This is a standalone Binary Tree data structure from the data-structure-typed collection. If you wish to access more
data structures or advanced features, you can transition to directly installing the
complete data-structure-typed package
const loanDecisionTree = new BinaryTree<string>(
['stableIncome', 'goodCredit', 'Rejected', 'Approved', 'Rejected'],
{ isDuplicate: true }
);
function determineLoanApproval(
node?: BinaryTreeNode<string> | null,
conditions?: { [key: string]: boolean }
): string {
if (!node) throw new Error('Invalid node');
if (!node.left && !node.right) return node.key;
return conditions?.[node.key]
? determineLoanApproval(node.left, conditions)
: determineLoanApproval(node.right, conditions);
}
console.log(determineLoanApproval(loanDecisionTree.root, { stableIncome: true, goodCredit: true }));
console.log(determineLoanApproval(loanDecisionTree.root, { stableIncome: true, goodCredit: false }));
console.log(determineLoanApproval(loanDecisionTree.root, { stableIncome: false, goodCredit: true }));
console.log(determineLoanApproval(loanDecisionTree.root, { stableIncome: false, goodCredit: false })); const expressionTree = new BinaryTree<number | string>(['+', 3, '*', null, null, 5, '-', null, null, 2, 8]);
function evaluate(node?: BinaryTreeNode<number | string> | null): number {
if (!node) return 0;
if (typeof node.key === 'number') return node.key;
const leftValue = evaluate(node.left);
const rightValue = evaluate(node.right);
switch (node.key) {
case '+':
return leftValue + rightValue;
case '-':
return leftValue - rightValue;
case '*':
return leftValue * rightValue;
case '/':
return rightValue !== 0 ? leftValue / rightValue : 0;
default:
throw new Error(`Unsupported operator: ${node.key}`);
}
}
console.log(evaluate(expressionTree.root));
| Principle |
Description |
| Practicality |
Follows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names. |
| Extensibility |
Adheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures. |
| Modularization |
Includes data structure modularization and independent NPM packages. |
| Efficiency |
All methods provide time and space complexity, comparable to native JS performance. |
| Maintainability |
Follows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns. |
| Testability |
Automated and customized unit testing, performance testing, and integration testing. |
| Portability |
Plans for porting to Java, Python, and C++, currently achieved to 80%. |
| Reusability |
Fully decoupled, minimized side effects, and adheres to OOP. |
| Security |
Carefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects. |
| Scalability |
Data structure software does not involve load issues. |