India · R20
Maulana Abul Kalam Azad University of Technology, West Bengal
27 lab practicals for the MAKAUT syllabus.
MAKAUT West Bengal’s B.Tech CSE (R20), from Programming for Problem Solving through data structures, algorithms and Java. Every lesson is stepped, compiled and checked by a real toolchain on your own machine — the model reviews your code afterwards, it does not decide whether you passed.
Updated
Semester by semester
Programme: B.Tech in Computer Science & Engineering. Scheme: 2020-21 curriculum (R20). Open a course to see its practical units and the lab lesson GroutCode ships for each.
Semester 2
2 courses11 lab lessonsC- ESCS201C
Programming for Problem Solving
10
lessons
- From algorithm to program — ten small number algorithms in C
- Precedence by hand — an arithmetic expression evaluator in C
- 1From algorithm to program — ten small number algorithms in CUnit 1 · Introduction to Programming
- 2Precedence by hand — an arithmetic expression evaluator in CUnit 2 · Arithmetic expressions and precedence
- 3Decisions and loops — grades, triangles, series and searches in CUnit 3 · Conditional Branching and Loops
- 4Arrays, matrices and strings — index arithmetic in CUnit 4 · Arrays
- 5Search, sort and solve — basic algorithms with their cost countedUnit 5 · Basic Algorithms
- 6A toolbox of C functions — values, arrays and library callsUnit 6 · Function
- 7Thinking recursively — from factorial to quicksortUnit 7 · Recursion
- 8Structures in C — a fraction type and a class registerUnit 8 · Structure
- 9Pointers in C — addresses, strings and a self-referential nodeUnit 9 · Pointers
- 10File handling in C — text streams and a binary record fileUnit 10 · File handling
- ESCS291C
Programming for Problem Solving Lab
1
lesson
- The PPS lab sheet — thirteen small C programs, from arithmetic to files
- 1The PPS lab sheet — thirteen small C programs, from arithmetic to filesUnit LAB · Laboratory
Semester 3
3 courses6 lab lessonsCPython- PCCCS301C
Data Structure & Algorithms
4
lessons
- Searching sorted and unsorted arrays — linear, binary, bounds and trade-offs
- Stacks and queues — expression conversion, circular buffers and a heap
- 1Searching sorted and unsorted arrays — linear, binary, bounds and trade-offsUnit 1 · Introduction and Searching
- 2Stacks and queues — expression conversion, circular buffers and a heapUnit 2 · Stacks and Queues
- 3Linked lists to AVL trees — pointers that build structuresUnit 3 · Linked Lists and Trees
- 4Six sorts, a hash table and graph traversalUnit 4 · Sorting, Hashing and Graphs
- PCCCS391C
Data Structure & Algorithm Lab
1
lesson
- A data-structures toolkit in C — arrays, stacks, queues, lists, polynomials, AVL trees and hashing
- 1A data-structures toolkit in C — arrays, stacks, queues, lists, polynomials, AVL trees and hashingUnit LAB · Laboratory Experiments
- PCCCS393Python
IT Workshop (Sci Lab/MATLAB/Python/R)
1
lesson
- Python from the ground up — conditionals, strings, collections, functions, files and exceptions
- 1Python from the ground up — conditionals, strings, collections, functions, files and exceptionsUnit LAB · Programming with Python
Semester 4
1 course1 lab lessonC- PCCCS494C
Design & Analysis Algorithm Lab
1
lesson
- The DAA lab in C — from binary search to the 15 puzzle, Bellman-Ford and minimum spanning trees
- 1The DAA lab in C — from binary search to the 15 puzzle, Bellman-Ford and minimum spanning treesUnit LAB · Laboratory Experiments
Semester 5
3 courses7 lab lessonsJavaC- PCCCS503Java
Object Oriented Programming
5
lessons
- Abstract data types in Java — a rational number and the Text ADT, from specification to rep invariant
- Encapsulation, identity and interface polymorphism in Java — accounts, money, currencies and shapes
- 1Abstract data types in Java — a rational number and the Text ADT, from specification to rep invariantUnit 1 · Abstract data types
- 2Encapsulation, identity and interface polymorphism in Java — accounts, money, currencies and shapesUnit 2 · Features of object-oriented programming
- 3Bank accounts and iterators — inheritance and the iterator pattern in JavaUnit 3 · Inheritance and design patterns
- 4A counter with undo — MVC, command objects, hand-built dispatch and garbage collectionUnit 4 · Model-view-controller pattern
- 5Generic containers, word statistics and a headless widget toolkit in JavaUnit 5 · Generic types, collections and GUIs
- PCCCS592C
Operating System Lab
1
lesson
- Processes, signals, semaphores, threads and pipes — the Unix system-call lab
- 1Processes, signals, semaphores, threads and pipes — the Unix system-call labUnit LAB · Laboratory Experiments
- PCCCS593Java
Object Oriented Programming Lab
1
lesson
- Complex numbers, students and a producer-consumer buffer — the Java OOP lab
- 1Complex numbers, students and a producer-consumer buffer — the Java OOP labUnit LAB · Lab Experiments (Use Java for programming)
Semester 6
2 courses2 lab lessonsSQLC- PCCCS691SQL
Database Management System Lab
1
lesson
- DBMS lab in SQLite: DDL, constraints, indexes, DML, queries, views, privileges, cursors and triggers on a college databa
- 1DBMS lab in SQLite: DDL, constraints, indexes, DML, queries, views, privileges, cursors and triggers on a college databaUnit LAB · Structured Query Language
- PCCCS692C
Computer Networks Lab
1
lesson
- Networks lab without a network: subnets, CRC, stop-and-wait, Go-Back-N and Selective Repeat in C
- 1Networks lab without a network: subnets, CRC, stop-and-wait, Go-Back-N and Selective Repeat in CUnit LAB · Laboratory Experiments
The full 47-course syllabus is transcribed in the app, including the theory courses. Lessons are authored against the course codes that have practical work, and the list grows with each release.
GroutCode is not affiliated with or endorsed by Maulana Abul Kalam Azad University of Technology, West Bengal. Course codes and titles are transcribed from the institution’s published scheme documents.
How a practical runs
The same five steps for every lesson, in every language.
- 1
Pick your syllabus
Choose your university or board and the semester or class you are in. The course list is the transcribed official scheme, not an approximation.
- 2
Open a lab lesson
Each lesson is a stepped practical for a specific course, with a starter file you edit and a test file you do not.
- 3
Write the code yourself
The starter has the signatures and the TODOs. You implement them in the editor, in the language your course actually uses.
- 4
Run the checks
The toolchain compiles and runs the tests — 8 to 15 of them across the lesson, one per step, so you find out which change broke what.
- 5
Get the review
Once the tests pass, the model reads your implementation and tells you the input that breaks it. It never reports the pass or fail itself.
Why the compiler grades, not the model
The obvious way to build an AI lab tool is to let the model read the student’s code and say whether it is correct. It is also the way that produces a tool nobody can trust. A model will tell you your code works when the compiler says otherwise, and it will fail you for a style it happens to dislike.
So the two jobs are split:
- The model designs the lesson, writes the starter and the tests, and — after the tests pass — reads what you actually wrote and tells you the input that breaks it.
- The toolchain decides whether it compiles and whether each step passes. That verdict is not negotiable and the model never issues it.
And why steps instead of one big task
A 40-to-60 minute practical with a single Run at the end gives a beginner one bit of feedback an hour, and it arrives after every decision has already been made. Each lesson here is 8 to 15 steps, each with its own instruction and its own check, so you find out which change broke what while you still remember making it.
Frequently asked questions
Does GroutCode cover the MAKAUT R20?
Yes. GroutCode ships the transcribed MAKAUT R20 for B.Tech in Computer Science & Engineering — 47 courses — with 27 authored lab lessons mapped to specific course codes. The syllabus was transcribed from the official documents, and the source and checksum of each one is recorded in the app.
Which languages do the MAKAUT practicals use?
C (19 lessons), Java (6 lessons), Python (1 lessons), SQL (1 lessons). The language is set per course code rather than guessed from the title, because the same subject is taught in different languages at different institutions.
Does the AI just write the practical for me?
No. The starter file has the signatures and the TODOs; you implement them. The toolchain — not the model — decides whether your code compiles and whether each step passes, so the AI cannot tell you your code works when the compiler disagrees. What it does afterwards is read your implementation and point out the input that breaks it.
Do the practicals work offline?
The lessons, the syllabus and the test runner are bundled in the app and run locally, so the compile-and-check loop works with no connection. The review step at the end uses a model, which can be a local one or a cloud one with your own key.
What do I need installed?
GroutCode detects which toolchains are present on your machine and tells you what is missing and what would fix it. You need the compiler or interpreter for the language your course uses — a C compiler, a JDK, Python, Node or SQLite.
Other syllabuses
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The 2024 scheme for Kerala’s technological university, covering CSE, IT, AI & DS and ECE from semester three onwards.
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VTU
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Karnataka’s 2022 scheme across CSE, ISE, AI-ML, AI-DS and ECE, including the dedicated lab courses.
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Anna University
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Anna University’s Regulations 2021 B.E. CSE, from Python and C programming to the data structures and OOP laboratories.
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