Posted by Leniel Macaferi on 5/20/2008 07:03:00 PM

This post is related to one of the best coursework I've done during the computer engineering course. I'm really proud of it. It was the cornerstone in my programming career and helped me choose an area to put my efforts from that moment on. I was in the 5th term out of 10 (3rd year of the course out of 5 more exactly). The discipline was Programming Languages.

This subject is fantastic and is used extensively throughout the the computer science field.

First I'll give a short description about the Quicksort and Binary Search algorithms and then I'll present the work that I and my dear brother in faith Wellington Magalhães Leite did.

Quicksort

Quicksort is a well-known sorting algorithm developed by C. A. R. Hoare. Typically, quicksort is significantly faster in practice than other sorting algorithms, because its inner loop can be efficiently implemented on most architectures.

Binary Search

A binary search algorithm (or binary chop) is a technique for finding a particular value in a sorted list. It makes progressively better guesses, and closes in on the sought value by selecting the median element in a list, comparing its value to the target value, and determining if the selected value is greater than, less than, or equal to the target value. A guess that turns out to be too high becomes the new top of the list, and a guess that is too low becomes the new bottom of the list. Pursuing this strategy iteratively, it narrows the search by a factor of two each time, and finds the target value.

Our paper

Our paper is entitled Quicksort and Binary Search Algorithms. You can get a copy at the end of this post.

Without more ado, see its abstract bellow:

Sorting and searching algorithms are a core part of the computer science area. They are used throughout the programming work when you need to sort a set of data and when you need to search for a specific record (key) present in such set of data.

Quicksort is one of the fastest (quick) sorting algorithms and is most used in huge sets of data. It performs really well in such situations.

Binary search tree is one of the fastest searching algorithms and is applied in a sorted set of data. It reduces the search space by 2 in each iteration, hence its name (binary).

In this paper we present the intrinsic nature of each algorithm as well as a functional implementation of such algorithms in the C++ programming language.

Keywords: quicksort, binary search, sorting algorithms, searching algorithms, c++ programming language

CONTENTS
1 INTRODUCTION 6
  1.1 Objective 6
  1.2 Definition 6
      1.2.1 Sorting algorithms 6
      1.2.2 Searching algorithms 7
2 DEVELOPMENT 8
  2.1 Quicksort algorithm (swapping and partitioning) 8
      2.1.1 Detailed steps 8
  2.2 Binary search algorithm 9
  2.3 Studying the efficiency of the methods 9
      2.3.1 The big O notation 9
      2.3.2 Quicksort efficiency 10
            2.3.2.1 The best and the worst case 10
            2.3.2.2 Comparison with other sorting algorithms 11
      2.3.3 Binary search efficiency 11
3 APPLICATION 12
  3.1 Quicksort implementation 12
  3.2 Binary search implementation 13
4 CONCLUSION 14
5 REFERENCES 15

Words of wisdom

As I mentioned, during the 5th term of the computer engineering course our teacher Marcus Vinicius Carvalho Guelpeli selected some sorting and searching algorithms to pass to the class as a coursework.

The coursework should be done in pairs and each pair should select a sorting and searching algorithm to compose a paper about it. We selected the quicksort and the binary search algorithms. The teacher advised us that these weren't the easy ones. I just thought: that's what I want. I don't want the easy ones. Why? Because if you get just the easy problems I'll never understand something that demands a more deep approach and every time a difficult task is given you'll tend to refuse it. What's the best thing to do? Just accept the challenge and go for it. Chances are you'll succeed. That's just what happened with us.

We haven't just written about the quicksort and the binary search, we implemented it and presented it to the class in a power point presentation. The teacher liked it so much that our grade was the highest possible! :-) In the end what did we feel? An amazing feeling. Something such that the work had been done and we learned a lot from it. That's what a college is supposed to do. Give you the subjects and motivate you; teaching the basic so that you can dig up the more difficult aspects of the subject being taught.

So what's next? Well, I'll explain how we implemented the quicksort and the binary search algorithms.

Quicksort and Binary search algorithms implementation in C++

One of the things that I've always listened to was about code reuse. You search for something already implemented so that you just haven't to reinvent the wheel. Of course you'll complement or even adapt the available code to your situation. That was what we did. I found some code for the quick sort at MSDN and implemented the binary search one. Unfortunately the page at MSDN isn't available anymore. It's been three years since I hit that page.

I wanted a way of measuring the time elapsed so that we could compare the efficiency of both methods when they were fed with different input data sets. The input is nothing more than a text file .txt full of numbers in this case. Can be any data you want. Each test case we passed a text file with different random numbers and different quantity of numbers. For example, in a test case we passed a file named 2500.txt, that means 2500 random numbers. In another test case we passed other file named 7500.txt as so on. I think you got it. Doing so we could compare how well the algorithms were performing.

To generate the random numbers we used an Excel spreadsheet with the formula =RAND()*1000000. For each set of data we generated new numbers and copied and pasted those numbers into the text files that are the input for our program. During a coursework as this one we get to learn everywhere, even a new formula in Excel. It's really good. ;-)

Again, I searched for a timing class that I could reuse with the code and for sure I found it. I didn't use it at all but I used it to learn about how to measure time in C++. It's amazing how fast you can implement something. Much of the things you need related to programming are already implemented. You just have to search for it as is what you're doing here, I think! You searched for the subject of this post and here you are seeing something implemented. Try to learn from it and just don't copy the entire work and think that you know about it. It's wrong. Try to understand what the code is doing. Dive into the theory because it explains the inner essence.

The code that follows is well commented which is something every developer should do. You see, it was three years ago when we worked with this code. Today it's difficult to remember every step I took. The comments helped me to remember almost everything.

Bellow I present the quick sort method we borrowed from MSDN (we adapted it to fit our case). Note the use of the Partition method (explained in the accompanying paper):

// QuickSort implementation
void QuickSort(char** szArray, int nLower, int nUpper)
{
 // Check for non-base case
 if(nLower < nUpper)
 {
   // Split and sort partitions
   int nSplit = Partition(szArray, nLower, nUpper);
   QuickSort(szArray, nLower, nSplit - 1);
   QuickSort(szArray, nSplit + 1, nUpper);
 }
}

// QuickSort partition implementation
int Partition (char** szArray, int nLower, int nUpper)
{
 // Pivot with first element
 int nLeft = nLower + 1;
 char* szPivot = szArray[nLower];
 int nRight = nUpper;

 // Partition array elements
 char* szSwap;
 while(nLeft <= nRight)
 {
   // Find item out of place
   while(nLeft <= nRight && strcmp (szArray[nLeft], szPivot) <= 0)
     nLeft = nLeft + 1;
   while (nLeft <= nRight && strcmp (szArray[nRight], szPivot) > 0)
     nRight = nRight - 1;

   // Swap values if necessary
   if(nLeft < nRight)
   {
     szSwap = szArray[nLeft];
     szArray[nLeft] = szArray[nRight];
     szArray[nRight] = szSwap;
     nLeft = nLeft + 1;
     nRight = nRight - 1;
   }
 }

 // Move pivot element
 szSwap = szArray[nLower];
 szArray[nLower] = szArray[nRight];
 szArray[nRight] = szSwap;
 return nRight;
}

Now see the binary search method implementation that we did:

int BinarySearch(char** szArray, char key[], int nLower, int nUpper)
{
 // Termination case
 if(nLower > nUpper)
   return 0;

 int middle = (nLower + nUpper) / 2;

 if(strcmp(szArray[middle], key) == 0)
   return middle;
 else
 {
   if(strcmp(szArray[middle], key) > 0)
     // Search left
     return BinarySearch(szArray, key, nLower, middle - 1);
   // Search right
   return BinarySearch(szArray, key, middle + 1, nUpper);
 }
}

The next ones are the method prototypes and the main entry point that calls a menu. According to the user passed parameters we call the quicksort and the binary search methods:

// Function prototypes
void Menu(void);
void QuickSort(char** szArray, int nLower, int nUpper);
int Partition(char** szArray, int nLower, int nUpper);
int BinarySearch(char** szArray, char key[], int nLower, int nUpper);

// Application initialization
void main(void)
{
 char op;

 do
 {
   Menu();
   printf("\n\nDo you wanna a new QuickSort? Y/N");
   op = getche();
   if(islower(op))
     op = toupper(op);
 }
 while(op == 'Y');
}

void Menu(void)
{
 // Clear screen
 system("CLS");

 // Control execution time
 clock_t initial, final;

 // Print startup banner
 printf("\nQuickSort C++ Sample Application\n");
 printf("Copyright (c)2001-2002 Microsoft Corporation. All rights reserved.\n\n");
 printf("MSDN ACADEMIC ALLIANCE [http://www.msdnaa.net/]\n\n");
 printf("BinarySearch C++ Sample Application\n");
 printf("Copyright (c)2005 Leniel Braz de Oliveira Macaferi & Wellington Magalhaes Leite.\n");
 printf("UBM COMPUTER ENGINEERING - 5TH SEMESTER [http://www.ubm.br/]\n\n");

 // Describe program function
 printf("This program example demonstrates the QuickSort and BinarySearch algorithms by\n");
 printf("reading an input file, sorting its contents, writing them to a new file and\n");
 printf("searching on them.\n\n");

 // Prompt user for filenames
 char szSrcFile[1024], szDestFile[1024];
 printf("Source: ");
 gets(szSrcFile);
 printf("Output: ");
 gets(szDestFile);

 // Read contents of source file
 const long nGrow = 8;
 long nAlloc = nGrow;
 long nSize = 0;
 char** szContents = new char* [nAlloc];
 char szSrcLine[1024];
 FILE* pStream = fopen(szSrcFile, "rt");

 while(fgets(szSrcLine, 1024, pStream))
 {
   // Trim newline character
   char* pszCheck = szSrcLine;
   while(*pszCheck != '\0')
   {
     if(*pszCheck == '\n' && *(pszCheck + 1) == '\0')
       *pszCheck = '\0';
     pszCheck++;
   }

   // Append to array
   szContents[nSize] = new char [strlen(szSrcLine) + 1];
   strcpy(szContents[nSize], szSrcLine);
   nSize = nSize + 1;

   if(nSize % nGrow == 0)
   {
     // Resize the array
     char** szPrev = szContents;
     nAlloc += nGrow;
     szContents = new char* [nAlloc];
     memcpy(szContents, szPrev, nSize * sizeof(char*));
     delete szPrev;
   }
 }
 fclose (pStream);

 initial = clock();

 // Pass to QuickSort function
 QuickSort(szContents, 0, nSize - 1);

 final = clock();

 // Write sorted lines
 pStream = fopen (szDestFile, "wt");
 for(int nIndex = 0; nIndex < nSize; nIndex++)
 {
   // Write line to output file
   fprintf (pStream, "%s\n", szContents[nIndex]);
 }
 fclose (pStream);

 // Report program success
 printf("\nThe sorted lines have been written to the output file.\n\n");

 // QuickSort execution time
 double duration = (double)(final - initial) / CLOCKS_PER_SEC;

 printf("The QuickSort execution time was: %2.9lf s = %.0lf ms = %.0lf \xE6s\n\n", duration, duration * 1000, duration * 1000000);

 char op = '\0';

 do
 {
   printf("Do you wanna a BinarySearch to locate a specific key? Y/N");

   op = getche();
   if(islower(op))
     op = toupper(op);
   if(op == 'Y')
   {
     printf("\n\nType the key you want to search for: ");
     char key[1024];
     gets(key);

     initial = clock();

     if(BinarySearch(szContents, key, 0, nSize - 1))
     {
       final = clock();

       duration = (double)(final - initial) / CLOCKS_PER_SEC;

       printf("\nKey found!\n\n");

       printf("The BinarySearch execution time was: %2.9lf s = %.0lf ms = %.0lf \xE6s\n\n", duration, duration * 1000, duration * 1000000);

     }
     else
     {
       final = clock();

       duration = (double)(final - initial) / CLOCKS_PER_SEC;

       printf("\nKey not found!\n\n");

       printf("The BinarySearch execution time was: %2.9lf s = %.0lf ms = %.0lf \xE6s\n\n", duration, duration * 1000, duration * 1000000);

     }
   }
   else
   {
     // Deallocate entire array
     for(int nIndex = 0; nIndex < nSize; nIndex++)
       // Delete current array element
       delete szContents[nIndex];

     delete szContents;
     szContents = NULL;
   }
 }
 while(op == 'Y'); 
}

Visual Studio C++ Console Application

You can get the project files at:
http://leniel.googlepages.com/QuicksortBinarySearchCPlusPlus.zip

Random number generator

You can get the spreadsheet responsible for this task at:
http://leniel.googlepages.com/QuicksortBinarySearchRandomNumGen.xls

How to use it?

To use the program:

1. Enter the name of a file that contains unsorted data;
2. Use the sample files included in the .ZIP package as: 1000.txt and 2500.txt;
3. In the command line "Source", type: 1000.txt;
4. In the command line "Output", type a name to the file that will be sorted. e.g.: sorted.txt;
5. After the sorting process, choose if you want or not to execute a Binary Search. If yes, provide a value to be searched. If not, choose if it is or not desired to execute a new Quicksort.

Postscript:
- To generate random numbers, use the file Random numbers generator.xls file;
- The file QuicksortBinarySearch.cpp contains the source code. The same can be used freely. Mention the authors.

Efficiency comparison

For the sake of comparison I've run some test cases with different input files. See the result in the table that follows:

Quicksort and Binary search performance

n	File name	File size (bytes)	Timing (milliseconds)
			Quicksort	Binary search
10000	10000.txt	122.880	16	0
25000	25000.txt	200.704	78	0
50000	50000.txt	401.408	219	0
75000	75000.txt	602.112	360	0
100000	100000.txt	802.816	516	0

It's important to note that the time the quicksort takes appears to be longer but it is not. Why? Because the the program needs to read the file content and write the sorted data back to the output file so that it appears to take longer than the milliseconds shown on the above table. The timing functions just operate while the quicksort is running.

For the the binary search key I've input a value localized in the beginning of the sorted file, in the middle and in the end. There was no time changes. The binary search found the key I entered with a time less than (0 µs - microsecond). I have an AMD Athlon XP 2400 with 512 MB RAM.

See a screenshot of the last test case:

The paper

You can get a copy of the paper in the .PDF format at:
http://leniel.googlepages.com/QuicksortAndBinarySearchAlgorithms.pdf

Posted by Leniel Macaferi on 5/03/2008 07:23:00 PM

Windows API
The Windows API, informally WinAPI, is Microsoft's core set of application programming interfaces (APIs) available in the Microsoft Windows operating systems. All Windows programs except console programs must interact with the Windows API regardless of the language.

Win32 API
The Win32 API is the 32-bit API for modern versions of Windows. The API consists of functions implemented, as with Win16, in system DLLs. The core DLLs of Win32 are kernel32.dll, user32.dll, and gdi32.dll. Win32 was introduced with Windows NT.

Words of wisdom
Dealing with the Win32 API appears to be a regression since it takes us to the last century, that is, when programming with such API we are writing code that resembles the code written 15 years ago or more. Regression was the feeling I felt when the teacher said we'd study this API. Nevertheless, there are billions of lines of code that need maintenance because great part of these lines are used in legacy systems. So you see that learning this API is fundamental even today. This is in contrast with the mainframe computers dilemma. Even today there are a bunch of companies that still use them because of legacy systems. The feeling of regression was substituted by a enthusiasm one in the end.

Mouse interaction app
One coursework related to the Object Oriented Systems discipline I had to develop was a program that draws on the screen by free hand with the mouse assistance. The program must monitor the mouse movement, indicating its position (x, y) in the upright corner of the application window, in the format (xxx, yyy). Pressing the left mouse button it draws and pressing the right mouse button, it wipes off the screen content.

Some valuable tips that the teacher gave:
Use the events WM_MOUSE, WM_LBUTTONDOWN, WM_LBUTTONUP, WM_RBUTTONDOWN, WM_RBUTTONUP and the function SetPixel()

lword(lParam) has 0 x
hiword(lParam) has 0 Y

I originally implemented this program using DevC++. Today while composing this post I just created a new Win32 Project application using the Microsoft Visual Studio C++ Express Edition. Although the implementation differs a little bit, it wasn't difficult to port it to the Microsoft programming environment. I'll provide both implementations at the end of the post.

Let's see the mouse app main block of code. It's inside the WndProc function that is responsible for processing the messages for the main window. The code is commented so I think it's unnecessary to add more to it.

//
//  FUNCTION: WndProc(HWND, UINT, WPARAM, LPARAM)
//
//  PURPOSE:  Processes messages for the main window.
//
//  WM_COMMAND     - Process the application menu
//  WM_PAINT       - Paint the main window
//  WM_DESTROY     - Post a quit message and return
//  WM_LBUTTONDOWN - Left mouse button clicked
//  WM_RBUTTONDOWN - Right mouse button clicked
//  WM_LBUTTONUP   - Left mouse button released
//  WM_RBUTTONUP   - Right mouse button released
//  WM_MOUSEMOVE   - Controls the mouse movement
//
LRESULT CALLBACK WndProc(HWND hWnd, UINT message, WPARAM wParam, LPARAM lParam)
{
  int wmId, wmEvent;

  switch(message) //Handle the messages
  {
    case WM_DESTROY:

      PostQuitMessage(0); // Send a WM_QUIT to the message queue

      break;

    case WM_PAINT:
      // TODO: Add any drawing code here...  
      hDC = GetDC(hWnd);

      BeginPaint(hWnd, &paintStruct);

      EndPaint(hWnd, &paintStruct);

      break;

    // Left button event used to print the screen
    case WM_LBUTTONDOWN:

      flag = true;

      // Black color   
      newColor = RGB(0, 0, 0);

      xMouse = LOWORD(lParam);

      yMouse = HIWORD(lParam);

      SetPixel(hDC, xMouse, yMouse, newColor);

      break;

    // Right button event used to erase the screen content
    case WM_RBUTTONDOWN:

      flag = true;

      // White color           
      newColor = RGB(255, 255, 255);

      xMouse = LOWORD(lParam);

      yMouse = HIWORD(lParam);

      SetPixel(hDC, xMouse, yMouse, newColor);

      break;

    // Sets the flag to false so that we know the left mouse button was released
    case WM_LBUTTONUP:

      flag = false;

      break;

    // Sets the flag to false so that we know the right mouse button was released
    case WM_RBUTTONUP:

      flag = false;

      break;

    // Controls the mouse movement and shows its current position on the Window title
    case WM_MOUSEMOVE:

      if(flag)
      {
        xMouse = LOWORD(lParam);

        yMouse = HIWORD(lParam);

        SetPixel(hDC, xMouse, yMouse, newColor);

        sprintf_s(strTitle, "  x=%d y=%d", xMouse, yMouse);

        SetWindowText(hWnd, strTitle);

        SetWindowText(hlabel, strTitle);
      }
      else
      {
        xMouse = LOWORD(lParam);

        yMouse = HIWORD(lParam);

        sprintf_s(strTitle, "  x=%d y=%d", xMouse, yMouse);

        SetWindowText(hWnd, strTitle);

        SetWindowText(hlabel, strTitle);
      }

      break;

    case WM_COMMAND:
      wmId    = LOWORD(wParam);
      wmEvent = HIWORD(wParam);
      // Parse the menu selections:
      switch(wmId)
      {
        case IDM_ABOUT:
            
          DialogBox(hInst, MAKEINTRESOURCE(IDD_ABOUTBOX), hWnd, About);
          
          break;
      
        case IDM_EXIT:
            
          DestroyWindow(hWnd);
          
          break;
          
        default:

          return DefWindowProc(hWnd, message, wParam, lParam);
      }

    break;

    default:  // For messages that we don't deal with

      return DefWindowProc (hWnd, message, wParam, lParam);
  }

  return 0;
}

Reference
To get more insight regarding the Win32 API, go to the Win32 Development site at the Microsoft Development Network: http://msdn.microsoft.com/en-us/library/aa139672.aspx

Dev-C++ and Visual Studio Projects
DevC++ project
http://leniel.googlepages.com/Win32APIMouseInteractAppDevCPlusPlus.zip

Visual Studio Win32 project
http://leniel.googlepages.com/Win32APIMouseInteractAppVCPlusPlus.zip

Posted by Leniel Macaferi on 3/22/2008 03:30:00 PM

As an extra, today I'm posting the C++ code of the breadth and depth first search algorithms. Take a look at part 1 and part 2 of this series.

When I had to hand in the work for the artificial intelligence discipline, the teacher wanted the code in C++ and I had already started developing the code in C#. The result was two versions of the same functions. The good part is that I could master both languages while developing such a code.

The code presented here uses an adjacency matrix to represent the links between the cities that are part of the Romania map shown bellow.

The following is the adjacency matrix:

// Adjacency matrix
int map[21][21] = {
/*   A B C D E F G H I L M N O P R S T U V Z */
  {0,1,2,3,4,5,6,7,8,9,0,1,2,3,4,5,6,7,8,9,0},
  {1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1}, // Arad
  {2,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,1,0,0}, // Bucharest
  {3,0,0,0,1,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0}, // Craiova
  {4,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0}, // Dobreta
  {5,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0}, // Eforie
  {6,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0}, // Fagaras
  {7,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}, // Girgiu
  {8,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0}, // Hirsova
  {9,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0}, // Iasi
  {0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0}, // Lugoj
  {1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0}, // Mehadia
  {2,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0}, // Neamt
  {3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1}, // Oradea
  {4,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0}, // Pitesti
  {5,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0}, // Rimnicu Vilcea
  {6,1,0,0,0,0,1,0,0,0,0,0,0,1,0,1,0,0,0,0,0}, // Sibiu
  {7,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0}, // Timisoara
  {8,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0}, // Urziceni
  {9,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0}, // Vaslui
  {0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0}  // Zerind
};

Note that the first commented line represents the initial letter of each city's name. The mapping done with the adjacency matrix refers to these letters so that it's easier to understand. For example, getting the first entry of the adjacency matrix that refers to Arad: we have that Arad has paths that lead us to Sibiu, Timisoara and Zerind, thus we put a value of 1 on the columns that represent those cities, in this case, the columns beneath the letters S, T and Z. That's how the mapping is done. We put a value of 0 on the other columns to state that there is no path that leads us to those cities.

The code also has a hand made version of the stack and queue data structures. Each one of these structures is on its proper header file and are inline functions. See their implementations:

// Queue struct Queue { int start, end, tot; int info[max + 1]; }; void StartQueue(Queue *q) { q->tot = 0; q->start = 1; q->end = 0; } int IsQueueEmpty(Queue *q) { return q->tot == 0 ? 1 : 0; } int IsQueueFull(Queue *q) { return q->tot == max ? 1 : 0; } int Adc(int x) { return x == max ? 1 : x + 1; } void Enqueue(Queue *q, int x) { if(!IsQueueFull(q)) { q->end = Adc(q->end); q->info[q->end] = x; q->tot++; } } int Dequeue(Queue *q) { int ret = 0; if(!IsQueueEmpty(q)) { ret = q->info[q->start]; q->start = Adc(q->start); q->tot--; } return ret; } // End Queue

// Stack struct Stack { int topo; int info[max + 1]; }; void StartStack(Stack *s) { s->topo = 0; } int IsStackEmpty(Stack *s) { return s->topo==0 ? 1 : 0; } int IsStackFull(Stack *s) { return s->topo == max ? 1 : 0; } void Push(Stack *s, int x) { if(!IsStackFull(s)) { s->topo++; s->info[s->topo] = x; } } int Pop(Stack *s) { int ret = 0; if(!IsStackEmpty(s)) { ret = s->info[s->topo]; s->topo--; } return ret; } // End Stack

The Breadth First Search and Depth First Search functions are written in the same fashion of the C# code, but with little modifications.

void BreadthFirstSearch(int origin, int destination)
{
  Queue *q = new Queue();

  StartQueue(q);

  Enqueue(q, origin);

  while(IsQueueEmpty(q) == 0)
  {
    int u = Dequeue(q);

    if(u == destination)
    {
      printf("Path found.");

      break;
    }
    else
    {
      visited[u] = 1;

      for(int v = 1; v <= 20; v++)
      {
        if(map[u][v] != 0)
        {
          if(visited[v] == 0)
          {
            visited[v] = 1;

            parents[v] = u;

            if(v != destination)
            {
              if(!IsQueueFull(q))
              {
                Enqueue(q, v);

                ShowPath(v);

                printf("\n");
              }
              else
              {
                printf("Queue full.");

                break;
              }
            }
            else
            {
              ShowPath(v);

              return;
            }
          }       
        }
      }
    }
  }
}

void DepthFirstSearch(int origin, int destination)
{
  Stack *s = new Stack();

  StartStack(s);

  Push(s, origin);

  while(IsStackEmpty(s) == 0)
  {
    int u = Pop(s);

    if(u == destination)
    {
      printf("Path found.");

      break;
    }
    else
    {
      visited[u] = 1;

      for(int v = 1; v <= 20; v++)
      {
        if(map[u][v] != 0)
        {
          if(visited[v] == 0)
          {
            visited[v] = 1;

            parents[v] = u;

            if(v != destination)
            {
              if(!IsStackFull(s))
              {
                Push(s, v);

                ShowPath(v);

                printf("\n");
              }
              else
              {
                printf("Stack full.");

                break;
              }
            }
            else
            {
              ShowPath(v);

              return;
            }
          }      
        }
      }
    }
  }
}

To show the travelled paths there is a recursive function called ShowPath:

void ShowPath(int u)
{
  if(parents[u] != 0)
    ShowPath(parents[u]);

  printf(" %s", cities[u]);
}

You see, I had finalized the C# code and even sent the code to the teacher, but I received his reply stating that he wanted the code in C++. I complained with him! I told him about the easiness that modern programming languages as C# offers us when writing code.

Today, the data structures (queue and stack) "hand made" in this code are present in modern and optimized fashions inside standard libraries. We just need to instantiate an object from that specific class, in this case, stack or queue, and tada, we get lots of functions that do the hard work. But the point here is not the easiness. What the teacher wanted to force us to do was to comprehend how those data structures really function.

Nothing is better than writing the data structures by yourself. Although I didn't agree at the time, I thank him for forcing me to learn. Needless to say, these are basic data structures and are used in a great amount of code. You'll see these data structures during your entire developer life.

Visual Studio C++ Console Application
You can get the Microsoft Visual Studio Project and the app executable at:

http://leniel.googlepages.com/BreadthDepthFirstSearchCPlusPlus.zip

Posted by Leniel Macaferi on 3/08/2008 12:02:00 PM

Last month was a busy one. On February 11th I started working on a project called Galileu. This project is being implemented by a joint venture between Petrobras and a group of universities. Amongst those universities is the Aeronautics Technological Institute (ITA).

I got such job opportunity through ITA's mechanical engineering department, more specifically the Computational Transport Phenomena Laboratory. I received an email from its group leader Marcelo de Lemos. I answered the email right way sending him my resume. They needed someone with expertise in programming languages and high performance computing (HPC). I was eagerly waiting a job opportunity because I finished the computer engineering course and there was no place to work. This opportunity was just what I needed.

My work is really exciting. Firstly I was given material about the message passing interface (MPI) and the Rocks clusters distribution for the Linux platform. After that I started playing with the Linux cluster, which was already installed. Who installed it was a great friend I met at the lab. His name is Arkady Petchenko.

As a lab we experiment with the available HPC platforms. The last two weeks I've been playing with the Windows Computer Cluster Server 2003. I was responsible for installing the Windows cluster.

I'm also doing development of code in C/C++ and Fortran. I compile and build applications that can explore the full potential of a cluster through the MPI API.

It's fantastic to see how a parallel program performs on different numbers of processors.

In future posts I'd like to discuss about the aspects of the technologies I work with. It's great stuff! I love programming languages and the parallel computing world is a fascinating one. With the increase of the number of processors in a single chip, we're going to see a vast amount of parallelized code being executed on distributed computing systems. Parallel APIs as the Microsoft Parallel Extensions for .NET framework are evolving rapidly. This will for sure change the way we think when working with code and specially with clusters and supercomputers.