India · R2021
Anna University, Chennai
31 lab practicals for the Anna University syllabus.
Anna University’s Regulations 2021 B.E. CSE, from Python and C programming to the data structures and OOP laboratories. 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.E. Computer Science and Engineering. Scheme: Regulations 2021. Open a course to see its practical units and the lab lesson GroutCode ships for each.
Semester 1
2 courses6 lab lessonsPython- GE3151Python
Problem Solving and Python Programming
5
lessons
- Algorithmic problem solving: minimum, card insertion, number guessing and Towers of Hanoi
- Values, types and expressions: swapping, circulating, distances and roots
- 1Algorithmic problem solving: minimum, card insertion, number guessing and Towers of HanoiUnit I · Computational Thinking and Problem Solving
- 2Values, types and expressions: swapping, circulating, distances and rootsUnit II · Data Types, Expressions, Statements
- 3Control flow, fruitful functions and strings: grades, square roots, GCD, searchingUnit III · Control Flow, Functions, Strings
- 4Lists, tuples and dictionaries: sorting, histograms, a marks statement and a retail billUnit IV · Lists, Tuples, Dictionaries
- 5Files, exceptions and command-line arguments: word count, file copy and input validationUnit V · Files, Modules, Packages
- GE3171Python
Problem Solving and Python Programming Laboratory
1
lesson
- Python lab exercises: billing, series, patterns, collections, strings, files and exceptions
- 1Python lab exercises: billing, series, patterns, collections, strings, files and exceptionsUnit LAB · Problem Solving and Python Programming Laboratory
Semester 2
2 courses6 lab lessonsC- CS3251C
Programming in C
5
lessons
- C basics: expressions, operators, decisions, switch with enums, and loops
- Arrays and strings in C: matrices, string operations, selection sort and searching
- 1C basics: expressions, operators, decisions, switch with enums, and loopsUnit I · Basics of C Programming
- 2Arrays and strings in C: matrices, string operations, selection sort and searchingUnit II · Arrays and Strings
- 3Functions and pointers in C: recursion, pass by reference, pointer arithmetic and arrays of pointersUnit III · Functions and Pointers
- 4Structures and unions in C: student records, a singly linked list, and storage classesUnit IV · Structures and Union
- 5A student records file — sequential text, random-access binary and argvUnit V · File Processing
- CS3271C
Programming in C Laboratory
1
lesson
- C lab record — twelve experiments from switch to files
- 1C lab record — twelve experiments from switch to filesUnit LAB · Programming in C Laboratory
Semester 3
4 courses11 lab lessonsCJava- CS3301C
Data Structures
5
lessons
- The List ADT — arrays, singly, doubly and circular lists, polynomials and radix sort
- Stacks and queues — expression parsing, recursion removal, scheduling
- 1The List ADT — arrays, singly, doubly and circular lists, polynomials and radix sortUnit I · Lists
- 2Stacks and queues — expression parsing, recursion removal, schedulingUnit II · Stacks and Queues
- 3Trees — BST, traversals, expression trees, AVL rotations and a binary heapUnit III · Trees
- 4Graph algorithms on an adjacency matrix — traversal, ordering, shortest paths and spanning treesUnit IV · Multiway Search Trees and Graphs
- 5Searching, sorting and hashing — five sorts, two searches and a hash table that rehashes itselfUnit V · Searching, Sorting and Hashing Techniques
- CS3311C
Data Structures Laboratory
1
lesson
- The data structures lab in C: stacks and queues to AVL trees, Dijkstra and hashing
- 1The data structures lab in C: stacks and queues to AVL trees, Dijkstra and hashingUnit LAB · Data Structures Laboratory
- CS3381Java
Object Oriented Programming Laboratory
1
lesson
- The OOP lab in Java: searches, stack and queue classes, payroll, shapes, exceptions, threads and files
- 1The OOP lab in Java: searches, stack and queue classes, payroll, shapes, exceptions, threads and filesUnit LAB · Object Oriented Programming Laboratory
- CS3391Java
Object Oriented Programming
4
lessons
- Grades, fractions and bank accounts — Java fundamentals, classes and static members
- A library catalogue — overloading, inheritance, abstract classes, interfaces and nested classes
- 1Grades, fractions and bank accounts — Java fundamentals, classes and static membersUnit I · Introduction to OOP and Java
- 2A library catalogue — overloading, inheritance, abstract classes, interfaces and nested classesUnit II · Inheritance, Packages and Interfaces
- 3Exceptions, wrappers and threads — from try/catch to a producer-consumer bufferUnit III · Exception Handling and Multithreading
- 4Strings, generic classes and file I/O in Java: from reverseWords to a word-frequency readerUnit IV · I/O, Generics, String Handling
- 5JavaFX Event Handling, Controls and Components
Semester 4
3 courses8 lab lessonsPythonCSQL- CS3401Python
Algorithms
6
lessons
- Measuring searches, string matchers and sorts: linear to KMP and heap sort
- Graph algorithms toolkit: traversal, connectivity, MST, shortest paths, flow and matching
- 1Measuring searches, string matchers and sorts: linear to KMP and heap sortUnit I · Introduction
- 2Graph algorithms toolkit: traversal, connectivity, MST, shortest paths, flow and matchingUnit II · Graph Algorithms
- 3Design techniques: divide and conquer, dynamic programming and greedy algorithmsUnit III · Algorithm Design Techniques
- 4State space search: backtracking and branch-and-bound solversUnit IV · State Space Search Algorithms
- 5Intractability in practice: SAT reductions, approximation and randomized algorithmsUnit V · NP-Complete and Approximation Algorithm
- 6CS3401 Algorithms lab: the fifteen practical exercisesUnit LAB · Practical Exercises
- CS3461C
Operating Systems Laboratory
1
lesson
- OS lab in C: CPU schedulers, Banker's algorithm, paging, page replacement, file allocation and disk scheduling
- 1OS lab in C: CPU schedulers, Banker's algorithm, paging, page replacement, file allocation and disk schedulingUnit LAB · Operating Systems Laboratory
- CS3481SQL
Database Management Systems Laboratory
1
lesson
- DBMS lab in SQLite: constraints, joins, subqueries, transactions, triggers, views, JSON documents and an EMI batch
- 1DBMS lab in SQLite: constraints, joins, subqueries, transactions, triggers, views, JSON documents and an EMI batchUnit LAB · Database Management Systems Laboratory
The full 71-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 Anna University, Chennai. 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 Anna University R2021?
Yes. GroutCode ships the transcribed Anna University R2021 for B.E. Computer Science and Engineering — 71 courses — with 31 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 Anna University practicals use?
C (13 lessons), Python (12 lessons), Java (5 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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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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AKTU
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AKTU Lucknow’s B.Tech CSE for the 2026-27 session: C programming, data structures, Java OOP and the operating system lab.
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