Implementing a Calculator in a Mobile App
A calculator seems trivial until you need to support operation chains, handle floating-point precision, and get the bug '0.1 + 0.2 = 0.30000000000000004' from QA. We develop custom calculators turnkey, guaranteeing computational accuracy and a reliable architecture. Our experience includes over 30 successful projects with custom calculation logic. Contact us for a consultation — we'll analyze your use case.
Why Computations Accuracy Matters for a Mobile Calculator?
The most important decision is where to calculate. Built-in Double/Float types follow IEEE 754 floating-point with known limitations. For a financial calculator or accounting app, this is unacceptable. On iOS, the correct path is NSDecimalNumber or Decimal from Foundation. Decimal(string: "0.1") + Decimal(string: "0.2") gives exactly 0.3. For complex expressions — NSExpression or a custom parser with a tokenizer. On Android — java.math.BigDecimal with explicit MathContext.DECIMAL128 and RoundingMode.HALF_UP for division. Dividing BigDecimal without MathContext throws ArithmeticException for non-terminating decimal results (e.g., 1/3).
For parsing expressions like 2 + 3 * 4 with operator precedence, we use Dijkstra's shunting-yard algorithm. It implements in about 100 lines, requires no third-party dependencies, and is covered by unit tests for every edge case. Alternatives include exp4j on Android or MathParser.org-mXparser for cross-platform.
How a Finite State Machine Simplifies Development?
Architecturally, a calculator is a finite state machine. States: idle, enteringFirstOperand, operatorEntered, enteringSecondOperand, resultDisplayed, error. Transitions occur on each button press. Storing simply currentInput: String and operator: String leads to bugs on sequential operator presses or pressing = without a second operand. On iOS — ViewModel with @Published properties or Combine. On Android — ViewModel + StateFlow. In Flutter — BLoC or ChangeNotifier. The computation logic lives in a separate use case / service, tested without UI dependency. Architecture on SwiftUI and Combine provides reactive UI updates without unnecessary re-renders.
Keyboard: LazyVGrid in SwiftUI or GridLayout in Compose is simplest. One nuance — the 0 button usually occupies double width, requiring GridItem with span or a separate HStack for the last row.
What Does Using BigDecimal and Decimal Give in Practice?
Consider an app for calculating loan interest. If each payment is computed via Double, an error of about 0.01 accumulates per month. Over a year, it's already 0.12, and over 10 years — 12. For banks, this is unacceptable. Using Decimal/BigDecimal provides penny-level accuracy over the entire term, and the balance matches the bank's accounting system.
Typical Edge Cases and Their Solutions
| Problem | Solution |
|---|---|
| Multiple dots in number | Check before adding . character |
| Division by zero | Display 'Error', allow reset |
| Display overflow | Limit digit count (e.g., 12) |
Operator chains (5 + 3 * 2) |
Left-to-right or precedence — based on requirements |
Precision loss in 0.1 + 0.2 |
Use Decimal / BigDecimal |
Why Order Development from Us?
- Extensive experience in iOS/Android/Flutter.
- Over 30 successful projects with custom logic.
- Guaranteed precision (0.1+0.2 = 0.3).
- Apple Developer and Google Play certifications.
- Individual approach — contact us, we'll assess your project for free.
Process of Working on a Custom Calculator
- Analysis — agree on mathematical operations, precedence, error handling, UI/UX.
- Design — finite state machine, ViewModel, tests for edge cases.
- Implementation — parser, precise calculations, keyboard, SwiftUI/Compose.
- Testing — unit tests, UI tests, floating-point validation.
- Deployment — App Store Connect / Google Play Console, TestFlight, Firebase Distribution.
Timelines: basic calculator with four operations — from 1 day. Scientific with operator precedence, history, and BigDecimal — from 2 to 3 days.
What's Included
- Source code with comments.
- Unit test suite (coverage >90%).
- Documentation on states and transitions.
- Repository access (GitHub/GitLab).
- CI/CD integration (optional).
- Post-deployment support (2 weeks).
Comparison of Expression Parsing Libraries
| Criterion | Custom shunting-yard | exp4j (Android) | mXparser (cross-platform) |
|---|---|---|---|
| Size | ~100 lines | ~200 KB | ~1 MB |
| Dependencies | None | None | None |
| Extensibility | Full | Limited | Medium |
| Parentheses support | Yes | Yes | Yes |
| Precision | IEEE 754 / BigDecimal | Double | Double / BigDecimal |
A custom parser is better for simple calculators — it's faster and doesn't add unnecessary dependencies. For scientific calculators with functions like sin/cos, use mXparser or exp4j.
Get a consultation on your calculator's architecture. Write to us — we'll analyze all edge cases together.