In short: an e-commerce project is judged on its data model, its order flow and how clearly you document them, not on how the site looks. This page shows how to design and write up your own project. FLN Tutors (Freelancer Network) offers one-to-one help with schema design, order logic and report structure. Matched to a verified specialist who knows your course, your university's marking criteria, and your deadline.
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FLN offers one-to-one online E-Commerce Development tutoring with verified subject specialists. Sessions focus on key models and theories, applied to real cases, including Shopify, WooCommerce, Magento and BigCommerce, using your own course material, so you understand the subject and can apply it yourself.
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Searching for an e-commerce project report returns dozens of uploaded PDFs and public repositories. Submitting one of those, or rewording it, is plagiarism, and university plagiarism software indexes exactly those sources, so it is also the most easily detected kind.
This page does something different. It shows you how to design the system and document it yourself, so the report describes work you actually did. Your tutor can review your design and your drafts, but the build and the writing must be yours.
| Area | What earns marks |
|---|---|
| Requirements | Clear, testable statements, not a feature wish list |
| Data model | Normalised schema with justified relationships |
| Order flow | A defined state machine, including failure paths |
| Security | Password hashing, no card data stored, HTTPS |
| Testing | Evidence of tests with results, not a claim |
| Documentation | Diagrams that match the code that exists |
The most common failure is a report describing a system more ambitious than the one that was built. Markers check the two against each other. A smaller system documented honestly scores better than a large one described aspirationally.
A workable minimum is seven tables.
| Table | Holds | Key points |
|---|---|---|
| users | Accounts | Store a password hash, never the password |
| categories | Product grouping | Self-referencing parent_id allows subcategories |
| products | Catalogue | Current price lives here |
| cart_items | In-progress basket | Tied to user or session |
| orders | Placed order | Status, totals, timestamps, address snapshot |
| order_items | Lines within an order | Stores price_at_purchase |
| payments | Payment attempts | Provider reference, status, amount |
The single most important design decision is that `order_items` stores the price at the time of purchase, rather than joining to `products` for the current price. If you join, then changing a product's price silently rewrites the value of every historical order, and your reports and invoices stop matching what customers actually paid. Explaining that choice in the report demonstrates you understand why the schema is shaped that way.
The same reasoning applies to the delivery address: store a copy on the order, because the user may edit their address later.
A cart holds 2 items at 499 and 1 item at 1,299. A 10% discount code applies, GST is 18%, and shipping is a flat 49.
| Step | Calculation | Amount |
|---|---|---|
| Subtotal | (2 × 499) + 1,299 | 2,297.00 |
| Discount | 10% of 2,297 | −229.70 |
| Taxable amount | 2,297 − 229.70 | 2,067.30 |
| GST | 18% of 2,067.30 | +372.11 |
| Shipping | flat | +49.00 |
| Total | 2,488.41 |
Order matters. Apply the discount before tax, not after. If you tax the full 2,297 first, you get 2,529.76 — a difference of 41.35 on one small order, and the customer has been overcharged tax on money they never paid.
Two further rules: store money as integer minor units or a fixed-point decimal, never as a floating point number, and recalculate the total on the server. A total submitted by the browser can be edited by the customer.
Define the states and the permitted transitions explicitly, including the ones that fail.
A state diagram showing which transitions are allowed, and which are impossible, is worth more in a report than several screenshots. The most frequently missing paths are a declined payment and a cancellation after payment but before dispatch, and markers look for them because that is where real systems break.
Never trust the client for payment confirmation. Confirm payment from the provider's server-side callback or by querying the provider, not from the browser returning to a success page, which anyone can request directly.
That sixth point is the one most often missed: being able to view another customer's order by changing the id in the URL is a real and common flaw, and it is easy for a marker to test.
Record the input, the expected result and the actual result in a table. A test table with real outputs is evidence; a sentence saying the system was tested thoroughly is not.
Two practical points. Diagrams must match the delivered code, so redraw them at the end if the design changed during the build. And a limitations section that names what does not work reads as competence, not weakness — markers already know a student project is not a production system.
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An academic e-commerce project builds an online shopping system covering a product catalogue, cart, checkout, payment and order management, then documents the design and testing. Marks come from the data model, the order logic and the clarity of the write-up rather than visual polish.
No. Submitting or rewording a report found online is plagiarism, and because those PDFs and repositories are publicly indexed they are among the easiest sources for university software to detect. Use them to understand expectations, then design, build and document your own.
A workable minimum is users, categories, products, cart_items, orders, order_items and payments. Larger systems add reviews, addresses, inventory movements, coupons and shipments, but those seven cover the full purchase journey end to end and are enough for most coursework at undergraduate level.
Because product prices change. If order lines join to the current product price, every historical order silently changes value whenever a price is edited, so invoices and revenue reports no longer match what customers paid. Storing the price at purchase keeps each order a fixed record.
Before tax in most systems, since tax is charged on the amount actually paid. Applying tax to the pre-discount subtotal overcharges the customer. State which convention your jurisdiction and your module require, and apply it consistently in both code and report.
As integer minor units, such as paise or cents, or as a fixed-point decimal type. Floating point introduces rounding errors that accumulate across order lines and produce totals that do not reconcile, which is both a correctness bug and an easy one for a marker to find.
Because anything sent from the browser can be edited by the user, including the price and the total. The server must recompute the amount from the stored product prices and the applicable discount before taking payment, treating the client's figures as untrusted input.
It is the defined set of states an order can occupy and the transitions allowed between them, such as created, payment pending, paid, failed, processing, shipped, delivered, cancelled and refunded. Documenting it, including failure paths, shows the system handles real situations.
Through the payment provider's server-side callback, or by querying the provider's API directly. Never mark an order paid because the browser reached a success page, since anyone can request that URL directly and would receive goods without paying for them.
Hashed with a deliberately slow algorithm designed for passwords, such as bcrypt or Argon2, with a per-user salt that those algorithms handle for you. Plaintext is indefensible, and fast general-purpose hashes like MD5 or SHA-1 are unsuitable because they are cheap to attack.
No. Storing card numbers brings PCI DSS obligations that no student project can satisfy. Use a payment provider's hosted checkout or tokenisation so card data never reaches your server, and say so explicitly in the security section of your report.
Authentication establishes who the user is; authorisation decides what that user may access. Checking only that someone is logged in is insufficient, because they could then open another customer's order by changing an id in the URL. Every request must check ownership.
Typically an ER diagram for the data model, a data flow diagram, use case diagrams and a state diagram for the order lifecycle, plus an architecture overview. They must reflect the system actually submitted, so redraw them at the end if the design changed during the build.
With a table giving each test case, its input, the expected result and the actual observed result, covering boundary cases such as an empty cart, out-of-stock items and a declined payment. A statement that the system was tested, with no recorded outcomes, earns little.
Yes. A one-to-one tutor can review your schema and order flow, check your total calculations and security approach, and give feedback on report structure and drafts. The code and the writing stay yours, in line with your course's academic integrity rules.
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