COPILOT STOPS AT CODE // ASSIGNDONE FINISHES THE LAB

COPILOT AUTOCOMPLETES. YOU STILL DO THE REST.

GitHub Copilot or Cursor suggest code inside your editor. You still have to set up compilers, execute the scripts, debug runtime errors, capture terminal screenshots, and manually format a word document. That's not automation.

ASSIGNDONE COMPILES, RUNS, CAPTURES SCREENSHOTS, AND FORMATS
IDE VS SANDBOX

10 STEPS vs 2 STEPS

Compare the manual compilation loop with Copilot vs the hands-free generation with AssignDone.

COPILOT WORKFLOW
01Open IDE (VS Code, Cursor, CLion)
02Trigger Copilot autocomplete suggestion
03Tab to accept, manually fix code issues
04Configure local compiler, JDK, Python, or GCC
05Compile and run program in the terminal
06Fix segmentation faults or import errors
07Take snippets/screenshots of execution logs
08Open MS Word / Google Docs
09Paste code blocks and screenshots
10Write Aim, Theory, and format margins manually

STILL A MANUAL LAB CYCLE.

ASSIGNDONE WORKFLOW
1

UPLOAD ASSIGNMENT BRIEF

Upload your lab PDF, instructions, or paste the text

2

DOWNLOAD COMPLETE DOCX

Sandbox runtime compiles, executes, snaps output, and builds the Word doc automatically

10 MINUTES. ZERO BUILD TIME.

VISUAL DIFFERENCE

IDE SUGGESTION vs READY LAB REPORT

WHAT COPILOT GIVES YOU
binary_search.py

# Implement Binary Search algorithm in Python

def

binary_search(arr, x):

# Copilot suggestion (Press Tab to Accept)

low = 0

high = len(arr) - 1

while low <= high:

mid = (high + low) // 2

if arr[mid] < x:

low = mid + 1

elif arr[mid] > x:

high = mid - 1

else:

return mid

return -1

Ctrl + Enter to open panelsGithub Copilot: Ready

CODE SNIPPET ONLY. YOU MUST EXECUTE AND BUILD DOCS.

WHAT ASSIGNDONE GIVES YOU
BINARY_SEARCH_LAB_REPORT.DOCX
Name
Rahul Mehta
Roll No
CS-2024-047
Subject
Analysis of Algorithms Lab
Date
08 June 2026

AIM

To implement the Binary Search algorithm in Python, execute the program with search inputs, and analyze its time complexity in typical cases.

THEORY

Binary Search is a search algorithm that finds the position of a target value within a sorted array. It compares the target value to the middle element of the array. If they are not equal, the half in which the target cannot lie is eliminated and the search continues on the remaining half. Time complexity: O(log n).

PROCEDURE

  1. Ensure the input array is sorted.
  2. Find the midpoint of the search interval.
  3. If target matches midpoint value, return index.
  4. If target is less than midpoint, search lower half.
  5. If target is greater than midpoint, search upper half.

RESULTS & EXECUTION PROOF

$ python binary_search.py

Sorted Array: [1, 3, 5, 7, 9, 11, 13, 15, 17]

Search Target: 7

Target found at index: 3

Search Target: 10

Target not found in array (returned -1)

Isolated sandbox screenshot captured automatically

READY-TO-SUBMIT REPORT WITH REAL SANDBOX PROOFS.

TECHNICAL MATRIX

FEATURE COMPARISON

CAPABILITY
GITHUB COPILOT
ASSIGNDONE
CODE RUNNER
None — you build and execute locally
Integrated isolated sandboxes
COMPILATION PROOFS
You take terminal clips manually
Captured terminal screenshots
WORD REPORT GENERATION
No — you write in Word/Docs
Complete styled DOCX generation
DOCUMENT LAYOUT
Manual styling and layout structure
Aim, Theory, Procedure, Results templates
ERROR DEBUG LOOP
Suggests solutions, you run again
Autonomously fixes and re-runs sandbox
GRADE ALIGNED TEMPLATE
Requires manual prompt engineering
Built-in academic style header tables
WORK REQUIRED
Interactive pairing & manual assembly
Upload brief and download DOCX
DECISION
YOU ARE THE COMPILER
BOT HANDLES ALL
QUIT MANUALLY COMPILING

SAVE THE HOUR OF DOCUMENT ASSEMBLY

Writing code is only 20% of a CS lab. Setting up compilation environment, executing test cases, capturing logs, and formatting report tables takes up the rest. Stop wasting time inside the IDE.

TRY ASSIGNDONE FOR FREE
1 FREE CREDIT ON SIGNUPNO SUBSCRIPTIONCREDITS NEVER EXPIRE