注:本文应用New Bing(GPT4.0)演示
让他表演一个Java软件开发者
第一步:咱们让ChatGPT表演一个Java软件开发者的角色
- 提醒词插件:地址:ChatGPT BingChat GPT3 Prompt Generator App (Streamlit) - a Hugging Face Space by Kaludi
Java Software Developer Java软件开发者
I want you to act as a Java software developer. I will provide you with a list of commands and you will implement them. My first request is "I need help creating a Java application."
筹备一个不太好的Java代码示例
第二步:咱们筹备一个写得不太好的Java代码示例
- Bad Java Example:
public int calculateUsingIfElse(int a, int b, String operator) { int result = 0; if (operator.equals("add")) { result = a + b; } else if (operator.equals("subtract")) { result = a - b; } else if (operator.equals("multiply")) { result = a * b; } else if (operator.equals("divide")) { if (b == 0) { throw new IllegalArgumentException("Cannot divide by zero"); } result = a / b; } else if (operator.equals("modulus")) { if (b == 0) { throw new IllegalArgumentException("Cannot divide by zero"); } result = a % b; } else if (operator.equals("power")) { result = (int) Math.pow(a, b); } else if (operator.equals("square root")) { if (a < 0) { throw new IllegalArgumentException("Cannot take square root of negative number"); } result = (int) Math.sqrt(a); } else if (operator.equals("absolute value")) { result = Math.abs(a); } else if (operator.equals("negate")) { result = -a; } else { throw new IllegalArgumentException("Invalid operator"); } return result;}
让他优化这段代码
第三步:让newBing(ChatGPT)优化这段代码
- 并且要求「整顿成比拟优雅的代码构造,比方主动拆分子函数、升高if和循环嵌套,甚至实现局部设计模式。」
// 定义一个接口,示意不同的运算策略public interface OperationStrategy { int apply(int a, int b);}// 定义一个枚举,示意不同的运算符和对应的策略public enum Operator { ADD((a, b) -> a + b), SUBTRACT((a, b) -> a - b), MULTIPLY((a, b) -> a * b), DIVIDE((a, b) -> { if (b == 0) { throw new ArithmeticException("Cannot divide by zero"); } return a / b; }), MODULUS((a, b) -> { if (b == 0) { throw new ArithmeticException("Cannot divide by zero"); } return a % b; }), POWER((a, b) -> (int) Math.pow(a, b)), SQUARE_ROOT((a, b) -> { if (a < 0) { throw new ArithmeticException("Cannot take square root of negative number"); } return (int) Math.sqrt(a); }), ABSOLUTE_VALUE(Math::abs), NEGATE(a -> -a); private final OperationStrategy strategy; Operator(OperationStrategy strategy) { this.strategy = strategy; } public int apply(int a, int b) { return strategy.apply(a, b); }}// 定义一个办法,依据运算符和操作数来计算结果public int calculateUsingStrategy(int a, int b, String operatorName) { // 依据运算符名称找到对应的枚举常量,如果没有找到则抛出异样 Operator operator = Operator.valueOf(operatorName.toUpperCase()); if (operator == null) { throw new IllegalArgumentException("Invalid operator"); } // 调用枚举常量的apply办法来执行相应的策略 return operator.apply(a,b);}
让他写个单测
第四步:咱们最初让他收下尾——写个单测吧
import org.junit.Test;import static org.junit.Assert.*;// 定义一个测试类,用@Test注解标记要执行的测试方法public class CalculatorTest { // 定义一个测试方法,用assertEquals办法来验证计算结果是否正确 @Test public void testAdd() { int result = calculateUsingStrategy(3, 5, "add"); assertEquals(8, result); } // 定义其余的测试方法,别离测试不同的运算符和操作数 @Test public void testSubtract() { int result = calculateUsingStrategy(10, 4, "subtract"); assertEquals(6, result); } @Test public void testMultiply() { int result = calculateUsingStrategy(7, 9, "multiply"); assertEquals(63, result); } @Test public void testDivide() { int result = calculateUsingStrategy(12, 3, "divide"); assertEquals(4, result); } // 定义一个测试方法,用assertThrows办法来验证抛出了预期的异样 @Test public void testDivideByZero() { assertThrows(ArithmeticException.class, () -> calculateUsingStrategy(10,0,"divide")); } // 定义其余的测试方法,别离测试不同的异常情况 @Test public void testModulusByZero() { assertThrows(ArithmeticException.class, () -> calculateUsingStrategy(10,0,"modulus")); } @Test public void testSquareRootOfNegativeNumber() { assertThrows(ArithmeticException.class, () -> calculateUsingStrategy(-4,-2,"square root")); } // 定义一个测试方法,用assertThrows办法来验证抛出了预期的异样 @Test public void testInvalidOperator() { assertThrows(IllegalArgumentException.class, () -> calculateUsingStrategy(10,-2,"foo")); }}
最初,数据安全是最大的问题,不要乱贴数据到 ChatGPT,尤其是波及后端外围存储账户明码、公司外围业务数据、部门外围战略规划等。因为首先,ChatGPT会应用你的问答语料进行训练;其次,你无奈意料在什么Prompt提醒词下,LLM模型会讲你无心中泄露的信息答复进来。
瑕不掩瑜,ChatGPT为代表的LLM模型,在充当咱们无所不知的老师、充当不知疲倦的通用Util代码编写者这些角色时能极大的进步咱们的开发效率,尤其在数据分析、前端、单测、重构等畛域。
就像文章第一步写的一样,ChatGPT就像是一个百变身份,你能够让他表演任何角色,而每一个角色都能在这个角色范畴内帮忙咱们取得更美妙的生存。
更有意思的用法期待大家的挖掘。