Java面试编程题 需求:在电商网站上，会展示每个店铺的描述相符，服务态度，物流服务得分，分值为0～5分，如小张店铺三项得分分别为4.2，4.8，4.6。

题目要求：
需求:在电商网站上，会展示每个店铺的描述相符，服务态度，物流服务得分，分值为0～5分，如小张店铺三项得分分别为4.2，4.8，4.6。
现在考虑到新店开张时一个差评就会严重影响得分，需要对新店进行扶持，避免得分过低，影响店铺成长。对平均分低于4.0的新店，将平均分拉高到4.0。请写个函数，对原始得分进行处理得到修正后的得分

import java.math.RoundingMode;
import java.text.DecimalFormat;
import java.util.ArrayList;
import java.util.DoubleSummaryStatistics;
import java.util.List;
import java.util.Random;
import java.util.stream.Collectors;

public class Stores {

    //需求:在电商网站上，会展示每个店铺的描述相符，服务态度，物流服务得分，
    //分值为0～5分，如小张店铺三项得分分别为4.2，4.8，4.6。
    //现在考虑到新店开张时一个差评就会严重影响得分，需要对新店进行扶持，避免得分过低，影响店铺成长。
    //对平均分低于4.0的新店，将平均分拉高到4.0。
    //1. 请写个函数，对原始得分进行处理得到修正后的得分。
    private Long id;
    private List<Double> Matching_DescriptionList = new ArrayList<>();
    private List<Double> Logistics_AttitudeList = new ArrayList<>();
    private List<Double> Logistics_ServicesList = new ArrayList<>();
    ;

    public static void main(String[] args) {
        Stores xiaozhang = new Stores();
        Rating(4.2, 4.8, 4.6, xiaozhang);
        System.out.println("现在的平均分为:" + CalAvgScore(xiaozhang));
        Rating(1.2, 2.8, 2.6, xiaozhang);
        Rating(1.2, 2.8, 2.6, xiaozhang);
        Rating(1.2, 2.8, 3.6, xiaozhang);
        System.out.println("差评后的平均分为:" + CalAvgScore(xiaozhang));
        SupportNewStore(xiaozhang);
        System.out.println("支持后的平均分为:" + CalAvgScore(xiaozhang));
        System.out.println("描述相符各项分数为：");
        PrintList(xiaozhang.Matching_DescriptionList);
        System.out.println("服务态度各项分数为：");
        PrintList(xiaozhang.Logistics_AttitudeList);
        System.out.println("物流服务各项分数为：");
        PrintList(xiaozhang.Logistics_ServicesList);

    }

    private static void PrintList(List<Double> list) {
        for (int i = 0; i < list.size(); i++) {
            System.out.println(list.get(i).doubleValue());
        }
    }

    public static void Rating(double Matching_Description,
                              double Logistics_Attitude,
                              double Logistics_Services, Stores store) {
        store.Matching_DescriptionList.add(Matching_Description);
        store.Logistics_AttitudeList.add(Logistics_Attitude);
        store.Logistics_ServicesList.add(Logistics_Services);
    }

    private static double CalAvgItem(List<Double> list) {
        double sum = 0;
        for (int i = 0; i < list.size(); i++) {
            sum += list.get(i).doubleValue();
        }
        return sum / list.size();
    }

    private static double CalAvgScore(Stores store) {


        double avgMatching_Description = CalAvgItem(store.Matching_DescriptionList);
        double avgLogistics_Attitude = CalAvgItem(store.Logistics_AttitudeList);
        double avgLogistics_Services = CalAvgItem(store.Logistics_ServicesList);

        double avgScore = (avgMatching_Description +
                avgLogistics_Attitude +
                avgLogistics_Services) / 3;
        DecimalFormat df = new DecimalFormat("0.00");
        df.setRoundingMode(RoundingMode.HALF_UP);
        avgScore = Double.parseDouble(df.format(avgScore));
        return avgScore;
    }

    private static double GenerateItem() {

        Random r = new Random();
        double item = r.nextDouble()  + 4;
        DecimalFormat df = new DecimalFormat("0.00");
        df.setRoundingMode(RoundingMode.HALF_UP);
        item = Double.parseDouble(df.format(item));
        //System.out.println("生成：" + item);
        return item;
    }

    private static void SupportNewStore(Stores store) {


        double avgScore = CalAvgScore(store);
        if (avgScore < 4.0) {
            while (CalAvgScore(store) < 4) {
                store.Matching_DescriptionList.add(GenerateItem());
                store.Logistics_AttitudeList.add(GenerateItem());
                store.Logistics_ServicesList.add(GenerateItem());
            }
        }
    }


}

运行结果：