Lecture 1:
Engineering
Software,
Constructing
Poetry and
Dancing about
Architecture
CS201j: Engineering Software?
University of Virginia
David Evans
Computer Science
http://www.cs.virginia.edu/~evans
Menu
• What is Engineering?
– Can we engineer software?
• Small, Fun Programs vs. Big, Important
Programs
• Managing Complexity
• Course Mechanics
• PS1, Java Introduction
29 August 2002
CS 201j Fall 2002
2
What is
Engineering?
29 August 2002
CS 201j Fall 2002
3
Webster’s Definitions
en·gi·neer·ing ( n j -nîr ng) n.
1a. The application of scientific and mathematical
principles to practical ends such as the design,
manufacture, and operation of efficient and
economical structures, machines, processes,
and systems.
b. The profession of or the work performed by
an engineer.
2. Skillful maneuvering or direction: geopolitical
engineering; social engineering.
29 August 2002
CS 201j Fall 2002
4
Design Under Constraint
“Engineering is design under
constraint… Engineering is synthetic
- it strives to create what can be, but it
is constrained by nature, by cost, by
concerns of safety, reliability,
environmental impact,
manufacturability, maintainability and
many other such 'ilities.' ...”
William Wulf
29 August 2002
CS 201j Fall 2002
5
Computing Power 1969-2002
(in Apollo Control Computer Units)
4500000
4000000
Moore’s Law: computing power
doubles every 18 months!
3500000
3000000
2500000
2000000
1500000
1000000
500000
2002
2001
1999
1998
1996
1995
1993
1992
1990
1989
1987
1986
1984
1983
1981
1980
1978
1977
1975
1974
1972
1971
1969
0
Constraints Software Engineers Face
• Not like those for “real” engineers:
– Cost, weight, physics, etc.
– Lab machines have ~ 1 million times what
was needed to get to the Moon
• Complexity of what we can understand
• Most important constraint is cost of
human effort to get reliability, safety,
maintainability
29 August 2002
CS 201j Fall 2002
7
How is engineering software
different from engineering
bridges?
29 August 2002
CS 201j Fall 2002
8
Bridges
• Continuous
Software
• Discrete
– Calculus
– Testing/analysis is
easy: if the bridge
holds for 1M kg, it also
probably holds
0.99Mkg
29 August 2002
– Logic, Discrete
Mathematics
– Testing/analysis is
difficult
CS 201j Fall 2002
9
Bridges
• Made of physical stuff
– Some costs are
obvious
– Changes after
construction are hard
Software
• Made of virtual stuff
– All costs are nonobvious
– Changes should be
easy (but they’re not)
for (int i = 0; i < rows; i++) {
for (int j = 0; j < columns; j++) {
nextStates [i][j] =
getCellAt (i, j).getNextState ();
}
}
29 August 2002
CS 201j Fall 2002
10
Bridges
• Obvious when it falls
down
– Bridge makers get
sued
– Architects need
licenses
29 August 2002
Software
• Falls down quietly
(usually)
– Software vendors
blame user, charge for
upgrades
– Anyone can make
software
CS 201j Fall 2002
11
Bridges
• Requirements are
(usually) obvious and
easy to describe
• A good design is
apparent to everyone
immediately
29 August 2002
Software
• Requirements are
mysterious and hard
to describe
• A good design is only
apparent to “experts”
but has impact later
on
CS 201j Fall 2002
12
Small, Fun Programs
vs.
Big, Important Programs
29 August 2002
CS 201j Fall 2002
13
Small, Fun
Programs
Big, Important
Programs
• CS101, CS200, etc.
• Happy if it works once
• Simulated in CS201j
• Must work on all
possible inputs
– Test by running once
• If it doesn’t work on
some input, no big
deal
29 August 2002
– Need validation
strategies
• If it doesn’t work on
some input millions
are lost, people die
CS 201j Fall 2002
14
Small, Fun
Programs
Big, Important
Programs
• Written by a few
people over a short
period of time
– Manage complexity
mostly by memory
• Used by a few people
over a short period of
time
29 August 2002
• Written by many
people over many
years
– Can’t rely on memory
to manage complexity
• Used by many people
over many years
– Needs to be
maintained as
requirements change
CS 201j Fall 2002
15
How Big are Big Programs?
• Largest program in CS200/CS101:
– ~500 lines
• F-22 Steath Fighter Avionics Software
– 1.5M lines of code
• 5EEE (phone switching software)
– 18M lines
• Windows XP
– ~50M lines
29 August 2002
CS 201j Fall 2002
16
How can we manage
Complexity?
29 August 2002
CS 201j Fall 2002
17
Modularity
• Divide complex systems into many
components
• Develop components independently
• Assemble them to solve the problem
29 August 2002
CS 201j Fall 2002
18
Abstraction and Specification
• Ignore details
• Separate what from how
• Need a specification – description of what
a component should do
• Components can be built based on what
they should do, not how they should do it
29 August 2002
CS 201j Fall 2002
19
How can we make systems
dependable?
29 August 2002
CS 201j Fall 2002
20
Analysis
• Use reasoning and tools to check a design
is sound
• Use reasoning and tools to check an
implementation is sound
• Test systematically
29 August 2002
CS 201j Fall 2002
21
Redundancy
• Express things in more than one way and
check they are consistent
• Extreme example:
– Space Shuttle
• 5 on-board computers
– 4 duplicates running same software
– 1 running completely separate implementation (to same
specifications)
• Common example: variable declarations
29 August 2002
CS 201j Fall 2002
22
Design
There are two ways of constructing a
software design. One way is to make it so
simple that there are obviously no
deficiencies. And the other way is to make
it so complicated that there are no obvious
deficiencies.
Tony Hoare
29 August 2002
CS 201j Fall 2002
23
Course Overview
• This course is about constructing
dependable software systems
– Managing complexity: modularity, abstraction,
specification
– Achieving dependability: analysis, redundancy
• Good design is key
– How to divide problems into modules
– How to hide details
29 August 2002
CS 201j Fall 2002
24
Course Mechanics
29 August 2002
CS 201j Fall 2002
25
Staff
• Coach: David Evans
– Joined UVA in Nov 1999
– Call me “Dave” or “Coach”
– Research areas: security, programming swarms
• Assistant Coaches
– Sol Chea
– Serge Egelman
– Tiffany Nichols
– Mike Peck
29 August 2002
CS 201j Fall 2002
26
Help Available
• Me
– Office Hours: Wednesdays 2:30-3:30pm
– Always available by email, if I don’t reply in 24 hours,
send again and complain
• TAs
– Will post staffed lab hours
• Web site: http://www.cs.virginia.edu/cs201j
– Everything goes on the web
• But mainly: your classmates
29 August 2002
CS 201j Fall 2002
27
CS201J
• Experimental Course
– National Science Foundation sponsorship
– Focus on using lightweight analysis tools
• First time offered
– I will probably make lots of mistakes
– But…you get to take it in a small class
• Counts as CS201, but doesn’t cover
everything in CS201
29 August 2002
CS 201j Fall 2002
28
Honor Code
• Classroom Pledge is Horrible!
• The whole point of being at a University is
so you can:
– Learn from your classmates
– Learn better by teaching your classmates
• Sign and return the CS201j Pledge on
Friday
29 August 2002
CS 201j Fall 2002
29
Java
Warning: will quickly introduce lots of new concepts – we
will spend a lot more time on many of these later.
29 August 2002
CS 201j Fall 2002
30
Java
• Syntax: a lot like C++ (designed to be
easy for C and C++ programmers to learn)
• Semantics (what programs mean): a lot
like Scheme
• This class does not focus on details of
Java language
29 August 2002
CS 201j Fall 2002
31
Programming Systems
C++ Program
Scheme Program
C++ Compiler
Object Files
Scheme Interpreter
Machine
29 August 2002
CS 201j Fall 2002
32
Java VM
Java Program
Why use a virtual machine?
• Portability
Java Compiler
Class Files
Java Virtual Machine
– If you can implement a Java
VM on your machine, then you
can run all Java programs
• Security
– A VM can limit what programs
can do to the real machine
• Simplicity
Machine
29 August 2002
– VM instructions can be simpler
than machine instructions
CS 201j Fall 2002
33
Programming in Java
• Program is divided into classes
• A class:
– Defines a new datatype
– Defines methods and state associated with
that datatype
• We call a value of a class datatype an
object
29 August 2002
CS 201j Fall 2002
34
Problem Set 1
• Lots of new concepts, but only a few lines
of code
• Implement a class that simulates
Conway’s Game of Life:
– If a cell is alive and it has 2 or 3 live
neighbors, it stays alive
– Otherwise it dies (overcrowding or isolation)
– If dead cell has exactly 3 live neighbors, it
becomes alive
What abstractions should we use?
29 August 2002
CS 201j Fall 2002
35
Game of Life Abstractions
• Grid of cells
• Cell
– Keeps track of its state
– Methods to calculate its next state
• But, this depends on states of its neighbors
• State of a cell
– Dead or alive
29 August 2002
CS 201j Fall 2002
36
Example Class
public class Cell {
// OVERVIEW: A Cell is an object that
//
represents a cellular automaton.
//
A cell has a current state and
//
location, and a method for
//
determining its next state.
private CellState state;
…
29 August 2002
CS 201j Fall 2002
37
Some Cell Methods
boolean isAlive()
// EFFECTS: Returns true if the cell is
//
alive, false otherwise.
{ return state.isAlive(); }
public CellState getNextState ()
// EFFECTS: Returns next state value for
// this.
{ return state; }
29 August 2002
CS 201j Fall 2002
38
Objects
local variable
Cell c1 = new Cell ();
abstract Cell object
c1
Cell object
instance variable
state:
CellState object
29 August 2002
CS 201j Fall 2002
39
Method Calls
<object>.<method> (<parameters>)
c1
.getNextState ()
abstract Cell object
local
variable
c1
this
Evaluate c1 to obtain the object it refers to.
Set this to point to that object
public CellState getNextState ()
Evaluate the body of the method
// EFFECTS: Returns next state value for
// this.
{ return this.state; }
29 August 2002
CS 201j Fall 2002
(this is optional here)
40
Inheritance
We can create a new class that inherits
methods and state from another class:
public class ExtremeLifeCell extends Cell {
…
}
29 August 2002
CS 201j Fall 2002
41
Overriding
In the new class, we can replace
implementations of methods:
public CellState getNextState ()
// EFFECTS: Returns the next state for this cell.
// The next state will be alive if this cell or any of its neighbors
// is currently alive.
{
if (countAliveNeighbors () > 0) {
return CellState.createAlive ();
} else {
return getState ();
}
}
29 August 2002
CS 201j Fall 2002
42
Dynamic Dispatch
Cell c;
…
c.getNextState ();
c could be any subtype of Cell
If c is an ConwayLifeCell, then the ConwayLifeCell
getNextState method is called
29 August 2002
CS 201j Fall 2002
43
PS1
• Create a ConwayLifeCell class that is a
subtype of the Cell class
• Override the getNextState method to
implement the Game of Life rules
• Because of dynamic dispatch, when you
run the simulator with your new class, it
will call your getNextState method
29 August 2002
CS 201j Fall 2002
44
Classes, Objects, Dispatch
• Lots of complicate issues to deal with:
– When is it safe to override a method?
– How do we hide implementation details?
– When should we use inheritance?
• We will address these later in the course
29 August 2002
CS 201j Fall 2002
45
Charge
• This class is about:
– Managing complexity: modularity, abstraction,
specification
– Engineering dependability: analysis,
redundancy, design
• Before 5pm Friday:
– Email registration survey
• Before class Tuesday:
– Read and sign CS 201j Pledge
Remember to take pictures!
– Problem Set 1 Due
29 August 2002
CS 201j Fall 2002
46