DTU Lab Files Repository

This repository contains comprehensive lab files from Delhi Technological University (DTU), covering multiple key subjects from the Computer Science and Engineering curriculum. These files are structured to provide practical insight and hands-on experience in various domains, including Computer Networks, Natural Language Processing, Software Requirement Engineering, Software Testing, and Empirical Software Engineering.

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Table of Contents

• Introduction
• Lab Files
  • 1. Computer Networks
  • 2. Natural Language Processing (NLP)
  • 3. Software Requirement Engineering
  • 4. Software Testing
  • 5. Empirical Software Engineering
• Installation
• Usage
• Contributing
• License

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Introduction

This repository serves as a comprehensive collection of DTU's lab files for various Computer Science and Engineering subjects. It includes well-documented assignments, coding exercises, and reports, allowing students and professionals to deepen their understanding of each subject through practical examples.

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Lab Files

1. Computer Networks

The Computer Networks section includes:

• Practical exercises on network protocols, socket programming, and network simulation tools.
• Projects focusing on TCP/IP, UDP, and routing algorithms.
• Labs covering DNS, DHCP, HTTP, and networking security concepts.

Files:

• network_lab1.pdf: Overview of TCP/IP protocol suite.
• network_simulations/: Code and simulations for different network topologies.

2. Natural Language Processing (NLP)

The NLP section covers:

• Text preprocessing techniques, including tokenization, stemming, and lemmatization.
• Building machine learning models for text classification, sentiment analysis, and named entity recognition (NER).
• Labs utilizing tools like NLTK, spaCy, and transformers.

Files:

• nlp_lab1.pdf: Introduction to text preprocessing.
• text_classification_code/: Python code for sentiment analysis.

3. Software Requirement Engineering

The Software Requirement Engineering section includes:

• Documentation on requirements elicitation and specification methods.
• Labs focused on use case diagrams, requirement modeling, and user stories.
• Case studies on requirement validation and management.

Files:

• requirement_lab1.pdf: Use case analysis of a software system.
• requirement_modeling_code/: Code for requirement management using UML diagrams.

4. Software Testing

The Software Testing section explores:

• Techniques like unit testing, integration testing, and system testing.
• Automation testing using Selenium and JUnit.
• Practical labs on test case generation, bug tracking, and test coverage analysis.

Files:

• testing_lab1.pdf: Introduction to manual and automated testing.
• automation_testing_code/: Selenium test scripts for web applications.

5. Empirical Software Engineering

The Empirical Software Engineering section includes:

• Labs on empirical methods to evaluate software development processes.
• Case studies analyzing software metrics, defect tracking, and performance evaluation.
• Practical application of statistical tools for software data analysis.

Files:

• empirical_lab1.pdf: Empirical study on software metrics.
• empirical_analysis_code/: Python scripts for statistical analysis.

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Installation

To run the code files, follow these instructions:

1. Clone the repository:

   git clone https://github.com/techysanoj/dtu-lab-file