B.Tech Laboratories

COMPUTER PROGRAMMING LAB:

• To write programs in C to solve the problem.
• To implement linear data structures such as lists, stacks, queues.
• To implement simple searching and sorting methods.

INFORMATION TECHNOLOGY WORKSHOP:

• To write programs in html.
• To design the paper presentations.
• To implement excel sheets and Ms Word.

DATA STRUCTURES LAB:

• To write and execute programs in C to solve problems using data structure such as arrays, linked lists, stacks, queues, trees, graphics, hash tables and search trees.
• To write and execute write programs in C to implement various sorting and searching methods.

JAVA PROGRAMMING LAB:

• To understands objects oriented programming concepts, and apply them in problem solving.
• To learn the basics of java console and GUI based programming.

DATABASE MANAGEMENT SYSTEMS LAB:

• To learn the security of databases.
• To learn the design techniques of database security.
• To learn the secure software design.

OPERATING SYSTEMS LAB:

• To understand the basic concepts such as Abstract data types, Linear and non linear Data Structure.
• To choose the appropriate data structure for a specified application.
• To understand and analyze various searching and sorting algorithms

COMPILER DESIGN LAB:

• To write and execute programs in java to solve problems using java swings, eclipse, net beans.
• To provide your identity namespace to applications
• To implement security system integration

CASE TOOLS & WEB TECHNOLOGIES LAB:

• To write and execute programs in web technology to solve problems using HTML, XML, HTTP, PHP.
• To learn how to implement and deploy web service client and server
• To explore interoperability between different frameworks.

LINUX PROGRAMMING LAB:

• To write shell scripts to solve problems.
• To implement some standard Linux utilities such as IS, cp etc using system calls.
• To develop network-based applications using C.

DATA WAREHOUSING & MINING LAB:

• To develop the abilities of critical analysis to data mining systems and applications.
• To implement practical and theoretical understanding of the technologies for data mining.
• To understand the strengths and limitations of various data mining models.

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