 3rd International Computing Education Research Workshop, ICER 2007, Atlanta, GA, USA, September 2007, pp. 111-122. [ Link ]

4. J.B. Bennedsen and M.E. Caspersen (2007), Assessing Process and Product — A Practical Lab Exam for an Introductory Programming Course, Innovation in Teaching and Learning in Information and Computer Sciences, Vol. 6 (4), Special Issue on Innovative Methods of Teaching Programming, pp. 183-202. [ Link ]

5. J.B. Bennedsen, M.E. Caspersen and M. Kölling (2008), Reflections on the Teaching of Programming, Lecture Notes in Computer Science, Vol. 4821, Springer-Verlag. [ Link, ToC ]

6. J. B. Bennedsen and M.E. Caspersen (2008), Model-Driven Programming, in [5], pp. 116-129. [ Link ]

7. M.E. Caspersen and M. Kölling (2009), STREAM: A First Programming Process, ACM Transactions on Computing Education (TOCE), Vol. 9 (1), Article No. 4, pp. 1-29. [ Link ]

ftp://ftp.cs.au.dk/pub/beta/betabook/betabook.pdf

http://www.daimi.au.dk/~mec/dissertation/Dissertation.pdf

http://cs.au.dk/~mec/publications/conference/26--icer2007.pdf

http://cs.au.dk/~mec/publications/journal/27--italics2007.pdf

http://www.springer.com/computer/general+issues/book/978-3-540-77933-9

http://link.springer.com/book/10.1007/978-3-540-77934-6/page/1

http://link.springer.com/chapter/10.1007/978-3-540-77934-6_10

http://cs.au.dk/~mec/publications/journal/34--toce2009.pdf

A Conceptual Framework forObject-Oriented Programming

There is more to OO than Java...


Kristen Nygaard on Object-Orientation

A program execution is regarded as a physical model system simulating the behavior of either a real or imaginary part of the world.

Physical modeling is based upon the conception of reality in terms of phe-nomena and concepts.

A physical model system is construc-ted, modeling phenomena by objects and concepts by categories of objects.

Kristen Nygaard, 1926-2002

An Interlude on Concepts


What is a concept?


Concepts and phenomenons of EPR

• Electronic Patient Record (EPR)

– Patient (Lance Armstrong, John Kerry, ...)

– Treatment (bandaging, rest, physical therapy, ...)

– Diagnosis (sprained wrist, broken leg, yellow fever, ...)

– Operation (removing the appendix, sterilization, brain surgery, ...)

– Doctor (Beth Barry, Lou Lazanta, ...)

– Nurse (Jane Clemenza, Laura Hopcroft, ...)


Model of EPR

Problem domain Model

Doctor

Patient Diagnosis

Treatment

SeniorDoctor

JuniorDoctor

...

*

1

*

*


Conceptual Modelling

Conceptual model(problem-specific

concepts)

Problem/vision concerning phenomena

Specification model (realised concepts)

Objects (program, language, OS,

machine)

abstraction abstraction

modelling


ACE 2013, Adelaide, AUS 18

Phenomena and Concepts

• A phenomenon is– a thing that has definite, individual existence in reality or in the

mind; anything real in itself

• A concept is– a generalised idea of a collection of phenomena, based on

knowledge of common properties of instances in the collection

Model-Driven Programming Education


Characterisation of Concepts

• Designation– The collection of names (or pictures) by which the concept is

known

• Extension– The collection of phenomena that the concept somehow covers

• Intension– The collection of properties that in some way characterize the

phenomena in the extension of the concept



Examples of Concepts

Designation Extension Intension

Horse

Car

Rectangle

Food



Aristotelian View

• Characterisation (intension :-)– The intension is a collection of properties that may be divided

into two groups• defining properties that all phenomena in the extension must have• characteristic properties that the phenomena may have

– Well-defined concepts with sharp borders– Relatively homogeneous phenomena– The extension is uniquely determined by the intension

(objectively determinable)

• Examples (extension :-)– Does to some extend exist in well-established topic areas such

as mathematics, physics, zoology, botany, ...



Prototypical View

• Characterisation (intension :-)– The intension of a concept consists of examples of properties

that phenomena may have, together with a collection of typical phenomena covered by the concept: prototypes

– Blurry concepts with vague borders– Great variation among phenomena– The extension is not uniquely determined by the intension

• Examples (extension :-)– Everywhere!



Conceptual Modelling, revisited

• Problem Specific Concepts (PSC) are almost always of prototypical nature

• Realised Concepts (RC) are Aristotelian (because of our programming languages)

• This mismatch represents a challenge for modelling– to give an Aristotelian definition to prototypical concepts


RCPSC



Concept Formation• Identification of phenomena

– Socrates– Batmobile– Hannibal’s march across the Alps– Neil Young– Sirius 2000– Herbie– Hillary Clinton

• Classification

Person

SocratesNeil Hillary

Car

Batmobile Herbie

Journey

Sirius 2000 Hannibal’s march across the Alps


Classification in UMLClasses represent concepts,objects represent phenomena

Example Concept: PersonPhenomena: Bruce, Paul, Michael

Person

isTeenager()isOld()age()

String nameint age

Class

: Person”Bruce”

63 : Person”Paul”

70: Person”Michael”

52

Objects


Classification in Java

class Person { private String name; private int age;

public Person(String name, int age) { this.name = name; this.age = age; }

public void birthday() { age++; }

public isTeenager() { return (age >= 13 && age <= 19) }}

List l = new ArrayList();

l.add( new Person(”Bruce”, 63) ); l.add( new Person(”Paul”, 70) ); l.add( new Person(”Michael”, 52) );


Relations between concepts

• Aggregation– has-a

• Association– X-a

• Generalization/specialization– is-a

Organization of knowledge...


Aggregation (has-a)

Relation between concepts describing a whole and (some of) the parts which constitutes the whole (part-whole structure).

UML: Composition

Car

Motor Wheel Body Seat

Door Roof Fender

Journey

Departure DestinationDuration Means oftransportation


Aggregation in UML (1)

ClockDisplay

timeTick()setTime(int h, int m)getTime(): String

NumberDisplay hours;NumberDisplay minutes;String displayString;


Aggregering i UML (2)

ClockDisplay

timeTick()setTime(int h, int m)getTime(): String

NumberDisplay

getValue()getDisplayValue()setValue()increment()

int limit;int value;String displayString;

2


Aggregation in Java

class NumberDisplay { private int limit, value;

public NumberDisplay() { ... } public int getValue() { ... } public String getDisplayValue() { ... } public void setValue(int replacementValue) { ... } public void increment() { ... }}

class ClockDisplay { private NumberDisplay hours; private NumberDisplay minutes; private String displayString;

public ClockDisplay() { hours = new NumberDisplay(24); minutes = new NumberDisplay(60); } public void timeTick() { ... } public void setTime(int hour, int minutes) { ... } public String getTime() { ... }}


Association (X-a)

Relation that describes a dynamic relation between concepts where the phenomena exist independently of each other and just occasionally are associated.

MailServer keeps MailItem

Person owns CarPerson rents Car

Person loves PersonPerson is-friend-with Person

Student is-enrolled-at Course

Patient have-had Disease


Association in UML

Person Car

MailServer MailItem

Student Course

*keeps

*owns

0..1 owned

*

takes

*

Multiplicity (cardinality): 0..1, 1, n, a..b, 0..* (*)

Role

Orientation (1-way, 2-way)

can-drive *


Association in UML (X-a)

MailServer

howManyMessages(String who): intgetNextMailItem(String who): MailItempost(MailItem item)

MailItem

getFrom(): StringgetTo(): StringgetMessage(): Stringprint()

0..*

X = keeps

from: Stringto: Stringmessage: String


Association in Java

class MailItem {

private String to; private String from; private String message;

public MailItem( ... ) { ... }

public String getFrom() { ... } public String getTo () { ... } public String getMessage() { ... } public void print() { ... }}

class MailServer {

private List messages;

public MailServer() { messages = new ArrayList(); }

public int howManyMessages (String who) { ... }

public MailItem getNextMailItem (String who) { ... }

public void post(MailItem item) { ... }}


Generalization/specialization (is-a)

Combine concepts to a more general concept.

Vehicle

TruckCar Bus

TaxiPassenger car Ambulance

Van Sedan


What makes a concept special?Means of transportation Plane Passenger plane Airliner Sports plane Military plane Ship Vehicle Car Bus Truck Lorry Pick-up Truck Passenger car Van Taxi Bicycle

Figure Ellipse Circle Triangle Isosceles triangle Equilateral Right-angled Four-sided polygon Trapezoid Parallelogram Rectangle Square Kite

Additional properties!


Specialization: extra properties

A

B

B is-a A

Intension(A) Intension(B)

Extension(B) Extension(A)

A concept’s intension: The collection of propertiescharacterising the concept

A concept’s extension: The collection of phenomenacovered by the concept


Specialization in UML

LendableItem

lend(l: borrower)return()isAvalable()

Book

author()publisher()ISBN()

Video

producer()format()playingTime()

Generalconcept

Specialconcepts


Specialization in Java

class LendableItem { void lend(Borrower b) { // code for lend }

void return() { // code for return }

boolean isAvalable() { // code for isAvalable }

...}

class Book extends LendableItem { String author() { ... } String puclisher() { ... } String ISBN() { ... } ...}

class Video extends LendableItem { String producer() { ... } String format() { ... } int playingTime() { ... } ...}


Concept formation and OO-languages

• Classification

• Aggregation– has-a

• Association– X-a

• Specialization– is-a

• class

• Reference (attribute)– aggregate has responsibility for

the creation

• Reference (attribute)– dynamic relation

• extends– subtype


Summary• Conceptual framework for object-orientation

– Concepts and modelling– Structure: aggregation, association, specialization– is used for organizing knowledge about a problem domain

and structure in the solution domain– Is (to some extend) supported by language constructs in OO

languages

• Modelling examples– Abstract models in UML– Implementation in Java– Examples from textbook [Barnes & Kölling] – which does not

explicitly present the models...

Model-Driven Programming

Programming in Context


Hand-in-Hand Modeling and Coding (1)

• David Gries (Edsger W. Dijkstra)– the loop body and the loop invariant is developed hand-in-hand

with the latter leading the way

• We (Kristen Nygaard)– coding and class modeling is done hand-in-hand with the latter

leading the way

• Design by contract and systematic programming– a class model is a design contract in precisely the same way

as a loop invariant is– code is introduced on purpose (fulfilling the contract)


Intermezzo: Contracts at Four Levels

• Model– relations between classes (interfaces)– association, aggregation/copmposition, specialization

• Interface (spec)– functional specification (pre and post conditions)

• Class (impl)– class invariant (representation invariant)

• Method– assertions (loop invariant)

• Systematic programming– systematic techniques associated with each level


Systematic Implementation Techniques

• Inter-class structure– implementation of specification model using standard patterns

for implementing relations between classes

• Intra-class structure– implementation of interface or class specifications using

STREAM– implementation using class invariants

• Methods– algorithmic patterns (sweep, search, divide and conquer, ...)– loop invariant techniques

Separation of concerns...


Intermezzo: Contracts at Four Levels

• Model– relations between classes (interfaces)– association, aggregation/copmposition, specialization

• Interface (spec)– functional specification (pre and post conditions)

• Class (impl)– class invariant (representation invariant)

• Method– assertions (loop invariant)

• Systematic programming– systematic techniques associated with each level

Our focustoday



Person

name

...



class Person { private String name;

public Person(String name) { this.name = name;

}

...}

Person

name

...



Person

class Person { private String name;

public Person(String name) { this.name = name;

}

...}

lover

0..1



Person

class Person { private String name; private Person lover;

public Person(String name) { this.name = name; lover = null;

}

public fallsInLoveWith(Person p) ...

...}

lover

0..1



Person

class Person { private String name; private Person lover;

public Person(String name) { this.name = name; lover = null;

}

public fallsInLoveWith(Person p) ...

...}

lover

0..1

spouse

0..1



Person

class Person { private String name; private Person lover; private Person spouse;

public Person(String name) { this.name = name; lover = null; spouse = null;

}

public fallsInLoveWith(Person p) ... public marries(Person p) ...

...}

lover spouse

0..1 0..1



Person

class Person { private String name; private Person lover; private Person spouse;

public Person(String name) { this.name = name; lover = null; spouse = null;

}

public fallsInLoveWith(Person p) ... public marries(Person p) ...

...}

lover spouse

friends

0..1

*

0..1



Person

class Person { private String name; private Person lover; private Person spouse; private List friends;

public Person(String name) { this.name = name; lover = null; spouse = null; friends = new ArrayList(); }

public fallsInLoveWith(Person p) ... public marries(Person p) ... public becomesFriendWith(Person p) ... ...}

lover spouse

friends

0..1

*

0..1


Example: Telstra Lite

Customer Subscription1 * Transaction*

PaymentCall

MMS SMS

Conversation

Image Sound

Video

MMObject *


Model-Driven Programming

• Model-driven– programming tasks starts from a class model– mostly, the model is given– sometimes, also (a part of) the model must be developed– Incremental development: Stepwise Improvement (STREAM)

• Progression– models become increasingly complex during the course– associated systematic programming techniques– language issues covered “by need” (introduced very early)


Course Progression

Conceptual Model

Problem/vision

Specification Model

Implementation Model

Analysis Implementation

Design

Reference System Model System


Course Progression

Conceptual model

Problem/vision

Specification model

Implementation model

Analysis Implementation

Design


60

Model-Based Progression

A

Stand-alone class

Shape, Turtle, Person, Die, Date, Heater, Account, ...

A

Simple association and composition

B A B22

DieCup, ClockDisplay, ...

A

Recursive Association0..1

A*

Person (lover and fiancee),Person (friends)

Animal (parents, brood), ...

A

Association (to another class)

B A B*0..1

Car-Person (isOwnedBy),Track-Playlist (contains)

Implementing an interface

A B*

IComparable and ComparatorUse of Collections.sort(), etc.

61

Faded Guidance and Cognitive Apprenticeship

3. A lab session follows where the students interact with, modify, and extend both examples.

1. In a lecture we present an example of development of a program with two classes, Playlist and Track. P T*

2. A video presentation of a partial development of a similar example (say Account and Transaction) is made available.

A T*

4. A follow-up exercise is provided where the students extend the Playlist-Track example by adding an Image

class.

P T*

I*

5. In the following week we give a mandatory assignment where the students implement a system of three classes,

say Notebook, Note, and Keyword.

Nb N*

K*

Worked examples with high variability increase cognitiv

e load and

learning (if intrin

sic cognitive load is suffic

iently low).

Variability

effect, 1

994 ( Germ

ane Cognitive Load)

Example


Exercise• Create one or two exercises by concretizing the

following models:

A B*

A B2

A B*

B1 B2

a)

b)

c)


Motivating and Engaging Problems

• Real-world examples– no factorial– no fibonacci numbers

• Multimedia– image and sound processing

• Mobile technology– cell phones– PDAs– MP3-players

• Internet technology– web browser

• Sample projects– Turtle Graphics– Die, Dice-cup– Date– Personal relations– Musician-Band-Festival– Car rental– Library (lending of books)– Banking (accounts, etc.)– Image and sound processing– Text processing (hyphenation)– Synchronizing calenders– MP3-player (track, tracklist, ...)– Web browser– ...


Assessment (Varying Cover Story)

Track * Playlist

Luggage * Flight

TextFile * Directory

Magazine * Subscriber

Card * Deck

Employee * Department

Diagnosis * Person

Plant * Allotment

SideEffect * Medicine

Picture * MemoryCard

TimeSheet * HourlyPaid

Instrument * Musician

65

Principles of Programming Education

Practice consume before produce

Present worked, exemplary examples

Reinforce patterns and conceptual frameworks

...

Method Class Model

Use 1 1 1

Modify 2 3 4

Create 5 6 7

Allows more interesting things to be done.

Helps separate spec and impl.

Applies at many levels (code specification, class libraries,

design patterns, frameworks, ...)

66

Course Phases(1) Getting started: Overview of

fundamental concepts. Learning the IDEs and other tools.

(2) Introduction to the basics: Class, object, state, behaviour, control structures.

(3) Conceptual framework and patterns: Control structures, data structures

(collections), class relationship, patterns for implementing structure (association).

(4) Programming method: STREAM, patterns for implementing functionality

(algorithmic patterns).

(5) Subject specific assignment: Practice on harder problems.

(6) Practice: Achieve routine in solving standard tasks (prep for exam).

Method modifyMethod create

Class modify

Method use

Class create

Class create

Class create

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tionACE 2013, Adelaide, AUS Model-Driven Programming Education


Benefits of MDP

The integrated approachmotivate and support students

in their understanding and practice ofthe programming process

The integration ofconceptual modeling and coding provides

structure, traceability, and a systematic approach toprogram development


Wrapping Up: Key Points

• Conceptual modeling– the defining characteristic of object-orientation

• Model-Driven Programming– programming tasks take-off from a class model– coding and conceptual modeling is done hand-in-hand with the

latter leading the way

• Progression– driven by complexity in class models– stressing associated techniques of systematic programming– language issues covered by need


Key Points (and Agenda)• Conceptual modelling

– Conceptual modelling is the defining characteristic of OO

• Progression– Progression in terms of complexity of class models (not

syntax of a programming language)

• Systematic programming– Systematic programming revealed through basic (structural and

algorithmic) patterns and STREAM (a programming method for novices)

• Learning-theoretic foundation– A learning-theoretic foundation (Cognitive Load Theory,

Cognitive Apprenticeship, and Worked Examples)

Model-DrivenProgramming Education

Michael E. Caspersen

Department of Computer Science

and Centre for Science Education

Aarhus University, Denmark

[email protected]

Workshop @ ACE 2013

Structure (for planning only)


Topic Key point Activity

Intro Exam and main points Introduction

Concepts and conceptual modeling

CM is a defining characteristic of OO

What is a concept?

Didactical design Progression in terms of complexity of class models, not syntax of a language

Design an exercise for a given generic class model

Algorithm vs. structure Lennon & McCartneyStan & LaurelAlice and Randy PauschACE and Mats Daniels

Find loop-based algorithms for the concrete structure from above

Forest and trees Code comprehension is not trivial! Beacons in the code is a necessity (assertions).

What does this program do? (three simple examples: one trivial and two hard ones)

Systematic programming Patterns and methodology (STREAM)

Identify other basic patterns

Parameterization Fundamental design tool Find good examples...


Programs as models

It’s not the purpose of our programsto instruct the computer;

it’s the purpose of the computerto execute our programs

E.W. Dijkstra

A program execution is regarded asa physical model system

K. Nygaard

73

Pattern-Based Instruction

MotivationPatterns capture chunks of programming knowledge and skills.

Reinforces schema creation when cognitive load is “controlled” (+germane cognitive load).

(Cognitive science and educational psychology)

OriginIdeas similar to pattern-based instruction can be traced back to

Mayer (1981), Soloway (1986), Rist (1989), Linn & Clancy (1992).

East et al. (1996) and Wallingford (1996) were among the first to accept the challenge put forward by Soloway.

Soon, others followed, e.g. Astrachan et al. (1997, 1998),Reed (1998), Bergin (2000).



Systematic Implementation Techniques

• Inter-class structure– implementation of specification model using standard patterns

for implementing relations between classes

• Intra-class structure– implementation of interface or class specifications using

STREAM– implementation using class invariants

• Method structure– algorithmic patterns (sweep, search, divide and conquer, ...)– loop invariant techniques

Separation of concerns...

75

Patterns at Two Levels

Inter-class structureStandard coding patterns for the implementation of relations

between classes.

Intra-class structureClass invariants and

techniques for evaluating these.

Method structureAlgorithmic patterns,

elementary patterns and loop invariants.

Association patternAggregation patternSpecialization pattern

Sweep patternSearch patternDivide, solve, and combine...


model-driven programming education michael e. caspersen department of computer science and centre...

Documents

purpose of programming

programming language

way systematic programming

test method exam

track class

method printsortedtracks

tostring method

test method findshortesttrack