99爱在线视频这里只有精品_窝窝午夜看片成人精品_日韩精品久久久毛片一区二区_亚洲一区二区久久

合肥生活安徽新聞合肥交通合肥房產生活服務合肥教育合肥招聘合肥旅游文化藝術合肥美食合肥地圖合肥社保合肥醫院企業服務合肥法律

CS209A代做、Java程序設計代寫
CS209A代做、Java程序設計代寫

時間:2024-12-25  來源:合肥網hfw.cc  作者:hfw.cc 我要糾錯



Project.md 2024-1**10
1 / 3
[CS209A-24Fall] Assignment2 (100 points)
Background
In the process of software development, many questions will arise. Developers may resort to Q&A website to
post questions and seek answers. Stack Overflow is such a Q&A website for programmers, and it belongs to the Stack Exchange Network. Stack
Overflow serves as a platform for users to ask and answer questions, and, through membership and active
participation, to vote questions and answers up or down and edit questions and answers in a fashion similar
to a wiki. Users of Stack Overflow can earn reputation points and "badges"; for example, a person is awarded
10 reputation points for receiving an "up" vote on a question or an answer to a question, and can receive
badges for their valued contributions. Users unlock new privileges with an increase in reputation, like the
ability to vote, comment, and even edit other people's posts. In this final project, we'll use Spring Boot to develop a web application that stores, analyzes, and visualizes
Stack Overflow Q&A data w.r.t. java programming, with the purpose of understanding the common
questions, answers, and resolution activities associated with Java programming. Data Collection (10 points)
On Stack Overflow, questions related to Java programming are typically tagged java. You could use this java
tag to identify java-related questions. A question and all of its answers and comments are together referred to
as a thread. For java-related threads on Stack Overflow, we are interested in answering a list of questions as described
below. You should first collect proper data from Stack Overflow to answer these questions. Please check the
official Stack Overflow REST API documentation to learn the REST APIs for collecting different types of data. . You may need to create a Stack Overflow account in order to use its full REST API service. · API requests are subject to rate limits. Please carefully design and execute your requests, otherwise
you may reach your daily quota quickly. . Connections to Stack Overflow REST service maybe unstable sometimes. So, please start the data
collection ASAP!
There are over 1 million threads tagged with java on Stack Overflow. You DON'T have to collect them all. Yet, you should collect data for at least 1000 threads in order to get meaningful insights from the data analysis. Important:
Data collection is offline, meaning that you need to collect and persist the data first. It is recommended that
you use a database (e.g., PostgreSQL, MySQL, etc.) to store the data. However, it is also fine if you store the
data in plain files. In other words, when users interact with your application, the server should get the data
from your local database (or local files), instead of sending REST requests to Stack Overflow on the fly. Hence, the data analysis for the below questions should be performed on the dataset you collected. That is, we first collect a subset of Stack Overflow data (e.g., 1000 threads tagged java) and then answer the
following questions using this subset.
Project.md 2024-1**10
2 / 3
Part I: Data Analysis (70 points)
For each question from this part, you should: . Figure out which data is needed to answer the question
. Design and implement the data analysis on the backend
. Visualize the results on the frontend using proper charts. In other words, when interacting with your web application from the browser, users could select interested
analysis, which sends requests to the server; the server performs corresponding data analysis and returns the
results back to the frontend, which visualizes the results on the webpages. Your work will be evaluated by: . whether the data analysis is meaningful and relevant, i.e., it can indeed answer the question with proper
they want
instantly by looking at the visualization. Take a look at the data visualization catalogue for inspirations. 1. Java Topics (10 points)
We have covered various topics in this course, e.g., generics, collections, I/O, lambda, multithreading, socket, etc. It's interesting to know, what are the top N (N>1, you may choose a proper N depending on your data
and your UI design, same below) topics that are most frequently asked on Stack Overflow?
2. User Engagement (15 points)
What are the top N topics that have the most engagement from users with higher reputation scores? User
engagement means any user activity (e.g., edit, answer, comment, upvote, downvote, etc.) on the thread. 3. Common Mistakes (15 points)
Developers make mistakes, which result in bugs in the code. Bugs manifest themselves as errors or
exceptions, which can be roughly classified as: . Fatal errors: errors like OutOfMemoryError that cannot be recovered at runtime. . Exceptions: checked exceptions and runtime exceptions that can be handled programmatically by
developers. What are the top N errors and exceptions that are frequently discussed by Java developers?
Note that, tags are high-level information and may not include low-level errors or exceptions. Hence, for this
question, you cannot only use tag information. You need to further analyze thread content (e.g., question text
and answer text) to identify error or exception related information, probably using advanced techniques such
as regular expression matching. 4. Answer Quality (30 points)
We consider an answer to be "high-quality" if it is accepted or has many upvotes. It's useful to know, what
factors contribute to high-quality answers?
3 / 3
Project.md 2024-1**10
Please investigate the following factors: . The elapsed time between question creation and answer creation (e.g., whether the first posted answer
tends to be accepted?). . The reputation of the user that creates the answer (e.g., whether answers created by high-reputation
users tend to be accepted or have more upvotes?). In addition to these 2 factors, you should also propose another 1 factor that may contribute to the quality of
answers. For each of the 3 factors, use proper data analysis and visualizations to demonstrate whether the factor
contributes to high-quality answers or not. Part II: RESTful Service (20 points)
Your application should also provide a REST service that answers the following two questions, so that users
may use RESTful APIs to GET the answers they want. The required REST services include: . Topic frequency: users could query for the frequency of a specific topic. Users could also query for the
top N topics sorted by frequency. . Bug frequency: users could query for the frequency of a specific error or exception. Users could also
query for the top N errors or exceptions sorted by frequency. Here, you could reuse the data analysis from Part I. Responses of the REST requests should be in json format. Requirements
Data Analysis
You should implement the data analysis by yourself, using Java features such as Collections, Lambda, and
Stream. You CANNOT feed the data to AI, ask AI to do the analysis, and use AI responses as your data analysis results. You will get 0 point for the question if you do so. Data analysis results should be dynamically generated by the server everytime clients send a request. You
SHOULD NOT precompute the results and stored it as a static content then simply display the precomputed
static content on the frontend. 20 points will be deducted if you do so. Web Framework
You should only use Spring Boot as the web framework. Frontend
Frontend functionalities, such as data visualization and interactive controls, could be implemented in any
programming language (e.g., JavaScript, HTML, CSS, etc.) with any 3rd-party libraries or framework.

請加QQ:99515681  郵箱:99515681@qq.com   WX:codinghelp



 

掃一掃在手機打開當前頁
  • 上一篇:代寫DTS207TC、SQL編程語言代做
  • 下一篇:CS305程序代做、代寫Python程序語言
  • 無相關信息
    合肥生活資訊

    合肥圖文信息
    急尋熱仿真分析?代做熱仿真服務+熱設計優化
    急尋熱仿真分析?代做熱仿真服務+熱設計優化
    出評 開團工具
    出評 開團工具
    挖掘機濾芯提升發動機性能
    挖掘機濾芯提升發動機性能
    海信羅馬假日洗衣機亮相AWE  復古美學與現代科技完美結合
    海信羅馬假日洗衣機亮相AWE 復古美學與現代
    合肥機場巴士4號線
    合肥機場巴士4號線
    合肥機場巴士3號線
    合肥機場巴士3號線
    合肥機場巴士2號線
    合肥機場巴士2號線
    合肥機場巴士1號線
    合肥機場巴士1號線
  • 短信驗證碼 豆包 幣安下載 AI生圖 目錄網

    關于我們 | 打賞支持 | 廣告服務 | 聯系我們 | 網站地圖 | 免責聲明 | 幫助中心 | 友情鏈接 |

    Copyright © 2025 hfw.cc Inc. All Rights Reserved. 合肥網 版權所有
    ICP備06013414號-3 公安備 42010502001045

    99爱在线视频这里只有精品_窝窝午夜看片成人精品_日韩精品久久久毛片一区二区_亚洲一区二区久久

          9000px;">

                久久只精品国产| 中文字幕一区二区在线观看| 国产精品理论在线观看| 日韩欧美中文字幕制服| 国产欧美视频在线观看| 久久嫩草精品久久久精品一| 最新久久zyz资源站| 91.xcao| 亚洲伦理在线精品| eeuss国产一区二区三区| 亚洲一区二区中文在线| 国产精品久久久久久福利一牛影视 | 91在线视频在线| 精品一区二区成人精品| 色伊人久久综合中文字幕| 一区二区三区欧美日| 久久久久久久久岛国免费| 欧美一卡二卡三卡| 成人avav在线| 亚洲国产精品麻豆| 午夜精品久久久久| 一区二区三区不卡视频| 亚洲综合久久av| 一区二区三区精品| 午夜久久久久久| 激情偷乱视频一区二区三区| 国产一区二区三区高清播放| 国产精品一区二区黑丝| 91亚洲精华国产精华精华液| 色婷婷综合五月| 欧美一级二级在线观看| 久久天天做天天爱综合色| 久久精品亚洲精品国产欧美kt∨| 日本一区二区三级电影在线观看 | 国产aⅴ精品一区二区三区色成熟| 久久99国产精品麻豆| 国产一区三区三区| 在线视频你懂得一区二区三区| 色婷婷久久99综合精品jk白丝| 从欧美一区二区三区| 欧美伦理影视网| 最近中文字幕一区二区三区| 亚洲v中文字幕| 成人丝袜视频网| 欧美精品xxxxbbbb| 亚洲三级电影网站| 国产一区二区三区四区五区美女| 日韩主播视频在线| 国产成人久久精品77777最新版本| 国产不卡一区视频| 日韩一区二区三区av| 亚洲福利视频三区| 欧美日韩国产一级| 丝袜国产日韩另类美女| 欧美伊人久久久久久久久影院 | 国产精品电影院| 欧美日韩国产综合一区二区 | 欧美另类z0zxhd电影| 国产精品综合一区二区| 久久久久免费观看| 日本国产一区二区| 国产精品综合在线视频| 一区二区三区自拍| 久久精子c满五个校花| 国产无人区一区二区三区| 午夜精品福利一区二区三区av | 欧美色综合影院| 国产精品综合一区二区| 日韩成人dvd| 日韩一区在线看| 久久久久久久久久久久电影| 在线观看免费一区| 99国产精品久久久久| 99久久99久久精品免费看蜜桃| 麻豆精品久久精品色综合| 欧美日韩一级二级三级| 午夜精品久久久久久久99水蜜桃| 一本大道久久a久久精品综合| 色94色欧美sute亚洲线路一久 | 欧美韩国日本一区| 中文字幕一区二区三区乱码在线 | 欧美高清一级片在线观看| 中文字幕亚洲欧美在线不卡| 国产在线播放一区| 国产精品亚洲一区二区三区妖精 | 亚洲制服丝袜在线| 欧美人牲a欧美精品| 欧美日韩在线电影| 欧美视频一区二区三区| 欧美优质美女网站| 欧美日韩在线电影| 亚洲综合小说图片| 日韩电影免费在线| 国产成都精品91一区二区三| 国产91丝袜在线播放| 国产午夜精品一区二区三区四区| 欧美影院一区二区| 久久蜜桃av一区精品变态类天堂 | 欧美a一区二区| 国产激情视频一区二区在线观看| 国产乱妇无码大片在线观看| 国产精品1区2区3区在线观看| 国产一区二区在线影院| 91免费观看视频在线| 欧美色大人视频| 国产精品久久三| 国产精品成人一区二区艾草| 欧美精品国产精品| 久久久久久97三级| 舔着乳尖日韩一区| 丰满岳乱妇一区二区三区| 91久久香蕉国产日韩欧美9色| 欧美一a一片一级一片| 亚洲国产激情av| 青青草一区二区三区| 99这里只有久久精品视频| 91福利视频网站| 成人免费三级在线| 日本电影欧美片| 国产欧美一区二区在线观看| 婷婷中文字幕一区三区| 色噜噜狠狠色综合中国| 国产香蕉久久精品综合网| 日韩高清欧美激情| 欧美一二三区精品| 久久精品国产99国产| 在线播放日韩导航| 天堂影院一区二区| 777色狠狠一区二区三区| 亚洲黄一区二区三区| 日本乱人伦aⅴ精品| 亚洲国产精品ⅴa在线观看| 成人黄色免费短视频| 亚洲三级电影网站| 欧美精品日韩一本| 精品在线一区二区三区| 欧美军同video69gay| 午夜影视日本亚洲欧洲精品| 日韩网站在线看片你懂的| 国产一区二三区| 一区二区三区**美女毛片| 日韩欧美亚洲一区二区| 高清日韩电视剧大全免费| 一区二区久久久久| 久久久久久久久久久久电影| 日本精品免费观看高清观看| 久久www免费人成看片高清| 国产人成一区二区三区影院| 欧美专区日韩专区| 国产在线精品一区二区三区不卡 | 欧美综合亚洲图片综合区| 久久国产精品99久久久久久老狼| 久久久久国产成人精品亚洲午夜 | 成人免费看片app下载| 日韩精品成人一区二区三区| 国产精品美日韩| 欧美精品一区视频| 在线观看91精品国产麻豆| 色婷婷一区二区三区四区| va亚洲va日韩不卡在线观看| 精品午夜一区二区三区在线观看 | 亚洲成人av电影| 亚洲一区av在线| 91精品国产一区二区三区蜜臀| 亚洲精品中文字幕在线观看| 欧美三级在线播放| 欧美日韩小视频| 91精品国产91久久久久久一区二区 | 经典一区二区三区| 国产毛片精品一区| 成人网页在线观看| 色哟哟欧美精品| 69堂国产成人免费视频| 久久先锋资源网| 亚洲你懂的在线视频| 亚洲综合色网站| 美女免费视频一区二区| 精品一区二区成人精品| 99综合影院在线| 日韩欧美高清在线| 亚洲免费观看高清| 99久久伊人久久99| 不卡的av网站| 免费人成黄页网站在线一区二区| 中文字幕欧美激情一区| 欧美成人乱码一区二区三区| 99久久99久久久精品齐齐| 韩国毛片一区二区三区| 日产国产欧美视频一区精品| 久久久精品tv| 日韩欧美一级精品久久| 91国偷自产一区二区三区观看 | 亚洲成人福利片| 色一区在线观看| 天天综合网天天综合色| 香蕉成人伊视频在线观看| 欧美日韩免费一区二区三区| 91免费看视频| 国产精品天美传媒| 日日嗨av一区二区三区四区|