一、单元测试
1.设计思路
- 固定返回值的函数通过对比与预期结果是否一致进行测试判断
- 随机返回值的函数通过对比是否在预期结果范围内进行测试判断
- 调度场算法通过函数异常中转进行测试判断
2.部分代码
import static org.junit.Assert.*;
import org.junit.Test;
public class ParameterTest {
@Test
// 测试 -n 数量 -Grade 年级
public void DealDataOne() {
String[] args = {"-n","10","-Grade","3"};
//测试boolean
assertTrue(new Parameter(args).DealData(args));
}
@Test
// 测试 -Grade 年级 -n 数量
public void DealDataTwo() {
String[] args = {"-Grade","10","-n","3"};
//测试boolean
assertTrue(new Parameter(args).DealData(args) == false);
}
@Test
// 测试 n 错误
public void DealDataThree() {
String[] args = {"n","10","-Grade","3"};
//测试boolean
assertTrue(new Parameter(args).DealData(args) == false);
}
@Test
// 测试参数数量错误
public void DealDataFour() {
String[] args = {"-n","10","-Grade"};
//测试boolean
assertTrue(new Parameter(args).DealData(args) == false);
}
@Test
// 测试 Grade 错误
public void DealDataFive() {
String[] args = {"-n","10","-Grade","10"};
//测试boolean
assertTrue(new Parameter(args).DealData(args) == false);
}
@Test
// 测试格式错误
public void DealDataSix() {
String[] args = {"n","10","-Grade","3"};
//测试boolean
assertTrue(new Parameter(args).DealData(args) == false);
}
@Test
// 测试格式错误
public void DealDataSeven() {
String[] args = {"-Grade","3","n","10"};
//测试boolean
assertTrue(new Parameter(args).DealData(args) == false);
}
@Test
// 测试不为纯数字
public void DealDataEight() {
String[] args = {"-Grade","3AA","-n","10"};
//测试boolean
assertTrue(new Parameter(args).DealData(args) == false);
}
@Test
// 测试不为纯数字
public void DealDataNine() {
String[] args = {"-Grade","3","-n","AAA"};
//测试boolean
assertTrue(new Parameter(args).DealData(args) == false);
}
@Test
public void GetNumber() {
String[] args = {"-n","10","-Grade","3"};
//测试boolean,long,int等
assertEquals(10, new Parameter(args).GetNumber());
}
@Test
public void GetGradeOne() {
String[] args = {"-n","10","-Grade","3"};
//测试boolean,long,int等
assertEquals(3, new Parameter(args).GetGrade());
}
@Test
public void GetGradeTwo() {
String[] args = {"-n","10","-Grade","4"};
//测试boolean,long,int等
assertEquals(0, new Parameter(args).GetGrade());
}
@Test
// 测试纯数字
public void isNumOne() {
String[] args = {"-n","10","-Grade","3"};
assertTrue(new Parameter(args).isNum("123"));
}
@Test
// 测试非纯数字
public void isNumTwo() {
String[] args = {"-n","10","-Grade","3"};
assertTrue(new Parameter(args).isNum("777A") == false);
}
}
3.测试覆盖率
![avatar][Cover]
[Cover]: 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
二、结构优化
1.UML类图
2.运行流程图
3.代码重构
(1)重构部分
- 题目生成
- 参数处理
(2)重构原因
- 便于单元测试
- 代码模块化
- 增加代码耦合度
(3)当前模块功能
- MathExam为主类,用于接收参数
- File为文件类,用于写出文件
- Parameter为参数处理类,用于检查接收到的参数是否合格并进行处理
- ShuntingYard为调度场算法类,用于实现调度场算法,计算表达式结果
- TaskMake为题目生成类,用于随机生成题目
三、性能调优
1.优化前效能分析
2.性能瓶颈
- String.toArray()方法处理效率较低
3.解决方案
- 使用String.charAt(index)方法替代
4.优化后效能分析
四、总结
- 同类功能的函数应该封装到同一个类中
- 多次使用的方法封装为函数,减少代码量,且代码美观