Difference between revisions of "Spring 2025: Software Engineering Lab"

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==''' Guidelines'''==
 
==''' Guidelines'''==
−
* As per DUCS guidelines [http://mkbhandari.com/mkwiki/data/fall2024/dm/DMGuideline.pdf  '''DSE: Data Mining''']
+
* As per DUCS guidelines [http://mkbhandari.com/mkwiki/data/guidelines/SEGuidelines.pdf  '''DSE: Software Engineering''']
  
−
== '''Lab 0: Getting Started''' ( week of 05<sup>th</sup> & 12<sup>th</sup >  August 2024 ) ==
+
== '''Lab 0: Getting Started''' ( week of Jan 2025 ) ==
 
{| class="wikitable" style="text-align: justify; width: 100%";  
 
{| class="wikitable" style="text-align: justify; width: 100%";  
 
|-
 
|-
−
! Q. NO.   
+
! Task. No.   
−
! Program 
+
! Task
−
! Practical No. 
+
! Outcome
 
! Remarks
 
! Remarks
 
|-
 
|-
 
| style="width: 8%"  | 1  
 
| style="width: 8%"  | 1  
−
| style="width: 60%" | https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial1/tutorial1.html
+
| style="width: 60%" | Overview of the Software Engineering Lab Outcomes/Target Projects
−
| style="width: 15%" | Practice Set No. 1
+
| style="width: 15%" | 
−
| Introduction to Python
+
| Sample Project Report
 +
|}
 +
 
 +
 
 +
== '''Lab 1:''' ( week of Jan 2025 ) ==
 +
{| class="wikitable" style="text-align: justify; width: 100%";
 +
|-
 +
! Task No.  
 +
! Task
 +
! Outcome 
 +
! Remarks
 +
|-
 +
| style="width: 8%"  | 2
 +
| style="width: 60%" | Problem Statement
 +
| style="width: 15%" |  Chapter 1
 +
|
 +
|}
 +
 
 +
 
 +
== '''Lab 2:''' ( week of Feb 2025 ) ==
 +
{| class="wikitable" style="text-align: justify; width: 100%";
 +
|-
 +
! Task No.  
 +
! Task
 +
! Outcome 
 +
! Remarks
 +
|-
 +
| style="width: 8%"  | 3
 +
| style="width: 60%" | Process Model
 +
| style="width: 15%" | Chapter 2
 +
|
 +
|}
 +
 
 +
 
 +
== '''Lab 3:''' ( week of Feb 2025 ) ==
 +
{| class="wikitable" style="text-align: justify; width: 100%";
 +
|-
 +
! Task No.  
 +
! Task
 +
! Outcome 
 +
! Remarks
 +
|-
 +
| style="width: 8%"  | 4
 +
| style="width: 60%" | Rquirement Analysis & Modelling
 +
| style="width: 15%" | Chapter 3
 +
|
 +
|}
 +
 
 +
 
 +
== '''Lab 4:''' ( week of Feb 2025 ) ==
 +
{| class="wikitable" style="text-align: justify; width: 100%";
 
|-
 
|-
−
| 2 || https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial2/tutorial2.html || Practice Set No. 2 || Introduction to Numpy and Pandas
+
! Task No.  
 +
! Task
 +
! Outcome  
 +
! Remarks
 
|-
 
|-
−
| 3 || https://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial3/tutorial3.html || Practice Set No. 3 || Data Exploration
+
| style="width: 8%"  | 5
 +
| style="width: 60%" | Software Requirement Specification(SRS)
 +
| style="width: 15%" | Chapter 4
 +
|  
 
|}
 
|}
  
−
== '''Lab 1:''' ( week of 19<sup>th</sup>  &  26<sup>th</sup>  August 2024 ) ==
+
 
 +
== '''Lab 5:''' ( week of Feb 2025 ) ==
 
{| class="wikitable" style="text-align: justify; width: 100%";  
 
{| class="wikitable" style="text-align: justify; width: 100%";  
 
|-
 
|-
−
! Q. NO.
+
! Task No.  
−
! Program 
+
! Task
−
! Practical No.  
+
! Outcome  
 
! Remarks
 
! Remarks
 
|-
 
|-
−
| style="width: 8%"  | 1
+
| style="width: 8%"  | 6
−
| style="width: 60%" | Apply data cleaning techniques on any dataset (e.g. Chronic Kidney Disease dataset from UCI repository). Techniques may include handling missing values, outliers and inconsistent values. Also, a set of validation rules may be specified for the particular dataset and validation checks performed.
+
| style="width: 60%" | Estimations
−
| style="width: 15%" |  Practical No. 1
+
| style="width: 15%" |  Chapter 5
−
| '''Dataset:''' [http://mkbhandari.com/mkwiki/data/fall2024/dm/datasets/kidneyDisease.csv '''kidneyDisease.csv'''] <br>
+
|
−
'''Download from Kaggle:''' [https://www.kaggle.com/datasets/mansoordaku/ckdisease Chronic KIdney Disease dataset] <br>
+
|}
−
'''Tutorial:''' [https://www.kaggle.com/code/alexisbcook/handling-missing-values#How-many-missing-data-points-do-we-have? Tutorial on Handling Missing values]
+
 
 +
 
 +
== '''Lab 6:''' ( week of March 2025 ) ==
 +
{| class="wikitable" style="text-align: justify; width: 100%";
 +
|-
 +
! Task No.  
 +
! Task
 +
! Outcome 
 +
! Remarks
 +
|-
 +
| style="width: 8%"  | 7
 +
| style="width: 60%" | Scheduling
 +
| style="width: 15%" | Chapter 6
 +
|
 +
|}
 +
 
 +
 
 +
== '''Lab 7:''' ( week of March 2025 ) ==
 +
{| class="wikitable" style="text-align: justify; width: 100%";
 +
|-
 +
! Task No.  
 +
! Task
 +
! Outcome 
 +
! Remarks
 +
|-
 +
| style="width: 8%"  | 8
 +
| style="width: 60%" | Risk Management
 +
| style="width: 15%" | Chapter 7
 +
|
 +
|}
 +
 
 +
 
 +
== '''Lab 8:''' ( week of April 2025 ) ==
 +
{| class="wikitable" style="text-align: justify; width: 100%";
 +
|-
 +
! Task No.  
 +
! Task
 +
! Outcome 
 +
! Remarks
 +
|-
 +
| style="width: 8%"  | 9
 +
| style="width: 60%" | Design
 +
| style="width: 15%" |  Chapter 8
 +
|
 
|}
 
|}
  
−
== '''Lab 2:''' ( week of 2<sup>nd</sup> &  9<sup>th</sup>  September 2024 ) ==
+
 
 +
== '''Lab 9:''' ( week of April 2025 ) ==
 
{| class="wikitable" style="text-align: justify; width: 100%";  
 
{| class="wikitable" style="text-align: justify; width: 100%";  
 
|-
 
|-
−
! Q. NO.
+
! Task No.  
−
! Program 
+
! Task
−
! Practical No.  
+
! Outcome  
 
! Remarks
 
! Remarks
 
|-
 
|-
−
| style="width: 8%"  | 1
+
| style="width: 8%"  | 10
−
| style="width: 60%" | Apply data pre-processing techniques such as standardization/normalization, transformation, aggregation, discretization/binarization, sampling etc. on any dataset
+
| style="width: 60%" | Coding
−
| style="width: 15%" |  Practical No. 2
+
| style="width: 15%" |  Chapter 9
−
| '''Dataset:''' [http://mkbhandari.com/mkwiki/data/fall2024/dm/datasets/rain.csv '''rain.csv'''] <br>
+
|  
−
'''Download from data.gov.in:''' [https://www.data.gov.in/catalog/rainfall-india Rainfall in India]
 
 
|}
 
|}
  
−
== '''Lab 3:''' ( week of 16<sup>th</sup>, 23<sup>rd</sup> &  30<sup>th</sup>September 2024 ) ==
+
 
 +
== '''Lab 10:''' ( week of April 2025 ) ==
 
{| class="wikitable" style="text-align: justify; width: 100%";  
 
{| class="wikitable" style="text-align: justify; width: 100%";  
 
|-
 
|-
−
! Q. NO.
+
! Task No.  
−
! Program 
+
! Task
−
! Practical No.  
+
! Outcome  
 
! Remarks
 
! Remarks
 
|-
 
|-
−
| style="width: 8%"  | 1
+
| style="width: 8%"  | 11
−
| style="width: 60%" | Writing/Review of Chapter 1, Chapter 3, and Chapter 4 of Project Report
+
| style="width: 60%" | Testing
−
| style="width: 15%" |  Project Work
+
| style="width: 15%" |  Chapter 10
 
|  
 
|  
 
|}
 
|}
  
−
== '''Lab 4:''' ( week of 7<sup>th</sup> October 2024 ) ==
+
 
 +
== '''Final Lab:''' ( week of April 2025 ) ==
 
{| class="wikitable" style="text-align: justify; width: 100%";  
 
{| class="wikitable" style="text-align: justify; width: 100%";  
 
|-
 
|-
−
! Q. NO.
+
! Task No.  
−
! Program 
+
! Task
−
! Practical No.  
+
! Outcome  
 
! Remarks
 
! Remarks
 
|-
 
|-
−
| style="width: 8%"  | 1
+
| style="width: 8%"  | 12
−
| style="width: 60%" | Apply simple K-means algorithm for clustering any dataset. Compare the performance of clusters by varying the algorithm parameters. For a given set of parameters, plot a line graph depicting MSE obtained after each iteration.
+
| style="width: 60%" | Project Presentations
−
| style="width: 15%" |  Practical No. 3
+
| style="width: 15%" |   
−
| '''Dataset:''' [http://mkbhandari.com/mkwiki/data/fall2024/dm/datasets/Mall_Customers.csv '''Mall_Customers.csv'''] <br>
+
|  
−
'''Download from data from kaggle:''' [https://www.kaggle.com/datasets/vjchoudhary7/customer-segmentation-tutorial-in-python Mall Customer Segmentation Data]
 
 
|}
 
|}
 +
  
 
== '''Projects''' ==
 
== '''Projects''' ==
Line 95: Line 197:
 
|-
 
|-
 
| style="width: 8%"  | 1  
 
| style="width: 8%"  | 1  
−
| style="width: 45%" | Title 1
+
| style="width: 35%" | Auction Website
−
| style="width: 25%" |   
+
| style="width: 35%" |   
−
# XYZ
+
# Quazi Bakhtiyar Ali (23/35079)
−
# XYZ
+
# Shahnawaz Hussain (23/35078)
−
# XYZ
+
# Vedansh Joharwal (23/35044)
−
# XYZ
+
# Azeemuddin Aziz (23/35099)
 +
|
 +
* Report:
 +
* Project Presentation:
 +
|-
 +
|2|| Fitness Management Website ||
 +
# Ishan Tomar (23/35060)
 +
# Yashika (23/35072)
 +
# Diya (23/35058)
 +
# Yogesh (23/35076)
 
|  
 
|  
 
* Report:
 
* Report:
 
* Project Presentation:
 
* Project Presentation:
 
|-
 
|-
−
|2|| Title 2||  
+
|3|| Library Management system ||  
−
# XYZ
+
# Navya Rattan (23/35035)
−
# XYZ
+
# Dishita Dhingra (23/35050)
−
# XYZ
+
# Harshit Raj (23/35025)
−
# XYZ
+
# Rashim (23/35063)
−
 
 
 
|  
 
|  
−
* Dataset:
 
 
* Report:
 
* Report:
 
* Project Presentation:
 
* Project Presentation:
 
|-
 
|-
−
|3|| Title 3 ||  
+
|4|| AC Service web App ||  
−
# '''Himanshu Kumar (25016)'''
+
# Saksham Raj (23/35081)
−
# Kanan Pal (25072)
+
# Harsh (23/35017)
−
# Khushboo Yadav (25082)
+
# Hemant (23/35055)
−
# Diksha Joshi (25091)
+
# Nikhil (23/35095)
 
|  
 
|  
−
* Dataset:
 
 
* Report:
 
* Report:
 
* Project Presentation:
 
* Project Presentation:
 
|-
 
|-
−
|4|| Title 4 ||  
+
|5|| Farming Assistance Website ||  
−
# Arihant (25003)
+
# Bittu Raj (23/35084)
−
# '''Ayush Pundir (25027)'''
+
# Vidhi (23/35073)
−
# Pratyush (25060)
+
# Harshit Prasad (23/35026)
−
# Ashish (25066)
+
# Ragini (23/35018)
 
|  
 
|  
−
* Dataset:
 
 
* Report:
 
* Report:
 
* Project Presentation:
 
* Project Presentation:
 
|-
 
|-
−
|5|| Title 5 ||  
+
|6|| Anonymous Chat Web App||  
−
# Vidhan (25044)
+
# Sumit Pandey (23/35092)
−
# '''Sandeep Kumar Sharma (25047)'''
+
# Lucky Tiwari (23/35041)
−
# Ayushman Pandey (25094)
+
# Pranjal Singh (23/35005)
−
# Tanishk Panchal (25095)
+
# Devesh Gupta (23/35009)
 
|  
 
|  
−
* Dataset:
 
 
* Report:
 
* Report:
 
* Project Presentation:
 
* Project Presentation:
 
|-
 
|-
−
|6|| Title 6||  
+
|7|| Expenses Tracker and Predictor||  
−
# Devesh Chauhan (25011)
+
# Gourav Joshi(23/35032)
−
# Shatrughan  (25084)
+
# Kavya (23/35040)
−
# Om Ranjan (25085)
+
# Kanishka Singhal (23/35022)
−
# '''Aman Sagar (25086)'''
+
# Reeshu Jangir (23/35053)
 
|  
 
|  
−
* Dataset:
 
 
* Report:
 
* Report:
 
* Project Presentation:
 
* Project Presentation:
 
|-
 
|-
−
|7|| Olympic Data Analysis and Prediction ||  
+
|8|| Contract farming||  
−
# Kusum (25002)
+
# Ashish sharma (23/35059)
−
# '''Aditya Kumar (25012)'''
+
# Ashish negi (23/35013)
−
# Divyanshi (25021)
+
# Rudransh (23/35034)
−
# Tushar Rana (25064)
+
# Akanksha (23/35038)
 
|  
 
|  
−
* Dataset:
 
 
* Report:
 
* Report:
 
* Project Presentation:
 
* Project Presentation:
 
|-
 
|-
−
|8|| Credit Card Fraud Detection ||  
+
|9|| Movie Recommendation Platform||  
−
# Ritesh Dhawan (25037)
+
# Md Jishan (23/xxxxx)
−
# Bitthal Varshney (25041)
+
# Jaydev Sarkar (23/xxxxx)
−
# Ansh Raj (25081)
 
−
# '''Uday Raj Verma (25083)'''
 
−
# Astitwa Rawat (25088)
 
 
|  
 
|  
−
* Dataset:
 
 
* Report:
 
* Report:
 
* Project Presentation:
 
* Project Presentation:
 
|-
 
|-
−
|9|| CreditMap: Exploring Credit Score Patterns through Data Mining ||  
+
|10|| Promise Check India||  
−
# Himanshu Singh (25017)
+
# Saksham Raj (23/35081)
−
# '''Garvit Kumar (25018)'''
+
# Harsh (23/35017)
−
# Mayank  (25022)
+
# Hemant (23/35055)
−
# Abhishek Kumar Singh(25032)
+
# Nikhil (23/35095)
 
|  
 
|  
−
* Dataset:
 
 
* Report:
 
* Report:
 
* Project Presentation:
 
* Project Presentation:
 
|-
 
|-
−
|10|| Movie Recommendation System ||  
+
|11|| Women’s health and well being||  
−
# Tanya Agrahari (25030)
+
# Anukriti (23/35051)
−
# Prakash Mishra (25035)
+
# ⁠Manvi (23/35077)
−
# '''Adarsh Singh (25074)'''
+
# Geetanshi (23/35047)
−
# Shivam Verma (25078)
+
# Mohammad Shaanu (23/35087)
 
|  
 
|  
−
* Dataset:
 
 
* Report:
 
* Report:
 
* Project Presentation:
 
* Project Presentation:
 
|-
 
|-
−
|11|| Wine Quality Prediction ||  
+
|12|| Canteen Food Review App||  
−
# '''Shivam Soni (250xx)'''
+
# Shivam kumar 23/35028
−
# ⁠Kashif (250xx)
+
# Harsh Singh 23/35012
−
# Akash Pathak (250xx)
+
# Dev sorout 23/35096
−
# ⁠Priyanshu Sachan (250xx)
 
 
|  
 
|  
−
* Dataset:
 
 
* Report:
 
* Report:
 
* Project Presentation:
 
* Project Presentation:
 
|}
 
|}

Latest revision as of 22:41, 13 February 2025

Instructions

  • Please be on time to avoid the Attendance Penalty.
  • Please put your mobile phone in the Silent Mode.
  • Each lab assignment needs to be submitted in the Google Classroom for evaluation(will be notified in the GC lab-wise, submit before the deadline).
  • Turn off(shut down) your assigned computer and arrange the chair before you leave the lab.

Guidelines

Lab 0: Getting Started ( week of Jan 2025 )

Task. No. Task Outcome Remarks
1 Overview of the Software Engineering Lab Outcomes/Target Projects Sample Project Report


Lab 1: ( week of Jan 2025 )

Task No. Task Outcome Remarks
2 Problem Statement Chapter 1


Lab 2: ( week of Feb 2025 )

Task No. Task Outcome Remarks
3 Process Model Chapter 2


Lab 3: ( week of Feb 2025 )

Task No. Task Outcome Remarks
4 Rquirement Analysis & Modelling Chapter 3


Lab 4: ( week of Feb 2025 )

Task No. Task Outcome Remarks
5 Software Requirement Specification(SRS) Chapter 4


Lab 5: ( week of Feb 2025 )

Task No. Task Outcome Remarks
6 Estimations Chapter 5


Lab 6: ( week of March 2025 )

Task No. Task Outcome Remarks
7 Scheduling Chapter 6


Lab 7: ( week of March 2025 )

Task No. Task Outcome Remarks
8 Risk Management Chapter 7


Lab 8: ( week of April 2025 )

Task No. Task Outcome Remarks
9 Design Chapter 8


Lab 9: ( week of April 2025 )

Task No. Task Outcome Remarks
10 Coding Chapter 9


Lab 10: ( week of April 2025 )

Task No. Task Outcome Remarks
11 Testing Chapter 10


Final Lab: ( week of April 2025 )

Task No. Task Outcome Remarks
12 Project Presentations


Projects

Team No. Project Title Team Members Outcomes/Remarks
1 Auction Website
  1. Quazi Bakhtiyar Ali (23/35079)
  2. Shahnawaz Hussain (23/35078)
  3. Vedansh Joharwal (23/35044)
  4. Azeemuddin Aziz (23/35099)
  • Report:
  • Project Presentation:
2 Fitness Management Website
  1. Ishan Tomar (23/35060)
  2. Yashika (23/35072)
  3. Diya (23/35058)
  4. Yogesh (23/35076)
  • Report:
  • Project Presentation:
3 Library Management system
  1. Navya Rattan (23/35035)
  2. Dishita Dhingra (23/35050)
  3. Harshit Raj (23/35025)
  4. Rashim (23/35063)
  • Report:
  • Project Presentation:
4 AC Service web App
  1. Saksham Raj (23/35081)
  2. Harsh (23/35017)
  3. Hemant (23/35055)
  4. Nikhil (23/35095)
  • Report:
  • Project Presentation:
5 Farming Assistance Website
  1. Bittu Raj (23/35084)
  2. Vidhi (23/35073)
  3. Harshit Prasad (23/35026)
  4. Ragini (23/35018)
  • Report:
  • Project Presentation:
6 Anonymous Chat Web App
  1. Sumit Pandey (23/35092)
  2. Lucky Tiwari (23/35041)
  3. Pranjal Singh (23/35005)
  4. Devesh Gupta (23/35009)
  • Report:
  • Project Presentation:
7 Expenses Tracker and Predictor
  1. Gourav Joshi(23/35032)
  2. Kavya (23/35040)
  3. Kanishka Singhal (23/35022)
  4. Reeshu Jangir (23/35053)
  • Report:
  • Project Presentation:
8 Contract farming
  1. Ashish sharma (23/35059)
  2. Ashish negi (23/35013)
  3. Rudransh (23/35034)
  4. Akanksha (23/35038)
  • Report:
  • Project Presentation:
9 Movie Recommendation Platform
  1. Md Jishan (23/xxxxx)
  2. Jaydev Sarkar (23/xxxxx)
  • Report:
  • Project Presentation:
10 Promise Check India
  1. Saksham Raj (23/35081)
  2. Harsh (23/35017)
  3. Hemant (23/35055)
  4. Nikhil (23/35095)
  • Report:
  • Project Presentation:
11 Women’s health and well being
  1. Anukriti (23/35051)
  2. ⁠Manvi (23/35077)
  3. Geetanshi (23/35047)
  4. Mohammad Shaanu (23/35087)
  • Report:
  • Project Presentation:
12 Canteen Food Review App
  1. Shivam kumar 23/35028
  2. Harsh Singh 23/35012
  3. Dev sorout 23/35096
  • Report:
  • Project Presentation:
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