Order tracking state machine in LLD - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define the initial state of the order.

LLD

class OrderStateMachine:
    def __init__(self):
        self.state = "[1]"

Drag options to blanks, or click blank then click option'

ACreated

BShipped

CDelivered

DCancelled

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'Shipped' or 'Delivered' as the initial state.

The initial state of an order is usually 'Created' when it is first placed.

2fill in blank

medium

Complete the code to add a method that changes the state to 'Shipped'.

LLD

def ship_order(self):
    if self.state == "Created":
        self.state = "[1]"

Drag options to blanks, or click blank then click option'

AReturned

BDelivered

CShipped

DCancelled

Attempts:

3 left

💡 Hint

Common Mistakes

Setting the state directly to 'Delivered' without shipping.

When an order is shipped, the state changes from 'Created' to 'Shipped'.

3fill in blank

hard

Fix the error in the method that cancels an order only if it is not yet shipped.

LLD

def cancel_order(self):
    if self.state == "[1]":
        self.state = "Cancelled"

Drag options to blanks, or click blank then click option'

AShipped

BDelivered

CReturned

DCreated

Attempts:

3 left

💡 Hint

Common Mistakes

Allowing cancellation after the order is shipped.

An order can only be cancelled if it is still in the 'Created' state, not after it has been shipped.

4fill in blank

hard

Fill both blanks to define a method that marks the order as delivered only if it is shipped.

LLD

def deliver_order(self):
    if self.state == "[1]":
        self.state = "[2]"

Drag options to blanks, or click blank then click option'

AShipped

BCreated

CDelivered

DCancelled

Attempts:

3 left

💡 Hint

Common Mistakes

Changing state from 'Created' directly to 'Delivered'.

The order can be marked as 'Delivered' only if it is currently 'Shipped'.

5fill in blank

hard

Fill both blanks to implement a method that returns True if the order is in a final state (Delivered or Cancelled).

LLD

def is_final_state(self):
    return self.state in ["[1]", "[2]"]

Drag options to blanks, or click blank then click option'

ACreated

BShipped

CDelivered

DCancelled

Attempts:

3 left

💡 Hint

Common Mistakes

Including 'Created' or 'Shipped' as final states.

The final states are 'Delivered' and 'Cancelled'.

Practice

1. What is the main purpose of an Order Tracking State Machine in system design?

easy

A. To manage user authentication and sessions

B. To store customer payment information securely

C. To calculate the total price of an order

D. To represent the different stages an order goes through and control transitions

Solution

1. Step 1: Understand the role of state machines

   A state machine models states and transitions between them based on events.

2. Step 2: Apply to order tracking context

   In order tracking, it shows order stages like placed, shipped, delivered, and controls valid moves.

3. Final Answer:

   To represent the different stages an order goes through and control transitions -> Option D

4. Quick Check:

   State machine = stages and transitions [OK]

Hint: Think: states show progress steps, transitions move between them [OK]

Common Mistakes:

• Confusing state machine with data storage
• Mixing order calculation with state control
• Assuming it handles user login

2. Which of the following is the correct way to define a state transition in a state machine for order tracking?

easy

A. transition('delivered', 'placed', event='return_order')

B. transition('placed', 'shipped', event='ship_order')

C. transition('shipped', 'placed', event='cancel_order')

D. transition('cancelled', 'delivered', event='refund')

Solution

1. Step 1: Identify valid order flow transitions

   Orders move forward: placed -> shipped -> delivered; backward or invalid transitions are not typical.

2. Step 2: Check each option's direction and event

   transition('placed', 'shipped', event='ship_order') correctly moves from placed to shipped on ship_order event; others reverse or skip states incorrectly.

3. Final Answer:

   transition('placed', 'shipped', event='ship_order') -> Option B

4. Quick Check:

   Valid forward transition = transition('placed', 'shipped', event='ship_order') [OK]

Hint: Transitions should follow logical order flow forward [OK]

Common Mistakes:

• Defining backward transitions without valid reason
• Skipping intermediate states
• Using wrong event names

3. Given this simplified state machine code snippet:

state = 'placed'
event = 'ship_order'
if state == 'placed' and event == 'ship_order':
    state = 'shipped'
elif state == 'shipped' and event == 'deliver_order':
    state = 'delivered'
print(state)

What will be the output if event = 'deliver_order' when state = 'placed'?

medium

A. shipped

B. delivered

C. placed

D. error

Solution

1. Step 1: Check condition for event 'deliver_order' when state is 'placed'

   The first if checks for 'ship_order' event; it does not match 'deliver_order'. The elif checks for 'shipped' state, but current state is 'placed'.

2. Step 2: Determine state after conditions

   No condition matches, so state remains unchanged as 'placed'.

3. Final Answer:

   placed -> Option C

4. Quick Check:

   No matching transition keeps state same [OK]

Hint: If no condition matches, state stays unchanged [OK]

Common Mistakes:

• Assuming event triggers transition regardless of current state
• Confusing elif with else
• Expecting error without exception handling

4. Identify the bug in this order tracking state machine snippet:

state = 'shipped'
event = 'cancel_order'
if state == 'placed' and event == 'cancel_order':
    state = 'cancelled'
elif state == 'shipped' and event == 'cancel_order':
    print('Cannot cancel after shipping')
else:
    state = 'cancelled'
print(state)

medium

A. The else block cancels order even after shipping

B. Missing transition from 'placed' to 'shipped'

C. No print statement for cancellation confirmation

D. State variable is not updated correctly for 'placed' state

Solution

1. Step 1: Analyze conditions for state 'shipped' and event 'cancel_order'

   The if does not match. The elif matches, prints 'Cannot cancel after shipping' but leaves state unchanged. However, if event were different (e.g., 'deliver_order') with state='shipped', if and elif fail, else wrongly sets state='cancelled'.

2. Step 2: Identify why this is a bug

   The else acts as a catch-all, allowing cancellation of shipped orders for unhandled events, contradicting the intent to prevent cancellation after shipping.

3. Final Answer:

   The else block cancels order even after shipping -> Option A

4. Quick Check:

   Else wrongly cancels unhandled shipped cases [OK]

Hint: Else block can override specific conditions--check carefully [OK]

Common Mistakes:

• Ignoring else block effects
• Assuming print prevents state change
• Not testing all branches

5. You need to design an order tracking state machine that handles normal flow and exceptions like cancellation and returns. Which design approach best ensures scalability and clarity?

hard

A. Model states hierarchically with sub-states for exceptions and normal flow

B. Use a single flat state list with many transitions for all cases

C. Handle exceptions outside the state machine with separate logic

D. Use only two states: 'active' and 'closed' to simplify design

Solution

1. Step 1: Understand complexity of order states

   Orders have normal states (placed, shipped, delivered) and exceptions (cancelled, returned) which can be grouped logically.

2. Step 2: Evaluate design approaches for scalability and clarity

   Hierarchical states allow grouping related states, reducing complexity and improving maintainability compared to flat or oversimplified models.

3. Final Answer:

   Model states hierarchically with sub-states for exceptions and normal flow -> Option A

4. Quick Check:

   Hierarchical states = scalable and clear [OK]

Hint: Group related states hierarchically for clarity and scale [OK]

Common Mistakes:

• Using flat states causing many transitions
• Ignoring exceptions in state machine
• Oversimplifying states losing detail