🎓 Computer Science & Engineering Portal

Master Engineering Disciplines with Structured Notes

Comprehensive academic lecture notes, exam-oriented unit summaries, laboratory manuals, and previous year question papers designed strictly for university students.

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University Syllabi

AKTU & AICTE aligned semester credit guidelines.

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Exam Question Papers

Previous 5 years solved university semester papers.

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Lab Manuals & Viva

Practical codes with outputs and interview questions.

Core Subjects & Units Hub

Click on any specific unit to immediately view its lecture notes below

🎨 Computer Graphics (CG)

Scan Conversion, Transformations, Viewing & Clipping.

Unit 1: Raster Scan & Bresenham→
Unit 2: 2D & 3D Transformations→
Unit 3: Viewing & Clipping→
Unit 4: Hidden Surface Elimination→
Unit 5: Curves & Animation→

🧠 Machine Learning (ML)

Regression, Decision Trees, SVM, Neural Nets & Clustering.

Unit 1: Supervised & Regression→
Unit 2: Decision Trees & SVM→
Unit 3: Unsupervised & K-Means→
Unit 4: Neural Networks→
Unit 5: Reinforcement Learning→

🤖 Artificial Intelligence (AI)

Search Algorithms, First Order Logic, Expert Systems.

Unit 1: Propositional Logic→
Unit 2: Probabilistic Reasoning→
Unit 3: State Space Search & A*→
Unit 4: First Order Predicate Logic→
Unit 5: Expert Systems→

🗄️ Database Management

ER-Modeling, SQL Queries, Normalization and ACID.

Unit 1: ER Model & Attributes→
Unit 2: Normalization (1NF-BCNF)→
Unit 3: ACID & Concurrency→
Unit 4: Relational Algebra & SQL→
Unit 5: NoSQL & Advanced DB→

🌲 Data Structures (DSA)

Arrays, Linked Lists, Trees, Graphs & Sorting.

Unit 1: Arrays & Recursion→
Unit 2: Stacks, Queues & Postfix→
Unit 3: Binary Trees & BST→
Unit 4: Graphs (BFS, DFS)→
Unit 5: Sorting & Hashing→

⚡ Operating Systems (OS)

Process Scheduling, Deadlocks, Virtual Memory & Disks.

Unit 1: Process States & Threads→
Unit 2: CPU Scheduling→
Unit 3: Deadlocks & Banker's Algo→
Unit 4: Virtual Memory & Paging→
Unit 5: File & Disk Management→

🌐 Computer Networks

OSI Models, Subnetting, Routing and TCP Handshake.

Unit 1: OSI vs TCP/IP Models→
Unit 2: Data Link Layer & Framing→
Unit 3: IPv4 & Subnetting→
Unit 4: Transport Layer (TCP)→
Unit 5: Application Layer (DNS)→

⚙ Design of Algorithms

Asymptotic Notations, Divide & Conquer, Greedy.

Unit 1: Time Complexity→
Unit 2: Divide & Conquer→
Unit 3: Dynamic Programming→
Unit 4: Greedy Approach→
Unit 5: Backtracking→
Viewing All Lectures

Structural Testing (White Box Testing)

Structural  Testing  (White Box  Testing):

  • White Box Testing is software testing technique in which internal structure, design and coding of software are tested to verify flow of input-output and to improve design, usability and security. In white box testing, code is visible to testers so it is also called Clear box testing, Open box testing, Transparent box testing, Code-based testing and Glass box testing.
  • Structure-based testing technique is also known as 'white-box' or 'glass-box' testing technique because here the testers require knowledge of how the software is implemented, how it works. In white-box testing the tester is concentrating on how the software does it.
  • It is one of two parts of the Box Testing approach to software testing. Its counterpart, Blackbox testing, involves testing from an external or end-user type perspective. On the other hand, White box testing in software engineering is based on the inner workings of an application and revolves around internal testing.

Advantages:

  • Code optimization by finding hidden errors.
  • White box test cases can be easily automated.

Disadvantages:

  • White box testing can be quite complex and expensive.
  • Developers who usually execute white box test cases detest it. The white box testing by developers is not detailed and can lead to production errors.

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