This section will document any updates applied to the project since original release:

• revision #: <description> (DATESTRING)

In this project, resume our conceptual journey and explore another data structure: queues.

A queue is considered one of the most important data structures, along with stack (last week's project), trees, and hash tables. And it is largely because of how often we find them playing out in nature or in our day-to-day lives.

The word “queue” is defined as:

• (generically): a line or sequence of items awaiting their turn to be attended to or to proceed
• (computing): a list of data items, commands, etc., stored so as to be retrievable in a definite order, usually the order of insertion

So, how does all this list and node stuff play into our queue implementation?

Well, like stacks, we're going to build the queue ON TOP OF lists (which are composed of nodes).

Therefore, a queue is a data structure that stores its data in a list (which consists of nodes), and we apply various rules/restrictions on our access of that list data.

The concept of restricting access is a very important one- which we did with our list as well (limiting our access to the list through the use of append(), insert(), and obtain() versus manipulating the there/back pointers manually all the time). By limiting how we access the data, we give ourselves certain algorithmic advantages:

• error reduction: if have a small set of operations that can do one thing, and do their one thing extremely well (insert(), append(), and obtain() again, for instance), we can then rely on them to do the low-level grunt work, freeing us up to accomplish higher level tasks (such as sorting or swapping), or even things like determining if a word is a palindrome, or just preserving order of items during storage.
• performance: by restricting our available choices, the edge cases we have to check for are reduced, and in ideal situations, the average case moves closer to the best case.

It is common to think of a queue as a horizontal object, much like a line of people that need to be services (such as a checkout line at the grocery store, or a line at the bank).

Although we've commonly viewed lists horizontally (from left to right), there is absolutely nothing requiring this positional orientation.

Similarly, queues possess no mandatory orientation, but we do usually visualize them as horizontal entities, largely because that's how we commonly find ourselves entangled in this data structure in nature.

The queue data structure presents certain advantages that encourages its use in solving problems (why is the notion of forming lines important? What problems does that solve? How are resources more efficiently utilized by this act?), and we accomplish that by its compositional definition:

• a queue has a back and a front, basically node pointers that constantly point to the back and front node in the queue (equivalent to the underlying list's closing and initial pointers, respectively).
• to put an item on the queue, we enqueue it (place it at the back of the queue). So one of the functions we'll be implementing is enqueue(), which will take the node we wish to place on the given queue, and enqueue will handle all the necessary coordination with its underlying list.
• to get an item off of the queue, we dequeue it. In our dequeue() function, we grab the front node off the queue (this also translates into a set of list-level transactions that our dequeue() function will handle for us).

These qualities cause the queue to be described as a FIFO (or LILO) structure:

• FIFO: First In First Out
• LILO: Last In Last Out

And that describes what is conceptually going on– if we can ONLY put our data on at one end (the back), and grab our data from the other (the front), the data most immediately available to us is that which we placed there first (hence the first one we enqueued would be the first one we get back when we dequeue it).

This concept is very important, and being aware of it can be of significant strategic importance when going about solving problems (and seeing its pattern proliferate in nature).

With that said, the existence of front, back, along with the core enqueue() and dequeue() functions defines the minimal necessary requirements to interface with a queue. Sometimes we'll see additional actions sneak in. While these may be commonly associated with queue, they should not be confused as core requirements of a queue:

• purge: a way to quickly empty out a queue (evacuate its contents– note this is partially similar in nature to what our rmqueue() function will do; only we won't take it the extra step of de-allocating and NULLifying the queue pointer).
  • this will be similar in nature to the list's empty() function, which properly clears a list to an empty state; only, purge() is operating at the queue level.

While we may be implementing these supplemental functions, it should be noted that not only are they in no way necessary for using a queue, they could be detrimental, as one could rely on them as a crutch.

Their inclusion should ONLY be viewed as a means of convenience (in certain scenarios they may result in less code needing to be written), but NOT as something you should routinely make use of.

With a queue, there sometimes exists a need to cap its total size (especially in applications on the computer, we may have only allocated a fixed amount of space and cannot exceed it). For this reason, we will need to maintain a count of nodes in the queue (ie the underlying list). For this reason, we continue to make use of the list's qty element.

Additionally, the queue will have a configured maximum buffer- if the quantity of nodes in the list exceeds the configured buffer of the queue, we should prevent any additional enqueues.

It should also be pointed out that in other applications, a queue need not have a maximum buffer size.. in which case it can theoretically grow an indefinite amount. We will explore both conditions (unbounded and bounded) in this project.

There are two very important operational error conditions a queue can experience:

• buffer overrun: this is the situation where the quantity of the list is equal to the configured queue buffer, and we try to enqueue another node onto the queue.
• buffer underrun: this is the situation where the queue is empty, yet we still try to dequeue a value from it.

For this project, we're going to be implementing the queue data structure atop of our recently re-implemented linked list (the doubly linked list).

Building on the data.h header file introduced in dls0, a section of status codes has been added for queues:

//////////////////////////////////////////////////////////////////////
//
// Status codes for the doubly linked queue implementation
//
#define  DLQ_SUCCESS         0x0000000100000000
#define  DLQ_CREATE_FAIL     0x0000000200000000
#define  DLQ_NULL            0x0000000400000000
#define  DLQ_EMPTY           0x0000000800000000        
#define  DLQ_OVERRUN         0x0000001000000000        
#define  DLQ_UNDERRUN        0x0000002000000000        
#define  DLQ_ERROR           0x0000004000000000
#define  DLQ_INVALID         0x0000008000000000
#define  DLQ_DEFAULT_FAIL    0x0000000000808000

1

#ifndef _QUEUE_H
#define _QUEUE_H
 
//////////////////////////////////////////////////////////////////////
//
// Queue relies on list (which relies on node) to work.
//
#include "list.h"
 
//////////////////////////////////////////////////////////////////////
//
// Define the queue struct
//
struct queue {
    Node *front;                       // pointer to front of queue
    Node *back;                        // pointer to back of queue
    List *data;                        // pointer to queue data
    ulli  buffer;                      // queue length (0- unbounded)
};
 
code_t    mkqueue(Queue **, ulli    ); // create new queue (of length)
code_t    cpqueue(Queue  *, Queue **); // create a copy of a queue
code_t    rmqueue(Queue **          ); // de-allocate a queue
 
code_t    purge  (Queue **          ); // clear an existing queue
 
code_t    enqueue(Queue **, Node  * ); // add node to back of queue
code_t    dequeue(Queue **, Node ** ); // grab node at front of queue
 
#endif

For our queue implementation, we will continue to utilize the double pointer, in order to practice passing parameters by address.

This is necessary so that we can free up the return value of enqueue() and dequeue() to be used for status codes (ie look out for buffer overruns and underruns).

Also, while nothing is stopping you from doing so, the idea here is that things like buffer and the underlying list qty in queue transactions will NOT be accessed outside of the enqueue() and dequeue() functions. Just like my warnings about using qty in your list solutions (save for display() when showing position values in a backwards orientation)– do not consider buffer as a variable for your general use.

In object-oriented programming, both buffer and qty would be private member variables of their respective classes, unable to be used by anything other than their respective member functions.

In src/queue/, you will find skeletons of the above prototyped functions, hollowed out in anticipation of being made operational.

Figure out what is going on, the connections, and make sure you understand it.

Again, your queue is to utilize the list for its underlying data storage operations. This is what the queue's data list pointer is to be used for.

In unit/queue/, you will find these files:

• unit-mkqueue.c - unit test for mkqueue() library function
• unit-enqueue.c - unit test for enqueue() library function
• unit-dequeue.c - unit test for dequeue() library function
• unit-cpqueue.c - unit test for cpqueue() library function
• unit-rmqueue.c - unit test for rmqueue() library function
• unit-purge.c - unit test for purge() library function

There are also corresponding verify-FUNCTION.sh scripts that will output a “MATCH”/“MISMATCH” to confirm overall conformance with the pertinent queue functionality.

These are complete runnable programs (when compiled, and linked against the queue library, which is all handled for you by the Makefile system in place).

Of particular importance, I want you to take a close look at:

• the source code to each of these unit tests
  • the purpose of these programs is to validate the correct functionality of the respective library functions
  • follow the logic
  • make sure you understand what is going on
  • ask questions to get clarification!
• the output from these programs once compiled and ran
  • analyze the output
  • make sure you understand what is going on
  • ask questions to get clarification!

To assist you in verifying a correct implementation, a fully working implementation of the queue library should resemble the following (when running the respective verify script):

Here is what you should get for queue:

lab46:~/src/data/dlq0$ make check
======================================================
=    Verifying Doubly-Linked Queue Functionality     =
======================================================
   [mkqueue] Total:   6, Matches:   6, Mismatches:   0
   [enqueue] Total:  18, Matches:  18, Mismatches:   0
   [dequeue] Total:  19, Matches:  19, Mismatches:   0
   [cpqueue] Total:  17, Matches:  17, Mismatches:   0
     [purge] Total:   7, Matches:   7, Mismatches:   0
   [rmqueue] Total:  10, Matches:  10, Mismatches:   0
======================================================
   [RESULTS] Total:  77, Matches:  77, Mismatches:   0
======================================================
lab46:~/src/data/dlq0$