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Results for "Author: david k richmond"

ASP_Volume2 #28810
Binary Search Tree Node Class (database engine)

Binary Search Tree Nodes Class - an effective and very fast searching/database storage methodology. This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. Now you can have the database power inside your application. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks regardless of the key your are trying to locate. Also included are member routines to output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and collection. Also extensive notes and a built-in commented example project/form to build a couple of example binary trees which output to a gui listbox. Also to demonstrate some of the class member functions usage. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels.(**IMPORTANT**: this latest version includes a major bug fix. When using the data index to reference external data, during a tree rebalance the data index was being lost or mixed up with another. It is a simple fix but significant to keeping the database integrity. This latest version is 1.1 and also includes the functions referenced in the supplemental article). ## LATEST: ## now includes a CD,DVD,Books Media Library application sample. ## (c) David K Richmond

ASP_Volume2 #28811
Binary Search Tree Node Class (database engine) - GetPrevInSortedOrder & GetNextInSortedOrder

Supplements existing article by similar name and by this author. This is a new release and includes the extra member functions in cBSTNStorage.cls in order to allow node removal. (INCLUDES major bug fix to preserve data index during node removal).

ASP_Volume3 #65038
Media Library Sample (using Binary Search Tree Node Class as database engine)

A 'vanilla' Media Library application sample to store, maintain and review CDs,DVDs,Books in a Media Library by barcode or unique media key. It's unique in that it is using a Binary Search Tree Nodes Class - an effective and very fast searching/database storage methodology. This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. Now you can have the database power inside your application. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks regardless of the key your are trying to locate. Also included are member routines to output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and collection. Also extensive notes and a built-in commented example project/form to build a couple of example binary trees which output to a gui listbox. Also to demonstrate some of the class member functions usage. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels. (c) David K Richmond

ASP_Volume3 #65039
Media Library Disk/Memory Sample (using Binary Search Tree Node Class as database engine)

(NEW UPDATE May 21/05) A unique Media Disk/Memory Library application sample with DISK BASED LIBRARY ACCESS as well as MEMORY LIBRARY ACCESS. It can be used to store, maintain and review CDs,DVDs,Books in a Media Disk/Memory Library by barcode or unique media key. It's unique in that it is using a Binary Search Tree Nodes Class (UPDATED since an earlier article here @psc) to allow optional DISK based BS Trees as well as the established previous existing in MEMORY version). This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. It's an effective and very fast searching/database storage methodology. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks per key search. BSTN class member routines include, the output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested in MEMORY MODE for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and beta level collection. This version has an updated BSTN Class (see other psc article) DISK ACCESS wrapper to overload the BSTN member functions/properties to allow direct access to a disk based node tree around the sample media library - sample included in this article. NOTE: The DISK ACCESS mode has NOT been extensively tested as yet (look out for release late May 2005), but the project was fit to publish. If you don't need the DISK ACCESS mode, it won't be turned on unless you choose to enable it but all the MEMORY functions will work as expected. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels. GARBAGE COLLECTION UPDATED under menu tools options. see Help How-To. (c) David K Richmond

ASP_Volume3 #65040
Binary Search Tree Node Class (database engine)

Binary Search Tree Nodes Class - an effective and very fast searching/database storage methodology. This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. Now you can have the database power inside your application. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks regardless of the key your are trying to locate. Also included are member routines to output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and collection. Also extensive notes and a built-in commented example project/form to build a couple of example binary trees which output to a gui listbox. Also to demonstrate some of the class member functions usage. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels.(**IMPORTANT**: this latest version includes a major bug fix. When using the data index to reference external data, during a tree rebalance the data index was being lost or mixed up with another. It is a simple fix but significant to keeping the database integrity. This latest version is 1.1 and also includes the functions referenced in the supplemental article). ## LATEST: ## now includes a CD,DVD,Books Media Library application sample. ## (c) David K Richmond

ASP_Volume3 #65041
Binary Search Tree Node Class (database engine) - GetPrevInSortedOrder & GetNextInSortedOrder

THE ARTICLE IS REDUNDANT NOW - PLEASE SEE ORIGINAL ARTICLE [ Binary Search Tree Node Class (database engine) ] ALL NEW WORK AND CHANGES ARE INCLUDED THERE ........Supplements existing article by similar name and by this author. This is a new release and includes the extra member functions in cBSTNStorage.cls in order to allow node removal. (INCLUDES major bug fix to preserve data index during node removal).

C_Volume2 #69872
Binary Search Tree Node Class (database engine)

Binary Search Tree Nodes Class - an effective and very fast searching/database storage methodology. This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. Now you can have the database power inside your application. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks regardless of the key your are trying to locate. Also included are member routines to output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and collection. Also extensive notes and a built-in commented example project/form to build a couple of example binary trees which output to a gui listbox. Also to demonstrate some of the class member functions usage. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels.(**IMPORTANT**: this latest version includes a major bug fix. When using the data index to reference external data, during a tree rebalance the data index was being lost or mixed up with another. It is a simple fix but significant to keeping the database integrity. This latest version is 1.1 and also includes the functions referenced in the supplemental article). ## LATEST: ## now includes a CD,DVD,Books Media Library application sample. ## (c) David K Richmond

C_Volume2 #69873
Binary Search Tree Node Class (database engine) - GetPrevInSortedOrder & GetNextInSortedOrder

Supplements existing article by similar name and by this author. This is a new release and includes the extra member functions in cBSTNStorage.cls in order to allow node removal. (INCLUDES major bug fix to preserve data index during node removal).

Java_Volume1 #88416
Binary Search Tree Node Class (database engine)

Binary Search Tree Nodes Class - an effective and very fast searching/database storage methodology. This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. Now you can have the database power inside your application. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks regardless of the key your are trying to locate. Also included are member routines to output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and collection. Also extensive notes and a built-in commented example project/form to build a couple of example binary trees which output to a gui listbox. Also to demonstrate some of the class member functions usage. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels.(**IMPORTANT**: this latest version includes a major bug fix. When using the data index to reference external data, during a tree rebalance the data index was being lost or mixed up with another. It is a simple fix but significant to keeping the database integrity. This latest version is 1.1 and also includes the functions referenced in the supplemental article). ## LATEST: ## now includes a CD,DVD,Books Media Library application sample. ## (c) David K Richmond

Java_Volume1 #88417
Binary Search Tree Node Class (database engine) - GetPrevInSortedOrder & GetNextInSortedOrder

Supplements existing article by similar name and by this author. This is a new release and includes the extra member functions in cBSTNStorage.cls in order to allow node removal. (INCLUDES major bug fix to preserve data index during node removal).

2_2002-2004 #115563
Binary Search Tree Node Class (database engine)

Binary Search Tree Nodes Class - an effective and very fast searching/database storage methodology. This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. Now you can have the database power inside your application. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks regardless of the key your are trying to locate. Also included are member routines to output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and collection. Also extensive notes and a built-in commented example project/form to build a couple of example binary trees which output to a gui listbox. Also to demonstrate some of the class member functions usage. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels.(**IMPORTANT**: this latest version includes a major bug fix. When using the data index to reference external data, during a tree rebalance the data index was being lost or mixed up with another. It is a simple fix but significant to keeping the database integrity. This latest version is 1.1 and also includes the functions referenced in the supplemental article). ## LATEST: ## now includes a CD,DVD,Books Media Library application sample. ## (c) David K Richmond

2_2002-2004 #115564
Binary Search Tree Node Class (database engine) - GetPrevInSortedOrder & GetNextInSortedOrder

Supplements existing article by similar name and by this author. This is a new release and includes the extra member functions in cBSTNStorage.cls in order to allow node removal. (INCLUDES major bug fix to preserve data index during node removal).

3_2004-2005 #134107
Binary Search Tree Node Class (database engine)

Binary Search Tree Nodes Class - an effective and very fast searching/database storage methodology. This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. Now you can have the database power inside your application. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks regardless of the key your are trying to locate. Also included are member routines to output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and collection. Also extensive notes and a built-in commented example project/form to build a couple of example binary trees which output to a gui listbox. Also to demonstrate some of the class member functions usage. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels.(**IMPORTANT**: this latest version includes a major bug fix. When using the data index to reference external data, during a tree rebalance the data index was being lost or mixed up with another. It is a simple fix but significant to keeping the database integrity. This latest version is 1.1 and also includes the functions referenced in the supplemental article). ## LATEST: ## now includes a CD,DVD,Books Media Library application sample. ## (c) David K Richmond

3_2004-2005 #134108
Binary Search Tree Node Class (database engine) - GetPrevInSortedOrder & GetNextInSortedOrder

Supplements existing article by similar name and by this author. This is a new release and includes the extra member functions in cBSTNStorage.cls in order to allow node removal. (INCLUDES major bug fix to preserve data index during node removal).

4_2005-2006 #170335
Media Library Sample (using Binary Search Tree Node Class as database engine)

A 'vanilla' Media Library application sample to store, maintain and review CDs,DVDs,Books in a Media Library by barcode or unique media key. It's unique in that it is using a Binary Search Tree Nodes Class - an effective and very fast searching/database storage methodology. This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. Now you can have the database power inside your application. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks regardless of the key your are trying to locate. Also included are member routines to output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and collection. Also extensive notes and a built-in commented example project/form to build a couple of example binary trees which output to a gui listbox. Also to demonstrate some of the class member functions usage. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels. (c) David K Richmond

4_2005-2006 #170336
Media Library Disk/Memory Sample (using Binary Search Tree Node Class as database engine)

(NEW UPDATE May 21/05) A unique Media Disk/Memory Library application sample with DISK BASED LIBRARY ACCESS as well as MEMORY LIBRARY ACCESS. It can be used to store, maintain and review CDs,DVDs,Books in a Media Disk/Memory Library by barcode or unique media key. It's unique in that it is using a Binary Search Tree Nodes Class (UPDATED since an earlier article here @psc) to allow optional DISK based BS Trees as well as the established previous existing in MEMORY version). This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. It's an effective and very fast searching/database storage methodology. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks per key search. BSTN class member routines include, the output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested in MEMORY MODE for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and beta level collection. This version has an updated BSTN Class (see other psc article) DISK ACCESS wrapper to overload the BSTN member functions/properties to allow direct access to a disk based node tree around the sample media library - sample included in this article. NOTE: The DISK ACCESS mode has NOT been extensively tested as yet (look out for release late May 2005), but the project was fit to publish. If you don't need the DISK ACCESS mode, it won't be turned on unless you choose to enable it but all the MEMORY functions will work as expected. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels. GARBAGE COLLECTION UPDATED under menu tools options. see Help How-To. (c) David K Richmond

4_2005-2006 #170337
Binary Search Tree Node Class (database engine)

Binary Search Tree Nodes Class - an effective and very fast searching/database storage methodology. This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. Now you can have the database power inside your application. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks regardless of the key your are trying to locate. Also included are member routines to output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and collection. Also extensive notes and a built-in commented example project/form to build a couple of example binary trees which output to a gui listbox. Also to demonstrate some of the class member functions usage. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels.(**IMPORTANT**: this latest version includes a major bug fix. When using the data index to reference external data, during a tree rebalance the data index was being lost or mixed up with another. It is a simple fix but significant to keeping the database integrity. This latest version is 1.1 and also includes the functions referenced in the supplemental article). ## LATEST: ## now includes a CD,DVD,Books Media Library application sample. ## (c) David K Richmond

4_2005-2006 #170338
Binary Search Tree Node Class (database engine) - GetPrevInSortedOrder & GetNextInSortedOrder

THE ARTICLE IS REDUNDANT NOW - PLEASE SEE ORIGINAL ARTICLE [ Binary Search Tree Node Class (database engine) ] ALL NEW WORK AND CHANGES ARE INCLUDED THERE ........Supplements existing article by similar name and by this author. This is a new release and includes the extra member functions in cBSTNStorage.cls in order to allow node removal. (INCLUDES major bug fix to preserve data index during node removal).

5_2007-2008 #192853
Media Library Sample (using Binary Search Tree Node Class as database engine)

A 'vanilla' Media Library application sample to store, maintain and review CDs,DVDs,Books in a Media Library by barcode or unique media key. It's unique in that it is using a Binary Search Tree Nodes Class - an effective and very fast searching/database storage methodology. This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. Now you can have the database power inside your application. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks regardless of the key your are trying to locate. Also included are member routines to output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and collection. Also extensive notes and a built-in commented example project/form to build a couple of example binary trees which output to a gui listbox. Also to demonstrate some of the class member functions usage. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels. (c) David K Richmond

5_2007-2008 #192854
Media Library Disk/Memory Sample (using Binary Search Tree Node Class as database engine)

(NEW UPDATE May 21/05) A unique Media Disk/Memory Library application sample with DISK BASED LIBRARY ACCESS as well as MEMORY LIBRARY ACCESS. It can be used to store, maintain and review CDs,DVDs,Books in a Media Disk/Memory Library by barcode or unique media key. It's unique in that it is using a Binary Search Tree Nodes Class (UPDATED since an earlier article here @psc) to allow optional DISK based BS Trees as well as the established previous existing in MEMORY version). This is a self-contained binary tree class along with a non-gui listbox class to create, search and maintain any unique key data in a binary tree. A lot of databases use this methodology as the basis for their database engines. It's an effective and very fast searching/database storage methodology. For example, a search of 3,000 keys will only require an average of 7-11 tree visits/seeks per key search. BSTN class member routines include, the output all the data keys in tree in alpha order or even in reverse alpha order. This has been extensively tested in MEMORY MODE for reliabilty and fast response for searching, insertions, deletions and traversals of tree nodes in general. Included root node release, tree re-balancing and garbage threshold detection and beta level collection. This version has an updated BSTN Class (see other psc article) DISK ACCESS wrapper to overload the BSTN member functions/properties to allow direct access to a disk based node tree around the sample media library - sample included in this article. NOTE: The DISK ACCESS mode has NOT been extensively tested as yet (look out for release late May 2005), but the project was fit to publish. If you don't need the DISK ACCESS mode, it won't be turned on unless you choose to enable it but all the MEMORY functions will work as expected. You may be surprised to learn there is little emphasis on recursion so no worries of runaway stack levels. GARBAGE COLLECTION UPDATED under menu tools options. see Help How-To. (c) David K Richmond

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