1 Course Summary Fall 2005 CS 101 Aaron Bloomfield

2 Course Reflection

3 Course goals  Objectives: Students who complete the course will: Understand fundamentals of programming such as variables, conditional and iterative execution, methods, etc. Understand fundamentals of object-oriented programming in Java, including defining classes, invoking methods, using class libraries, etc. Be aware of the important topics and principles of software development. Have the ability to write a computer program to solve specified problems. Be able to use the Java SDK environment to create, debug and run simple Java programs.

4 Unstated course goals  Everybody needs to have a “base” level of programming to continue on in the CS courses (or as required by other departments) CS 101 and 201 provide that “base” level

5 What was new this semester  Test code required In hindsight, this should have been explained better  More TA office hours This was well received by everybody  Faculty mini-talks Had trouble scheduling this in a coherent way, so only one happened this semester. Should I do more?  Labs Many were improved upon, and a few were added  Increased number of HWs by 2  Final few assignments were for a common big program In hindsight, we see a better way to implement this next semester  Changing of the order the chapters were gone over

6 Changes on deck for next semester  Will keep (and improve upon) all the stuff from the last slide  Study groups The idea is a way for people to study and/or work together  This does NOT mean group assignments, however There were not enough people to make this work this semester  Probably will ditch CodeLab - it didn’t work as well as I had hoped It’s a good idea, but a real pain to manage properly  I want to talk about debugging more We are considering a site license for the debugging version of JCreator  Better web site design (it’s in development now – thoughts?)  Will most likely lower the number of midterms to two (and require the final)  Want to put more diagrams in the slides (make them more visual)  Will have the TAs give review sessions before the tests  Might have forums/newsgroups on the website

7 What didn’t work this semester  I botched a lecture back in September (in chapter 3) With this fixed, I’ll have freed up one more lecture session Plus one for the removed midterm  A number of things worked, but need improvement (mentioned before): Implementation of the game Faculty mini-talks Required test code  The semester schedule (i.e. Thanksgiving break) made it difficult to properly teach arrays There wasn’t a HW on 1-D arrays as a result This won’t be a problem in the spring, but will be next fall  Had a bit of trouble keeping the lectures interesting towards the end of the semester  Want to lower the amount of student frustration

8 What did work this semester  This class learned much more than last semester’s class did Even if you feel confused now, take my word for it And as my goal is to teach (and not to be popular), this is a good thing  Changing of the order the chapters were gone over  Improved TA office hours  Improvements to the labs  Grading system worked very well this semester  All the code on the website  Many things that were “behind the scenes” TA organization and utilization Grading system Me delegating the work better to the TAs

9 Did I push too hard this semester?  I pushed the class much harder this semester than last semester  But did I push too hard?  Consider: I’ve gotten as many “things are going great” comments as I have “things are too hard” comments (anecdotal) Homeworks took under 5 hours on average  The results from the survey questions for each HW There were 8 HWs over about 16 weeks  That’s 2.5 hours (on average) on homeworks per week  Ultimately, I think that with a bit better organization, I can lower the amount of time spent on the HWs while still having people learn the same amount  I’m interested in your feedback on this! But not today in lecture….

10 The Big OOP Picture

11 The classes for the game  Creature (HW J6)  Weapon (HW J6)  Room (HW J7)  Map (HW J8)  Game (HW J8)  Parser (lab 9)  Descriptions (lab 10)  MapPrinter (lab 11)

12 How a big OOP program interacts  Note how the classes interacted in the game  A lot of objects were created and manipulated A Room for each spot in the grid Creatures and Weapons for some of the Rooms A Map object Etc.  The way this game has objects interacting is how a big OOP program would work  Encapsulation The Room class didn’t need to know how the Creature class kept track of whether the monster was angry or not  It just called getAngry() and setAngry()  It could have been stored as a boolean or an int

13 Problem solving  To solve a problem in CS, you break it down into smaller and smaller pieces  A big program is broken down into packages Which we haven’t seen yet Consider the game to be one package  The packages are broken down into hierarchies This uses inheritance Our game didn’t use a hierarchy, as you did know of inheritance at that point  The hierarchies are broken down into classes The game had 8 classes  Each class is broken down into methods and variables Some (such as MapPrinter) only had 1; others (such as Map) had dozens  Each method is broken down into parts, etc.

14 The completed game  This could easily be made by multiple people Each person does a separate class Not exactly equal, but it still lowers the workload  Our (fully commented) code for the game was over 1,300 lines  However long yours was, it was a program greater than 1,000 lines Even if you had trouble getting parts working, and had to use our code You still wrote part, and saw how it interacted with the rest of the system

15 Review of Chapter 1

16 Demotivator winners! Methodology Methodology –1 st place vote counted for 3 points –2 nd place vote counted for 2 points –3 rd place vote counted for 1 point Will buy two demotivators and hang them in my office… Will buy two demotivators and hang them in my office… The results, with 137 of 173 precincts reporting… The results, with 137 of 173 precincts reporting…

17 Engineering software  Complexity of software grows as attempts are made to make it easier to use

18 Software engineering  Goal Production of software that is effective and reliable, understandable, cost effective, adaptable, and reusable  Goal Production of software that is effective and reliable, understandable, cost effective, adaptable, and reusable  Work correctly and not fail  Goal Production of software that is effective and reliable, understandable, cost effective, adaptable, and reusable  Because of the long lifetime many people will be involved Creation Debugging Maintenance Enhancement  Two-thirds of the cost is typically beyond creation  Goal Production of software that is effective and reliable, understandable, cost effective, adaptable, and reusable  Cost to develop and maintain should not exceed expected benefit  Goal Production of software that is effective and reliable, understandable, cost effective, adaptable, and reusable  Design software so that new features and capabilities can be added  Goal Production of software that is effective and reliable, understandable, cost effective, adaptable, and reusable  Makes sense due to the great costs involved to have flexible components that can be used in other software

19  Abstraction  Encapsulation  Modularity  Hierarchy  Abstraction  Encapsulation  Modularity  Hierarchy  Abstraction  Encapsulation  Modularity  Hierarchy  Abstraction  Encapsulation  Modularity  Hierarchy  Abstraction  Encapsulation  Modularity  Hierarchy Separate components into external and internal aspects Construct a system from components and packages Ranking or ordering of objects Principles of software engineering Determine the relevant properties and features while ignoring nonessential details

20 Object-oriented design  Purpose Promote thinking about software in a way that models the way we think and interact with the physical word  Including specialization  Object Properties or attributes Behaviors

21 Programming  Problem solving through the use of a computer system  Maxim You cannot make a computer do something if you do not know how to do it yourself

22 Problem Solving Process  What is it? Analysis Design Implementation Testing

23 Problem Solving Process  What is it? Analysis Design Implementation Testing Determine the inputs, outputs, and other components of the problem Description should be sufficiently specific to allow you to solve the problem

24 Problem Solving Process  What is it? Analysis Design Implementation Testing Describe the components and associated processes for solving the problem Straightforward and flexible Method – process Object – component and associated methods

25 Problem Solving Process  What is it? Analysis Design Implementation Testing Develop solutions for the components and use those components to produce an overall solution Straightforward and flexible

26 Problem Solving Process  What is it? Analysis Design Implementation Testing Test the components individually and collectively

27 Problem Solving Process

28 Tips  Find out as much as you can  Reuse what has been done before  Expect future reuse  Break complex problems into subproblems

29 Tips  Find out as much as you can  Reuse what has been done before  Expect future reuse  Break complex problems into subproblems Find out what is known about the problem Talk to the presenter Determine what attempts have succeeded and what attempts have failed Research can require significant time and generate questions The effort is worthwhile because the result is a better understanding True understanding of the problem makes it easier to solve Consider Sketching a solution and then repeatedly refine its components until the entire process is specified

30 Tips  Find out as much as you can  Reuse what has been done before  Expect future reuse  Break complex problems into subproblems Your time is valuable Correctness is probably even more valuable Use existing infrastructure that is known to work Be open to indirect use of existing materials

31 Tips  Find out as much as you can  Reuse what has been done before  Expect future reuse  Break complex problems into subproblems Make as few assumptions as necessary Maximizes the likelihood that your effort can be used in future situations

32 Tips Divide-and-conquer Solve subproblems and combine into an overall solution  Find out as much as you can  Reuse what has been done before  Expect future reuse  Break complex problems into subproblems

33 Have a great holiday break!