One of the most important steps toward writing good code is writing good test cases. In DrScheme, you should
check-expect for testing.
check-expect takes two expressions as input and verifies
that their values are the same.
(check-expect (+ 1 1) 2)
would result in a successful test, while
(check-expect (+ 1 1) 0) would not. If all your tests pass, DrScheme will happily tell you so. When a test fails, a window will appear
describing the result.
For example, if you wrote the following function to calculate the absolute value of a number,
(define (absolute x) (if (< x 0) (* x -1) x))it would be important to verify that it works correct on both positive and negative numbers. It's also important to test the "edge cases" (like 0 for this function). These are where errors are most likely to be made.
(check-expect (absolute 2) 2) (check-expect (absolute -5) 5) (check-expect (absolute 0) 0)
You must completely test every function you write for CS19. We will grade you on the quality of your test cases.
There are three basic operators for building lists: cons, list, and append (concatenation). Their contracts are as follows:
For each of the following expressions, try to predict (a) what they will return and (b) what the length of the resulting list is, then check your answers in DrScheme:
(cons empty empty)
(list empty empty)
(append empty empty)
(cons (list 1 2 3) (list 4 5))
(list (list 1 2 3) (list 4 5))
(append (list 1 2 3) (list 4 5))
Computer scientists and computer engineers frequently describe systems as finite-state machines (also called finite-state automata). The best way to understand a finite-state machine is through an example.
Imagine that you want to show how a soda/vending machine behaves. To keep the example small, we'll assume that a soda costs 25 cents and that the machine accepts nickels and dimes. The machine will not give change. The following figure shows the state machine:
The circles are called states. Each state corresponds to an amount of money that has been deposited into the machine. The state corresponding to the amount of money deposited at any time is called the current state. The bold arrow marks the state to use as the first current state. In this case, the machine starts with no money.
The arrows between states are called transitions. Transitions show what actions have to happen for the machine to go from one state to another. For example, if the machine currently has 5 cents and a nickel is deposited, then the machine has 10 cents. The labels on each state (here, nickel and dime) are the "actions" that the machine can react to.
The soda machine is a trivial example. In reality, state machines are used to capture all sorts of systems, many with more than 2 to the power of 500 states.
If we give a name to each state, we can represent a state machine as a list of transition structures. A transition structure consists of three pieces of information: the name of the states on either end of the arrow and the label on the arrow.
; transition : string string string (define-struct transition (source label target)) ; We create transitions with the make-transition function ; For example, (make-transition "5-cents" "nickel" "10-cents")
You are going to write a series of programs to work with state
machines. Copy the definition of the
transition struct into
the DrScheme definitions window before you start. Make sure to have a
TA check your work when you're done.
Write the list of transitions for the soda machine example
showed above. Define it as a constant called
Write a function
get-next-state that consumes the
name of a state, an action, and a list of transitions and produces the
name of a state. The produced state should be the target state of a
transition with the input source state name and action. For
(get-next-state "10-cents" "dime" soda-machine)
Write a function
get-state-sequence that consumes
the name of a state, a list of actions, and a list of transitions and
produces a list of state names. The produced list should show the
sequence of states visited while processing the list of actions (in
order), starting from the given state. For example,
(get-state-sequence "0-cents" (list "nickel" "dime" "nickel") soda-machine)
(list "0-cents" "5-cents" "15-cents" "20-cents")
Write a function
gets-soda? that consumes a list
of actions and produces a boolean indicating whether that sequence of
actions visits the "soda" state.
If our state machine definition includes multiple transitions with the
same source state and action but different target states, it will be unclear
which state to enter next. To check for these ambiguities, write a function
ambiguous-states that consumes a list
of transitions and produces a list of names of source states that have
multiple target states for the same action. State
machines with ambiguity, or nondeterministic finite-state machines, are a
central part of the theory of computation; if you're curious, you can read more
This definition of state machines relies on matching state
names to hook up the transitions. If you made a typo when entering a
state name (say "5-cts" instead of "5-cents"), you would create a
machine in which there is no transition out of some state. Programs
can help check whether such errors exist in a list of transitions.
Write a function
dead-end-states that consumes a list
of transitions and produces a list of names of target states out of
which there are no other transitions.
It would seem that the problems with typos in the previous problem would go away if we made a structure for each state (containing its name and outgoing transitions), then put the state structure instead of the state name as the "target" of each transition. Why didn't we set the problem up this way? Consider what you would need to do this that you haven't learned in Scheme yet and argue why it is technically necessary.