026-nato-alphabet/docs/business-case.md

Business Case

Metadata

Key	Value
ID	BC-001
CrossReference	SA-001
Language	en
Domain	it

Version History

Date	Status	Author	Reviewer	Change	Commit
2026-10-13	Accepted	Jens Tirsvad Nielsen	AI as stand-in for S01	Initial version, reviewed in RC-001	pending

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Executive Summary

Day 26 of the Udemy course "100 Days of Code: The Complete Python Pro Bootcamp" teaches list and dictionary comprehensions through a small console tool: the user types a word and the program spells it out with the NATO phonetic alphabet. This project delivers that assignment as a clean, tested, documented Python repository that other course participants and GitHub visitors can read, run and compare against their own solutions. It uses only the Python standard library at runtime.

Methodological and Standards Foundation

• Methodology: the project follows the SQA and QC framework mounted at framework/ (plan first, review every artifact against its QC checklist, one pull request per milestone).
• Quality model: ISO/IEC 25010:2023 characteristics tag every QC criterion; code is reviewed against qc-programming-python.md.
• Engineering practice: Clean Architecture layering at a size proportionate to the program, tests written with pytest, source documented with Doxygen comments.

Problem Statement

• The course assignment ships as a loose main.py and a CSV file with no tests, no run instructions and no project structure, so a participant cannot easily share or compare a solution.
• Public solutions to course assignments are often undocumented, depend on heavy libraries (the course uses Pandas for a 26-row table) and are not runnable without guesswork.

Business Opportunity

A small, exemplary solution lets the Product Owner practise professional project hygiene (packaging, tests, CI, documentation, multilingual wiki) on a trivially small domain, and gives other learners and GitHub visitors a reference they can run in a minute.

Objectives

1. O1: Deliver a console program that converts a word typed by the user into the list of NATO phonetic code words, built with list and dictionary comprehensions, keeping the assignment's function names.
2. O2: Make the repository runnable by following the README on Windows PowerShell, Debian Linux and macOS with a local .venv.
3. O3: Cover the behaviour with automated pytest tests that run in continuous integration.
4. O4: Document the source with Doxygen comments and a Doxyfile, and document the project in a README and a wiki in English, Danish and Bahasa Malaysia, with screenshots.
5. O5: Present the repository to GitHub viewers with a description and topics, and with no runtime dependencies.

Scope

In Scope

• Console program: reads a word, prints the NATO code words for its letters; asks again when the input contains a character that is not a letter.
• NATO alphabet data file (comma-separated values, CSV, as supplied with the assignment) and a loader that uses the standard library.
• Project structure src/, tests/, docs/; pyproject.toml; constants.py; Python .gitignore; Doxyfile.
• pytest test suite; continuous integration (CI) workflow that runs the tests.
• README from the framework template; wiki pages in en, da and ms; screenshots for README and wiki.
• Repository description and topics on the git host.

Out of Scope

• A graphical or web interface.
• Publishing a package to the Python Package Index (PyPI).
• Runtime dependencies such as Pandas.
• Non-Latin alphabets and digits (rejected with a message).
• Other course days.

Expected Benefits

Tangible Benefits

• A runnable, tested reference solution with a one-command test run.
• A reusable repository skeleton (pyproject, continuous integration, Doxygen, wiki) for later course days.

Intangible Benefits

• Practice in professional project hygiene.
• A readable example for other learners, in three languages.

Strategic Alignment

The project supports the Product Owner's personal goal of completing the 100 Days of Code bootcamp with portfolio-quality repositories, and the framework's goal of demonstrating the plan-first workflow on a small project.

Success Criteria

#	Criterion	Target	Measure
1	Program spells a word correctly	Every letter A-Z maps to its NATO code word; input is case-insensitive	pytest: all 26 letters and a mixed-case word pass
2	Tests pass	100 % of tests pass on Python 3.13 locally and in CI	python -m pytest exit code 0; CI run green
3	No runtime dependencies	0 runtime dependencies	pyproject.toml has an empty dependencies list
4	Setup works from the README	A fresh clone runs the program using only the README steps	Manual run of the README steps on Windows PowerShell
5	Documentation complete	README sections of the template, wiki in 3 languages, Doxygen builds without warnings	check-readme.sh exit 0; every wiki page exists in en, da and ms; doxygen Doxyfile reports 0 warnings
6	Repository presented	Description and at least 5 topics set	Repository page and API show both

Risks

Risk	Impact	Mitigation
The git host token lacks scope for editing the repository or wiki	Description, topics or wiki cannot be published	Stop and report; keep the wiki content as files in the working tree and ask S01 for a token with the needed scope
The wiki is not enabled on the host	Wiki pages cannot be pushed	Enable it through the repository settings API; otherwise stop and report
Danish and Bahasa Malaysia translations contain errors	S02 or S03 read wrong text	Keep wiki sentences short and simple; S01 reviews the translations in the pull request
Starter code is copied verbatim	Originality concerns	The program is written fresh; only the supplied CSV data is reused, as the assignment intends
Secrets in .env leak into the repository	Credential exposure	.env is git-ignored, never imported by the program or tests, and never echoed

Assumptions

• The Product Owner is S01, who also develops and reviews; in autonomous mode the AI acts as S01's stand-in reviewer and the review records say so.
• Python 3.13 or newer is available on the machines of the readers.
• The git host (Gitea) offers repository, topic and wiki features through its application programming interface (API) and git remote.
• The CSV with 26 letter/code word rows supplied with the assignment is the data source.

Constraints

• Python 3.13 or newer, a local venv, pytest, constants in constants.py, configuration in pyproject.toml.
• Folder structure src/, tests/, docs/.
• No runtime dependencies unless needed.
• Tokens are read from .env for personal use only; the project and its tests never import or test it.
• One pull request per milestone; no commit on main.

Cost–Benefit Assessment

Qualitative, because the project is a personal learning exercise with no revenue; the effort is a few hours of S01's time and AI assistance.

Costs	Benefits
A few hours of effort; hosting on an existing git host	A reusable reference repository, practice with the framework, a shareable example for S02 and S03

Stakeholders

Stakeholder ID (SA)	Interest in this project
S01	Owns and builds the project; wants a clean, complete solution
S02	Wants readable, runnable code with the assignment's function names and run instructions
S03	Wants a clear description, topics and README, and no runtime dependencies

Recommendation

Proceed: the scope is small, the risks are low and every objective is verifiable.

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