Description of the Tech Debt

Oct 13, 2025 by orovajewels.com 126 views

Description of the Tech Debt

The current implementation of Operation Type SFO and EIO in our Django application allows for multiple facilities to be manually inserted into the database. This can lead to inconsistencies and errors in the system. To address this technical debt, we need to add a constraint to limit the number of facilities for EIO and SFO.

Tech Debt Triage

The purpose of our technical debt triage process is to analyze technical debt to determine the risk level of the technical debt and the value in tackling that technical debt. In this case, the technical debt is related to the lack of a constraint on the number of facilities for EIO and SFO.

Risk Value Scoring:

Level	Value
High	3
Medium	2
Low	1
Technical Debt - Risk Types	Level	Value
-----------------------------------------------------------------------------------------------------------------------------	-----	-----
Business Area Risk - Risk of business area visibility / damage to user experience	2	2
Developer Fault Risk - How likely will this tech debt cause a future error related to coding on top of it	1	1
System Fault Risk - Risk of system errors or application downtime	1	1
Time Scale Risk - Compound risk effect if left alone. How much more difficult to fix or dangerous will this become over time?	2	2
Time Sink Risk - How much will this tech debt slow the development process down	2	2
TOTAL SCORE:	8	8

Development Checklist:

[ ] Add constraint to models.py: Add a constraint to the models.py file to limit the number of facilities for EIO and SFO.
[ ] Update database schema: Update the database schema to reflect the new constraint.
[ ] Test the constraint: Test the constraint to ensure it is working correctly.
[ ] Document the change: Document the change in the code and the database schema.

Implementation

To add a constraint to limit the number of facilities for EIO and SFO, we need to modify the models.py file. We can use the models.IntegerField field to create a field that represents the number of facilities.

from django.db import models

class OperationType(models.Model):
    name = models.CharField(max_length=255)
    facilities = models.IntegerField(default=1)

    def __str__(self):
        return self.name

In this example, we have added a new field called facilities to the OperationType model. This field represents the number of facilities for each operation type.

To update the database schema, we need to run the following command:

python manage.py makemigrations
python manage.py migrate

This will update the database schema to reflect the new constraint.

Testing the Constraint

To test the constraint, we can create a new instance of the OperationType model and try to set the facilities field to a value greater than 1.

from django.test import TestCase
from .models import OperationType

class TestOperationTypeModel(TestCase):
    def test_facilities_constraint(self):
        operation_type = OperationType.objects.create(name='Test Operation Type')
        operation_type.facilities = 2
        with self.assertRaises(ValueError):
            operation_type.save()

In this example, we have created a new test case that tests the facilities constraint. We create a new instance of the OperationType model and try to set the facilities field to 2. We then use the assertRaises method to check that a ValueError is raised when we try to save the instance.

Documenting the Change

To document the change, we need to update the code and the database schema documentation.

# models.py
class OperationType(models.Model):
    name = models.CharField(max_length=255)
    facilities = models.IntegerField(default=1)

    def __str__(self):
        return self.name

# database_schema.sql
CREATE TABLE operation_type (
    id SERIAL PRIMARY KEY,
    name VARCHAR(255) NOT NULL,
    facilities INTEGER DEFAULT 1 NOT NULL
);

In this example, we have updated the models.py file and the database_schema.sql file to reflect the new constraint.

Conclusion

Q: What is the purpose of adding a constraint to limit the number of facilities for EIO and SFO?

A: The purpose of adding a constraint is to prevent inconsistencies and errors in the system by limiting the number of facilities for EIO and SFO.

Q: Why is it necessary to add a constraint to limit the number of facilities for EIO and SFO?

A: It is necessary to add a constraint to limit the number of facilities for EIO and SFO because the current implementation allows for multiple facilities to be manually inserted into the database, which can lead to inconsistencies and errors in the system.

Q: How do I add a constraint to limit the number of facilities for EIO and SFO?

A: To add a constraint, you need to modify the models.py file and update the database schema. You can use the models.IntegerField field to create a field that represents the number of facilities.

Q: What is the `models.IntegerField` field used for?

A: The models.IntegerField field is used to create a field that represents the number of facilities for each operation type.

Q: How do I update the database schema to reflect the new constraint?

A: To update the database schema, you need to run the following command:

python manage.py makemigrations
python manage.py migrate

Q: How do I test the constraint to ensure it is working correctly?

A: To test the constraint, you can create a new instance of the OperationType model and try to set the facilities field to a value greater than 1. You can use the assertRaises method to check that a ValueError is raised when you try to save the instance.

Q: What is the `assertRaises` method used for?

A: The assertRaises method is used to check that a specific exception is raised when a certain condition is met.

Q: How do I document the change to the code and the database schema?

A: To document the change, you need to update the models.py file and the database_schema.sql file to reflect the new constraint.

Q: What is the benefit of adding a constraint to limit the number of facilities for EIO and SFO?

A: The benefit of adding a constraint is that it prevents inconsistencies and errors in the system by limiting the number of facilities for EIO and SFO.

Q: Can I add a constraint to limit the number of facilities for other operation types as well?

A: Yes, you can add a constraint to limit the number of facilities for other operation types as well by modifying the models.py file and updating the database schema.

Q: How do I handle cases where the constraint is violated?

A: To handle cases where the constraint is violated, you can use a try-except block to catch the ValueError exception and handle it accordingly.

Q: What is the best practice for adding constraints to limit the number of facilities for EIO and SFO?

A: The best practice for adding constraints is to follow the standard Django convention of using the models.IntegerField field to create a field that represents the number of facilities, and to update the database schema accordingly.

Q: Can I use a different field type to represent the number of facilities?

A: Yes, you can use a different field type to represent the number of facilities, but you need to ensure that it is compatible with the database schema.

Q: How do I ensure that the constraint is enforced consistently across all instances of the `OperationType` model?

A: To ensure that the constraint is enforced consistently across all instances of the OperationType model, you need to use a try-except block to catch the ValueError exception and handle it accordingly.

Q: What is the impact of adding a constraint to limit the number of facilities for EIO and SFO on the system's performance?

A: The impact of adding a constraint to limit the number of facilities for EIO and SFO on the system's performance is minimal, as it only affects the database schema and does not impact the system's overall performance.

Q: Can I add a constraint to limit the number of facilities for EIO and SFO in a production environment?

A: Yes, you can add a constraint to limit the number of facilities for EIO and SFO in a production environment, but you need to ensure that it is thoroughly tested and validated before deploying it to production.