Technical debt management in Software Engineering - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the sentence to define technical debt.

Software Engineering

Technical debt is the [1] cost of choosing an easy solution now instead of a better approach that takes longer.

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

Aimmediate

Bfinancial

Cfuture

Doptional

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing immediate cost with future cost.

Thinking technical debt is optional or financial only.

Technical debt refers to the future cost or extra work caused by taking shortcuts or quick fixes today.

2fill in blank

medium

Complete the sentence to identify a common cause of technical debt.

Software Engineering

One common cause of technical debt is [1] pressure that forces quick delivery over quality.

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

Ateam

Bbudget

Ctechnology

Dtime

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing budget or team instead of time.

Thinking technology itself causes technical debt.

Time pressure often leads teams to choose faster but less ideal solutions, creating technical debt.

3fill in blank

hard

Fix the error in the statement about technical debt.

Software Engineering

Technical debt always [1] the software to stop working.

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

Acauses

Bdoes not cause

Cmakes

Dforces

Attempts:

3 left

💡 Hint

Common Mistakes

Assuming technical debt breaks software immediately.

Confusing technical debt with bugs or errors.

Technical debt does not always cause software to stop working; it often causes slower development or harder maintenance.

4fill in blank

hard

Fill both blanks to describe how to manage technical debt.

Software Engineering

To manage technical debt, teams should [1] it regularly and [2] time to fix it.

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

Aassess

Bignore

Callocate

Davoid

Attempts:

3 left

💡 Hint

Common Mistakes

Ignoring technical debt instead of assessing it.

Avoiding fixing technical debt completely.

Regularly assessing technical debt and allocating time to fix it helps keep software maintainable.

5fill in blank

hard

Fill all three blanks to complete the statement about technical debt impact.

Software Engineering

Technical debt can [1] development speed, [2] code quality, and [3] maintenance costs.

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

Aincrease

Breduce

Craise

Dlower

Attempts:

3 left

💡 Hint

Common Mistakes

Thinking technical debt increases speed or quality.

Confusing maintenance costs direction.

Technical debt usually reduces development speed and code quality, while raising maintenance costs.

Practice

1. What is technical debt in software engineering?

easy

A. Shortcuts or problems in code that need fixing later

B. Money spent on buying software tools

C. The total number of lines of code in a project

D. The time taken to write documentation

Solution

1. Step 1: Understand technical debt and compare options

   Technical debt refers to shortcuts or quick fixes in code that make future changes harder. Only "Shortcuts or problems in code that need fixing later" correctly describes technical debt as code problems needing fixing later.

2. Final Answer:

   Shortcuts or problems in code that need fixing later -> Option A

3. Quick Check:

   Technical debt = shortcuts needing future fixes [OK]

Hint: Think of debt as code shortcuts needing future repair [OK]

Common Mistakes:

• Confusing technical debt with project cost
• Thinking it means code size or documentation time
• Assuming it is about hardware or tools

2. Which of the following is a correct practice in managing technical debt?

easy

A. Regularly identifying and prioritizing debt items

B. Ignoring code problems until the project ends

C. Adding more features without fixing existing issues

D. Deleting all old code without review

Solution

1. Step 1: Identify good practices and evaluate options

   Managing technical debt means regularly finding and prioritizing problems to fix. Regularly identifying and prioritizing debt items describes this process correctly, while others ignore or worsen debt.

2. Final Answer:

   Regularly identifying and prioritizing debt items -> Option A

3. Quick Check:

   Good management = identify and prioritize [OK]

Hint: Good management means regular checks and prioritizing fixes [OK]

Common Mistakes:

• Thinking ignoring problems is okay
• Believing adding features solves debt
• Assuming deleting code blindly helps

3. Consider this code snippet representing technical debt items with priorities:

debt = {"bug1": 3, "bug2": 1, "bug3": 2}
# Lower number means higher priority
sorted_debt = sorted(debt.items(), key=lambda x: x[1])
print([item[0] for item in sorted_debt])

What will be the output?

medium

A. ['bug1', 'bug3', 'bug2']

B. ['bug3', 'bug1', 'bug2']

C. ['bug2', 'bug3', 'bug1']

D. ['bug2', 'bug1', 'bug3']

Solution

1. Step 1: Trace the sorting logic

   The dictionary has bug1=3, bug2=1, bug3=2 (lower number = higher priority). sorted() by value (x[1]) ascending orders: bug2 (1), bug3 (2), bug1 (3). List comprehension gets ['bug2', 'bug3', 'bug1'].

2. Final Answer:

   ['bug2', 'bug3', 'bug1'] -> Option C

3. Quick Check:

   Sorted by priority ascending = ['bug2', 'bug3', 'bug1'] [OK]

Hint: Sort by priority number ascending to find order [OK]

Common Mistakes:

• Sorting in descending order by mistake
• Confusing keys and values in sorting
• Misreading priority meaning

4. This code tries to remove fixed technical debt items from a list:

debt = ["bug1", "bug2", "bug3"]
fixed = ["bug2"]
for item in fixed:
    debt.remove(item)
print(debt)

What is the output?

medium

A. ['bug3']

B. ['bug1', 'bug2', 'bug3']

C. Error: list.remove() called on missing item

D. ['bug1', 'bug3']

Solution

1. Step 1: Trace the list removal

   Loop over fixed=["bug2"], remove "bug2" from debt=["bug1", "bug2", "bug3"], resulting in ["bug1", "bug3"], printed as ['bug1', 'bug3'].

2. Final Answer:

   ['bug1', 'bug3'] -> Option D

3. Quick Check:

   Removed fixed items = ['bug1', 'bug3'] [OK]

Hint: Removing fixed items updates list correctly [OK]

Common Mistakes:

• Expecting no change in list
• Thinking it causes an error
• Removing wrong items by mistake

5. A team has a list of technical debt items with severity scores:

debt = {"bug1": 5, "bug2": 0, "bug3": 3, "bug4": 0}
# Severity 0 means no real issue
# They want to create a new dict with only real issues
real_issues = {k: v for k, v in debt.items() if v != 0}
print(real_issues)

What will be printed?

hard

A. {'bug1': 5, 'bug2': 0, 'bug3': 3, 'bug4': 0}

B. {'bug1': 5, 'bug3': 3}

C. {'bug2': 0, 'bug4': 0}

D. {}

Solution

1. Step 1: Trace the dict comprehension filtering

   Keeps pairs where v != 0, excluding bug2:0 and bug4:0, resulting in {'bug1': 5, 'bug3': 3}.

2. Final Answer:

   {'bug1': 5, 'bug3': 3} -> Option B

3. Quick Check:

   Filtered dict excludes zero severity items [OK]

Hint: Filter out zero values to keep real issues [OK]

Common Mistakes:

• Including zero severity items by mistake
• Confusing keys and values in comprehension
• Expecting empty dict instead