MODULE-I
Basics of Software Testing and Examples: Basic definitions, Test cases, Insights from a Venn diagram,
Identifying test cases, Error and fault taxonomies, Levels of testing. Examples: Generalized pseudocode,
The triangle problem, The NextDate function, The commission problem, The SATM (Simple Automatic
Teller Machine) problem. 10 hours
MODULE-II
Decision Table-Based Testing: Decision tables, Test cases for the triangle problem, Test cases for the
NextDate function, Test cases for the commission problem, Guidelines and observation ....etc

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To get full information or details of enterprise resource planning please have a look on the pages

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Data Compression
This video lecture series by Dr. Naveen Garg, Department of Computer Science & Engineering ,IIT Delhi includes Introduction to Data Structures and Algorithms, Stacks, Queues and Linked Lists, Dictionaries, Hashing, Trees, Tree Walks-Traversals, Ordered Dictionaries, Deletion, Quick Sort, AVL Trees, Red Black Trees, Disk Based Data Structures, Tries, Data Compression, Priority Queues, Binary Heaps, Data Structures for Graphs, Applications of DFS, Minimum Spanning Trees, The Union, Single Source Shortest Paths, Correctness of Dij ....etc

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To get full information or details of pattern recognition and image analysis please have a look on the pages

http://seminarsprojects.net/Thread-an-efficient-algorithm-for-iris-pattern-recognition-using-2d-gabor-wavelet

http://seminarsprojects.net/Thread-an-efficient-algorithm-for-iris-pattern-recognition-using-2-download-seminar-report

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Parallel Databases : I/O Parallelism, Interquery Parallelism, Intraquery Parallelism,
Intraoperation Parallelism, Interoperation Parallelism, Design of Parallel Systems ....etc

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lecture notes of data compression by khalid sayood

In digital signal processing, data compression, source coding, or bit-rate reduction involves encoding information using fewer bits than the original representation. Compression can be either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by identifying unnecessary information and removing it. The process of reducing the size of a data file is ref ....etc

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arer notes.pls se t me the notes immediately ....etc

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