ICS 46 Spring 2022
Project #2: Time Waits for No One

Due date and time: Wednesday, April 27, 11:59pm


Introduction

In business or scientific contexts, it's sometimes very costly to make changes to the way that you're doing things, yet sometimes the changes you consider might yield great benefits. Unfortunately, you don't always know if they'll yield those benefits without some experimentation. But if the experimentation is too costly, you might never be willing to pay the cost of finding out whether the changes you're considering are worthwhile or not.

Computers have a role to play in situations like this. If you can write a simulation that models reality well enough that it can demonstrate how things would turn out in various scenarios, you might be able to more cheaply find the answer you're looking for — should I make this change or not? — and, if it turns out to be a positive one, you can proceed.

In this project, we'll write a simulation like this one. Suppose that a chain of big-box retail stores is considering a rearrangement of the way that customers go through the check-out process, in hopes of processing customers more efficiently, helping them spend less time waiting in line, and keeping their business from being lost to more efficient competitors. To aid in that analysis, you'll build a program that will simulate two different arrangements of lines and registers, generating a log of the movement of customers throughout the simulation and, at the end, overall statistics.

Along the way, you'll implement a doubly-linked list with head and tail pointers, then use it as the basis for a queue, which you'll then use in your simulation. This will give you additional practice with the kind of thinking and techniques you need to implement data structures, while also building your experience with some new areas of C++ that you may not have used a lot previously, such as templates, public and private inheritance, and move semantics.


Getting started

Before you begin work on this project, there are a couple of chores you'll need to complete on your ICS 46 VM to get it set up to proceed.

Refreshing your ICS 46 VM environment

Even if you previously downloaded your ICS 46 VM, you will probably need to refresh its environment before proceeding with this project. Log into your VM and issue the command ics46 version to see what version of the ICS 46 environment you currently have stored on your VM. Note, in particular, the timestamp; if you see a version with a timestamp older than the one listed below, you'll want to refresh your environment by running the command ics46 refresh to download the latest one before you proceed with this project.

2022-04-15 15:02:06
Project 2 template added

If you're unable to get outgoing network access to work on the ICS 46 VM — something that afflicts a handful of students each quarter — then the ics46 refresh command won't work, but an alternative approach is to download the latest environment from the link below, then to upload the file on to your ICS 46 VM using SCP. (See the Project #0 write-up for more details on using SCP.) Once the file is on your VM, you can run the command ics46 refresh_local NAME_OF_ENVIRONMENT_FILE, replacing NAME_OF_ENVIRONMENT_FILE with the name of the file you uploaded; note that you'd need to be in the same directory where the file is when you run the command.

Creating your project directory on your ICS 46 VM

A project template has been created specifically for this project, containing a similar structure to the basic template you saw in Project #0, but including a starting point that you must use. So you'll absolutely need to use the project2 template for this project, as opposed to the basic one.

Decide on a name for your project directory, then issue the command ics46 start YOUR_CHOSEN_PROJECT_NAME project2 to create your new project directory using the project2 template. (For example, if you wanted to call your project directory proj2, you would issue the command ics46 start proj2 project2 to create it.) Now you're ready to proceed!


The first step: Implementing the necessary data structures

Your first step is to implement the necessary data structures to support your application. Since we're building a simulation that's fundamentally centered around people standing in line, a queue implementation is what we need here. This part will be tested and graded separately — and you can obtain a substantial proportion of the correctness score for this project for submitting just this part, even if you don't build the application around it. But the implementation will need to be painstakingly complete and correct; we'll be doing the kind of testing we did in Project #0 when we grade it.

In the core directory within your project directory, you'll find two files that you'll be most interested in:

In the gtest directory, you'll find a collection of sanity-checking unit tests for both Queue and DoublyLinkedList, which demonstrates how each of the member functions are expected to behave and interact with one another. The depth of the testing is fairly light — while the sanity-checking tests touch all of the basic functionality, there are a lot of interesting cases missing, so you'll want to be sure that you write your own DoublyLinkedList tests, as well. Note, too, that your best bet is not to change any of the sanity-checking unit tests — other than perhaps commenting some of them out and then bringing them back later, if you need to run some of them in the absence of the others — because they're a fundamental way to demonstrate that your implementation will compile against our unit tests, so we'll be able to test it.

For this part, any code you write needs to be in the core directory. There's a good chance you won't be making changes to any files except DoublyLinkedList.hpp, but even if you choose to add files, you would add them in the core directory. Avoid the temptation to create a DoublyLinkedList.cpp, though; templates are generally written entirely in header files. (See the Templates notes if you need a refresher on why.)

Features of your DoublyLinkedList class template

Your DoublyLinkedList class template must implement all of the public member functions that have been declared within it already, which include all of the following:

Of course, partial credit is available for a partial implementation, though some features are going to be more fundamental than others. For example, if we can't construct a list, there's not much else we can do to test it; if the only thing missing is the move constructors or the iterators, there's still a lot we can test. Of paramount importance is that our unit tests can compile. Be sure your code compiles against all of the sanity-checking unit tests, even if they don't all pass; it we can't compile our tests, we can't run them, and we're not going to be willing or able to spend time debugging your code to make them compile.

Limitations

When you work on Queue and DoublyLinkedList, you are not permitted to use any part of the C++ Standard Library. Do not submit a version of DoublyLinkedList.hpp, Queue.hpp (or any file that they include) that includes any C++ Standard Library headers. (This includes things like adding a print() member function that requires <iostream>. Remove anything like that — including any #include of any standard library header file! — before you submit your work.)

The nodes in your DoublyLinkedList must remain completely private. There should be no part of the public interface that exposes the notion of Node, because the nodes in a linked list are an implementation detail; exposing nodes to code outside of DoublyLinkedList invites code that breaks the list's fundamental assumptions, such as introducing cycles or losing links to nodes and causing memory leaks. This is why the provided version of DoublyLinkedList has its Node struct declared as a private member of DoublyLinkedList, why there are iterators (to provide a way for code outside of DoublyLinkedList to iterate through a list without manually twiddling pointers), and why the iterator classes are also declared within DoublyLinkedList; that way iterators can see the nodes, but no code outside of DoublyLinkedList can.


The second step: Writing the application

In the app directory, you'll write the rest of your code, a program that performs the following simulation. The format of the input and output are described in detail and need to be followed carefully; spelling, capitalization, and spacing are all relevant and must be correct for full credit. Your simulator will read all of its input from std::cin and write all of its output to std::cout. While you may want to use the technique of redirection to use files for this purpose (see below), your simulator will always use std::cin and std::cout.

What are we simulating?

In our hypothetical big-box retail store, customers shop and choose the merchandise they want to buy. Each customer then proceeds to get into a line to wait to be checked out. When there is an available cashier, the customer goes to the register where that cashier is waiting. When the cashier is finished checking the customer out, the customer exits the register and is considered finished.

What we're interested in doing is tracking these movements: when customers enter lines, exit lines and enter registers, and finally exit registers. We'll then report various statistics at the conclusion of the simulation, to summarize the overall outcome.

Arrangements of lines and registers

There are two different arrangements of lines and registers that our simulation will support.

  1. One or more registers, each with its own separate line. A customer in a particular line will only ever proceed to the corresponding register.
  2. One or more registers, with one shared line feeding customers to all of them.

The input

First of all, you may freely assume that the input given to your simulation will match the description below. It may obviously be different than what's shown here, but it will always follow all of the rules here. Your program is free to do anything you'd like — up to and including crashing — in the case that the input is invalid.

The simulator's input begins with what we'll call the setup section, which specifies the parameters that control how the simulation will run. The setup section looks like this — the italiczed portions are included here for descriptive purposes, but are not included in the actual input.

4       the length of the simulation, in minutes
3       the number of registers
3       the maximum line length, beyond which customers be lost
M       S for a single line, M for multiple lines (one for each register)
40      register #1 takes 40 seconds to process a customer
50      register #2 takes 50 seconds to process a customer
30      register #3 takes 30 seconds to process a customer

There are a few notes to be aware of:

After reading the setup section of the input, your simulator will have what it needs to set things up and get started. From there, the rest of the input specifies customer arrivals. Each line in the customer arrival section of the input consists of two numbers: a positive number of customers and the time that these customers arrived. (Time in our simulation is always measured in terms of the number of seconds since the simulation started.) You can assume that the time associated with each line describing an arriving of customers will be greater than the time associated with the previous one.

The input will always end with a line consisting of the word END. That doesn't mean that the simulation should end immediately; it just means that there are no more customer arrivals.

The movement of customers through the simulation

So that we can all agree on the proper output of the simulation, we'll need to agree on the precise details of how customers move through the simulation. In the interest of keeping things simple, we'll take some liberties with reality — customers won't always do the smartest thing, we'll ignore how long it takes for customers to physically move around, and so on. Also, all actions are considered to have happened at discrete times measured in an integer number of seconds since the start of the simulation; something might happen at time 10 or time 11, but never at time 10.5.

The output

The output of your simulator consists of two sections:

Example input and output

A complete example of the simulator's input and expected output (for that input) are provided in the examples directory within your project directory in files called sample.in (the input) and sample.out (the output). Your goal is to match this format precisely; spelling, capitalization, and spacing are all relevant, so take some time to study the example and make sure you recognize the little details within it.

Limitations

You must use your own Queue class template to implement the concept of a line of customers. Beyond that, you are free to use any part of the C++ Standard Library you wish in your simulator, even though it's forbidden in your DoublyLinkedList and Queue implementations. For example, you may prefer to use std::vector to store the registers or the lines (though you can certainly use DoublyLinkedList if you prefer).


What is private inheritance?

The provided Queue class template is quite short, even though it's also quite capable. You won't need to write any code in Queue to make it work completely and correctly. That's because it inherits its implementation from the DoublyLinkedList class template. In general, for any type T, the type Queue<T> inherits from the type DoublyLinkedList<T>. As you would expect, then, Queue objects have all of the member variables and member functions that DoublyLinkedList objects have, which means the entire implementation of DoublyLinkedList is inherently a part of Queue.

It's not entirely crazy that Queue inherits from DoublyLinkedList, because you could certainly say that a queue is a linked list, if that's how you wanted to implement one. A queue is a linked list that provides more limited abilities; it does less than a linked list does, rather than doing more. And, in fact, we'd like to keep it that way. If we have a queue-shaped problem, we probably only want to be able to perform queue-specific operations like enqueue, dequeue, and front, with anything else likely to be a bug in our program, anyway. What we really want is for Queue to inherit from DoublyLinkedList, but for that inheritance relationship to be a secret; only Queue knows about it, so code outside of Queue can't do things like call removeFromEnd or create iterators that can insert elements in the middle somewhere.

In C++, private inheritance is how you achieve this kind of goal. Private inheritance is what it sounds like: It's an inheritance relationship that only the inheriting class knows about. Suppose you start a class declaration in C++ like this:

class Y : private X

What this means is that Y inherits from X, but that the only code in the program that can make use of that relationship is Y. A Y object will have all of the member variables and member functions of X, but they won't be accessible outside of Y. Inside of the Y class, it would be possible to point an X* to a Y object, but this wouldn't be possible outside of the Y class.

Why a feature like this is useful is that it allows a class to inherit an implementation without inheriting an interface. This way, a Queue can be a DoublyLinkedList, but no one else knows it; no one can treat a Queue like a DoublyLinkedList except Queue. So if a Queue member function wants to call addToEnd() or removeFromFront() on the this object, it can do that; but code outside of the Queue class won't be able to do it.

There are two ways to avoid bugs. One is being careful not to do things you shouldn't do. The other is to make it impossible to do the things you shouldn't do. The latter is something to strive for, and static type checking in C++ is a useful tool to help you get there, with private inheritance one of the many techniques available to express the features and constraints in your design.


Iterators

An iterator is an abstraction for a position within a data structure, the goal of which is to allow the values in a data structure to be accessed (and potentially modified) without relying on the details of how the data structure is implemented. Given an iterator, an algorithm can obtain all of the values in the data structure without manipulating pointers, understanding the data structure's layout, or sometimes without even being aware of what kind of data structure it is. When you can separate an algorithm from the details of the data structures it operates on, it becomes possible to write the algorithm generally; linear search is the same algorithm no matter what kind of data structure you're searching, as long as there's a way to say "Give me the next thing I haven't seen" and ask "Is there anything left that I haven't seen?" Iterators provide those kinds of fundamental capabilities.

For more background on this topic, see the section titled Iterators in the Standard Library notes from my ICS 45C course. Our iterators aren't quite the same as the ones in the standard library, but their purpose is the same.

The difference between Iterator and ConstIterator

Our implementation of DoublyLinkedList draws a distinction between Iterators and ConstIterators. That distinction mirrors a similar distinction in the containers in the C++ Standard Library such as std::vector and std::list. For our purposes, the distinction is this:

Note, too, that it's possible to have a const Iterator (i.e., a variable of the type Iterator that is itself marked as const), but this is a different thing altogether. What a const Iterator holds constant is the iterator (i.e., you can't move it), but it makes no promise about the contents of the list. This is similar, in concept, to the way that the const specifier interacts with pointer types, in that const can be used to protect the pointer, the value the pointer points to, or both.

How our iterators are different from the standard ones

The key difference between our iterators and the ones in the C++ Standard Library is our design avoids the need for the deep use of a C++ called feature called operator overloading, in which the meaning of operators is redefined for objects of classes you write; this is not something that's commonly been seen in depth by students coming into ICS 46, even if it's been touched on. Fundamentally, our iterators are pretty similar to the bidirectional iterators in the standard library, with member functions taking the place of the operator overloads, along with some slight differences in semantics. So, if you understand how to use the standard iterators, you'll find using and testing your own iterators to be pretty similar.


Redirection (or, How to avoid re-typing the input every time you run your program)

When you use the run script to execute your program — and, generally, by default in Linux — the standard input and standard output are connected to the shell window where you executed the program. The program's input is typed into that shell window; the program's output is written to that shell window.

However, you can also use a technique called redirection to connect the standard input and/or standard output to other devices — most importantly for us, to files! — instead of the default. For example, the contents of an existing file may be redirected into the standard input, so that your program will read its input from the file instead of from the shell window; similarly, the standard output can be redirected into a file, meaning that all of the output printed to std::cout will be saved into that file, rather than being displayed in the shell window.

The typical mechanism for redirection is to use the < and > operators on the command line, like this:

SomeProgramYouWantToRun <FileContainingStdInput.txt >FileToStoreStdOutput.txt

You don't have to use both; you can use only < (in which case the standard input is read from a file, but the standard output is written to the shell window) or only > (in which case the standard input is read from the shell window, but the standard output is written to a file). It's up to you.

Using redirection to avoid re-typing test input

This can be a handy technique to use in your testing, to avoid the problem of having to re-type the program's input every time you run it. If you used the project2 project template — and you should have! — when creating your project, you should see a directory called examples in your project directory; in the examples directory, you should see a file sample.in, which contains the sample input from this project write-up. If you want to run your program using the same input, issue this command (from your project directory):

./run <examples/sample.in

The effect is that the contents of the sample.in file in the examples directory will be redirected into your program's standard input, in lieu of you having to type it. You might also want to write other test files for yourself in that same examples directory, then use a similar technique to redirect them into the standard input of your program. You can avoid a lot of re-typing this way!

Similarly, you can use redirection to send the output of your program to a file.

./run <examples/sample.in >my.out

That would create a file called my.out in your project directory containing the output of your program. You could then compare it to the example output using the diff command, which is a handy way to quickly see if there are any differences.

diff my.out examples/sample.out

Deliverables

After using the gather script in your project directory to gather up your C++ source and header files into a single project2.tar.gz file, then submit that file (and only that file!) to Canvas.

Understand that we will only accept projects submitted to the appropriate dropbox (for the appropriate assignment) on Canvas; we do not accept printed copies of your projects, nor do we accept them via email or other means under any circumstances.

You are responsible for submitting the version of your project that you want graded. We will grade the most recent submission made before the deadline. Accidentally submitting the wrong version, nor is there any remedy (outside of the late policy described above) for forgetting to submit your work at all.

Can I submit after the deadline?

Yes, it is possible, subject to the late work policy for this course, which is described in the section titled Late work at this link.

What do I do if Canvas slightly adjusts my filename?

Canvas will sometimes modify your filenames when you submit them (e.g., when you submit the same file twice, it will change the name of your second submission to end in -1.tar.gz instead of just .tar.gz). In general, this is fine; as long as the file you submitted has the correct name, we'll be able to obtain it with that same name, even if Canvas adjusts it.