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intro-to-python
  • An Introduction to Programming in Python (for Business Students)
  • exercises
    • Data Flow Diagramming Exercise
    • Developer Collaboration Exercise
    • README
    • "Web App" Exercise
      • checkpoints
        • Checkpoint 5: Bootstrap Layout
        • Checkpoint 4: Submitting Data from Web Forms
        • Checkpoint 3: Rendering HTML Pages
        • Checkpoint 1: Routing
        • Checkpoint 2: Modular Organization
      • "Web App" Exercise - Further Exploration
    • hello-world
      • "Hello World (Local)" Exercise
      • "Hello World (Local w/ Version Control)" Exercise
      • "Hello World (Colab)" Exercise
    • "Interface Capabilities" Exercise
    • "Continuous Integration 1, 2, 3" Exercise
    • "Web Service" Exercise
      • "Web Service" Exercise - Further Exploration
    • "Testing 1, 2, 3" Exercise
    • "Command-line Computing" Exercise
      • "Command-line Computing" Exercise
      • Professor Rossetti's Mac Terminal Configuration
      • Command-line Computing Exercise
    • "Codebase Cleanup" Assignment
    • "List Comprehensions" Exercise
    • "Groceries" Exercise
      • Python Datatypes (a.k.a. "Groceries") Exercise
      • Python Datatypes (a.k.a. "Groceries") Exercise
    • "Rock, Paper, Scissors" Exercise
      • "Rock, Paper, Scissors" Exercise
    • README
    • "Monthly Sales Predictions" Exercise
    • Setting up your Local Development Environment
    • "Chart Gallery" Exercise
    • "Run the App" Exercise
    • "Web Requests" Exercise
    • "API Client" Exercise
    • "Custom Functions" Exercise
    • Process Diagramming Exercise
  • notes
    • python
      • packages
        • The bigquery Package
        • The PySimpleGUI Package
        • The dotenv Package
        • The matplotlib Package
        • The requests Package
        • The altair Package
        • The gspread Package
        • The PyMySQL Package
        • The psycopg2 Package
        • The selenium Package
        • The seaborn Package
        • The pytest Package
        • The SpeechRecognition Package
        • The flask Package
        • The pandas Package
        • The spotipy Package
        • The pipenv Package
        • The nltk Package
        • The sqlalchemy Package
        • The pymongo Package
        • The plotly Package
        • The BeautifulSoup Package
        • The sendgrid Package
        • The fpdf Package
        • The autopep8 Package
        • The tweepy Package
        • The twilio Package
        • The tkinter Package
      • Python Datatypes Overview
        • Numbers
        • Classes
        • Dates and Times
        • Strings
        • None
        • Dictionaries
        • Booleans
        • Lists
        • Class Inheritance
      • Control Flow
      • Python Modules
        • The webbrowser Module
        • The time Module
        • The csv Module
        • The sqlite3 Module
        • The itertools Module
        • The json Module
        • The math Module
        • The os Module
        • The statistics Module
        • The random Module
        • The pprint Module
        • The datetime Module
        • The collections Module
      • Printing and Logging
      • Comments
      • Syntax and Style
      • Functions
      • Variables
      • Errors
      • Docstrings
      • File Management
      • User Inputs
      • Debugging
    • clis
      • The git Utility
      • Heroku, and the heroku Utility
      • Anaconda
      • The chromedriver Utility
      • The brew Utility (Mac OS)
      • The pdftotext Utility
      • The python Utility
      • The pip Utility
    • Software
      • Software Licensing
      • Software Documentation
      • Software Ethics
      • Software Testing Overview
      • Application Programming Interfaces (APIs)
      • Software Version Control
      • Software Refactoring Overview
    • devtools
      • The VS Code Text Editor
      • Code Climate
      • Travis CI
      • GitHub Desktop Software
      • Git Bash
      • Google Colab
    • Information Systems
      • Computer Networks
      • Processes
      • Datastores
      • Information Security and Privacy
      • People
    • Technology Project Management
      • Project Management Tools and Techniques
      • The Systems Development Lifecycle (SDLC)
    • hardware
      • Servers
    • Environment Variables
  • projects
    • "Executive Dashboard" Project
      • testing
      • "Exec Dash" Further Exploration Challenges
    • The Self-Directed (a.k.a "Freestyle") Project
      • "Freestyle" Project - Demonstration
      • "Freestyle" Project - Implementation (TECH 2335 Version)
      • "Freestyle" Project - Implementation
      • "Freestyle" Project Proposal
      • plan
    • "Robo Advisor" Project
      • Robo Advisor Project - Automated Testing Challenges
      • "Robo Advisor" Further Exploration Challenges
    • "Shopping Cart" Project
      • "Shopping Cart" Project - Automated Testing Challenges
      • "Shopping Cart" Further Exploration Challenges
      • "Shopping Cart" Project Checkpoints
  • License
  • Exam Prep
  • units
    • Unit 4B: User Interfaces and Experiences (Bonus Material)
    • Unit 5b: Databases and Datastores
    • Module 1 Review
    • Unit 7b: Processing Data from the Internet (Bonus Material)
    • Unit 9: Software Products and Services
    • Unit 8: Software Maintenance and Quality Control
    • Unit 7: Processing Data from the Internet
    • Unit 6: Data Visualization
    • Unit 5: Processing CSV Data
    • Unit 4: User Interfaces and Experiences
    • Unit 3: Python Datatypes
    • Unit 12: Project Presentations
    • Unit 2: Python Language Overview
    • Unit 11: Project Implementation Sprint
    • Unit 1: The Python Development Environment
    • Unit 10: Software Planning, Analysis, and Design
    • Unit 0: Onboarding
    • Unit 5B: Advanced Data Analytics
  • Contributor's Guide
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  • Learning Objectives
  • Discussions and Notes
  • Activities and Exercises

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  1. units

Unit 8: Software Maintenance and Quality Control

Learning Objectives

For businesses which provide software products and services, improved code quality leads to better user experiences, higher customer satisfaction and retention, and lower maintenance costs. In this unit, we'll learn ways to control and improve the quality of our applications.

Discussions and Notes

  • Developer Collaboration:

    • The git Utility, revisited

    • Git Branch Operations, revisited

    • GitHub Pull Request (PR) Workflow

    • Code Reviews

  • Code Style:

    • The autopep8 Package

  • Code Documentation:

    • Python Docstrings

  • Code Simplification and Refactoring

  • Code Quality:

    • The Code Climate Platform

  • Automated Testing:

    • The pytest Package

  • Continuous Integration (CI):

    • The Travis CI Platform

Activities and Exercises

  • "Developer Collaboration" Exercise

  • "Codebase Cleanup" Exercise

  • "Testing 1, 2, 3" Exercise

  • "Continuous Integration 1, 2, 3" Exercise

PreviousUnit 9: Software Products and ServicesNextUnit 7: Processing Data from the Internet

Last updated 4 years ago

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