Stack Overflow slides Data Analytics
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Analysis of StackOverflow posts/user data trend analysis. Predicting time to answer (classification) using Weka. CSCI599 final project on Social media data analytics
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StackOverflow
The document discusses stack overflow attacks and protection against them. It begins with an introduction to stack overflows, explaining that they occur when more items are pushed onto the stack than allocated space allows. This can overwrite adjacent memory and execute arbitrary code. Next, it describes the operation of the stack, how functions use stacks to store data and return addresses. The document then explains how attackers can exploit buffer overflows to manipulate the return address and inject shellcode to execute malicious code. Finally, it discusses some methods to protect against stack overflow attacks, such as bounds checking, address space layout randomization, and nonexecutable stacks.
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Video: https://www.youtube.com/watch?v=kkOG_aJ9KjQ
This talk gives details about Spark internals and an explanation of the runtime behavior of a Spark application. It explains how high level user programs are compiled into physical execution plans in Spark. It then reviews common performance bottlenecks encountered by Spark users, along with tips for diagnosing performance problems in a production application.
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Enjoy the video: https://youtu.be/42Oo8TOl85I.
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StackOverflow
The document discusses stack overflow attacks and protection against them. It begins with an introduction to stack overflows, explaining that they occur when more items are pushed onto the stack than allocated space allows. This can overwrite adjacent memory and execute arbitrary code. Next, it describes the operation of the stack, how functions use stacks to store data and return addresses. The document then explains how attackers can exploit buffer overflows to manipulate the return address and inject shellcode to execute malicious code. Finally, it discusses some methods to protect against stack overflow attacks, such as bounds checking, address space layout randomization, and nonexecutable stacks.
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So you know you want to write a streaming app, but any non-trivial streaming app developer would have to think about these questions:
– How do I manage offsets?
– How do I manage state?
– How do I make my Spark Streaming job resilient to failures? Can I avoid some failures?
– How do I gracefully shutdown my streaming job?
– How do I monitor and manage my streaming job (i.e. re-try logic)?
– How can I better manage the DAG in my streaming job?
– When do I use checkpointing, and for what? When should I not use checkpointing?
– Do I need a WAL when using a streaming data source? Why? When don’t I need one?
This session will share practices that no one talks about when you start writing your streaming app, but you’ll inevitably need to learn along the way.
Intro to AutoML + Hands-on Lab - Erin LeDell, Machine Learning Scientist, H2O.ai
Presented at #H2OWorld 2017 in Mountain View, CA.
Enjoy the video: https://youtu.be/42Oo8TOl85I.
Learn more about H2O.ai: https://www.h2o.ai/.
Follow @h2oai: https://twitter.com/h2oai.
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This document discusses 5 common mistakes when writing Spark applications:
1) Improperly sizing executors by not considering cores, memory, and overhead. The optimal configuration depends on the workload and cluster resources.
2) Applications failing due to shuffle blocks exceeding 2GB size limit. Increasing the number of partitions helps address this.
3) Jobs running slowly due to data skew in joins and shuffles. Techniques like salting keys can help address skew.
4) Not properly managing the DAG to avoid shuffles and bring work to the data. Using ReduceByKey over GroupByKey and TreeReduce over Reduce when possible.
5) Classpath conflicts arising from mismatched library versions, which can be addressed using sh
STACK OVERFLOW DATASET ANALYSIS
The document describes a Big Data project analyzing the Stack Overflow dataset. Key points:
- The dataset was obtained from Stack Exchange and consists of XML files totaling around 20GB that were parsed and loaded into HDFS.
- The data was analyzed to identify trending questions, unanswered questions, closed questions, dead questions, top tags, and more. PageRank analysis was also performed to rank posts.
- The results were visualized in a web application using technologies like Hive, HBase, Pig, and Mahout recommendation. Performance issues were encountered during the MapReduce parsing of the large XML files.
Understanding Stack Overflow
In this talk we briefly discuss some of our recent studies of Stack Overflow, a popular Q&A site targeting software developers. As opposed to studies of software artefacts discussed at Stack Overflow (e.g., APIs or programming examples), we focus on studying individuals active on Stack Overflow---who are they, what motivates them, and what affects their participation in Stack Overflow discussions.
Our findings indicate that Stack Overflow is no different from other communities of software developers in terms of gender representation but is significantly different from them in terms of gender engagement: controlling for engagement duration women and men ask and answer comparable number of questions, but women disengage faster. We conjecture that faster disengagement of women is the less pretty consequence of gamification mechanisms embedded in Stack Overflow, the same gamification mechanisms that provide developers with faster answers than ever before, attract numerous contributors and ultimately catalyse software development.
As an additional contribution we present genderComputer, a tool inferring gender of an individual based on her/his name and location.
The talk is based on the following papers:
* Gender, representation and online participation: A quantitative study, Vasilescu, B., Capiluppi, A. and Serebrenik, A., Interacting with Computers. 2013, Oxford University Press.
* How social Q&A sites are changing knowledge sharing in open source software communities, Vasilescu, B., Serebrenik, A., Devanbu, P. T. and Filkov, V., In CSCW, 2014, ACM.
* StackOverflow and GitHub: Associations between software development and crowdsourced knowledge, Vasilescu, B., Filkov, V. and Serebrenik, A., In Social Computing, 2013, IEEE.
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3) Jobs running slowly due to data skew in joins and shuffles. Techniques like salting keys can help address skew.
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Real Time UI with Apache Kafka Streaming Analytics of Fast Data and Server Push
Real Time UI with Apache Kafka Streaming Analytics of Fast Data and Server Push
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Apache Arrow: High Performance Columnar Data Framework
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STACK OVERFLOW DATASET ANALYSIS
The document describes a Big Data project analyzing the Stack Overflow dataset. Key points:
- The dataset was obtained from Stack Exchange and consists of XML files totaling around 20GB that were parsed and loaded into HDFS.
- The data was analyzed to identify trending questions, unanswered questions, closed questions, dead questions, top tags, and more. PageRank analysis was also performed to rank posts.
- The results were visualized in a web application using technologies like Hive, HBase, Pig, and Mahout recommendation. Performance issues were encountered during the MapReduce parsing of the large XML files.
Understanding Stack Overflow
In this talk we briefly discuss some of our recent studies of Stack Overflow, a popular Q&A site targeting software developers. As opposed to studies of software artefacts discussed at Stack Overflow (e.g., APIs or programming examples), we focus on studying individuals active on Stack Overflow---who are they, what motivates them, and what affects their participation in Stack Overflow discussions.
Our findings indicate that Stack Overflow is no different from other communities of software developers in terms of gender representation but is significantly different from them in terms of gender engagement: controlling for engagement duration women and men ask and answer comparable number of questions, but women disengage faster. We conjecture that faster disengagement of women is the less pretty consequence of gamification mechanisms embedded in Stack Overflow, the same gamification mechanisms that provide developers with faster answers than ever before, attract numerous contributors and ultimately catalyse software development.
As an additional contribution we present genderComputer, a tool inferring gender of an individual based on her/his name and location.
The talk is based on the following papers:
* Gender, representation and online participation: A quantitative study, Vasilescu, B., Capiluppi, A. and Serebrenik, A., Interacting with Computers. 2013, Oxford University Press.
* How social Q&A sites are changing knowledge sharing in open source software communities, Vasilescu, B., Serebrenik, A., Devanbu, P. T. and Filkov, V., In CSCW, 2014, ACM.
* StackOverflow and GitHub: Associations between software development and crowdsourced knowledge, Vasilescu, B., Filkov, V. and Serebrenik, A., In Social Computing, 2013, IEEE.
Stackoverflow Data Analysis-Homework3
The document discusses a project to analyze Stack Overflow data to identify the next trending programming language. It states hypotheses that Stack Overflow data will be used to determine the trending language and why. It designed SAX parsers to handle the XML format data and assumes Java may be trending due to its widespread use. Elastic Search and Kibana will be used for analysis. Future plans include using the Stack Overflow API to collect live data through surveys and experiments.
StackOverflow Architectural Overview
- Study the architecture and design
- Compare Old & New Technology stack
- Analyze evolution of architecture and scalability
- Lessons learned over time
Analyzing Stack Overflow - Problem
This document describes an assignment to analyze response times for questions on Q&A websites like StackOverflow. Specifically, it involves analyzing questions from a gaming StackExchange dataset and calculating features related to tags for each question, including tag popularity, number of popular tags, number of active subscribers to tags, and percentage of subscribers who are active. Response times will then be plotted against these tag features to analyze correlations. The deliverables are to calculate the features for each question programmatically and generate box plots and CDF plots of response times for each feature.
Stack Overflow - It's all about performance / Marco Cecconi (Stack Overflow)
Stack Overflow, and its Q&A network Stack Exchange, have been growing exponentially for the last five years. They now encompass
~150 Q&A sites
~9 million users
~13 million questions
~22 million answers
In this talk, I will describe:
+ The physical architecture of Stack Overflow. How many servers are there? What is their purpose and what are their specs?
+ The logical architecture of the software. How do we scale up? What are the main building blocks of our software?
+ The tooling system. What supports our extreme optimization philosophy?
+ The development team. What are our core values? What footprint do we want to leave as developers?
Software Engineering and Social media
This document discusses the use of social media in software engineering. It explores several social media channels used in software development, including Q&A websites like Stack Overflow, microblogging platforms like Twitter, and developer blogs. For each channel, it summarizes relevant research that looks at how developers use these tools, what kinds of content and discussions they facilitate, and their potential benefits and risks. The document also considers how social media could enhance tasks like collaboration and learning, but also reverse trends like reliance on formal documentation or obsolesce tools like email lists. It concludes that while software development is becoming more collaborative, the impacts of social media are still unknown and require more research.
Towards the Social Programmer (MSR 2012 Keynote by M. Storey)
Audio+slide video is posted at http://margaretannestorey.wordpress.com.
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Repositorio Institucional para el manejo de Investigaciones de la UNAN-Manag...
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El documento describe un sistema de repositorio institucional basado en el software DSpace para almacenar y hacer accesibles las investigaciones realizadas en la UNAN-Managua. El repositorio permitiría incrementar la visibilidad y el prestigio de la universidad al proveer acceso público a las investigaciones producidas. El software DSpace, de código abierto, ofrece características como almacenar diferentes tipos de documentos digitales, organizarlos en comunidades y colecciones, y permitir el control y seguimiento de versiones.groovy & grails - lecture 13
This document discusses various topics related to programming efficiently in Groovy and Grails, including:
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Implementación Repositorio De Objetos De Aprendizajes Basado En
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What is Node.js used for: The 2015 Node.js Overview Report
This document discusses Node.js developers based on surveys from Moz.com and Stack Overflow. It provides statistics on Node.js developers such as their locations being mostly in the US, Canada, UK, Germany and India. It also discusses the technologies Node.js developers use most like JavaScript, PHP, AngularJS, MongoDB. Additional details are given on source control, work environments, and preferences around microservices architecture and coffee. The document promotes further insights into Node.js developers.
Presentacion MoodleMoot 2014 Colombia - Integración Moodle con un Repositorio...
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Responsive Design
Here at MRM, we are delivering new and exciting work with
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Stack_Overflow-Network_Graph
This document summarizes a project to visualize the relationships between questions in a network graph. It discusses using properties like node size, distance, and directed edges to represent the quality, similarity, and associations between questions. The team explored the data, performed cleansing and analysis, and used tools like R, Hive, and Sigma.js to generate the network graph and allow interactive exploration of the question relationships. The final product is deployed online for users to interact with the graph visualization.
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StrongLoop Overview
OpenSource API Server based on Node.js API framework built on supported Node.js platform with Tooling and DevOps. Use cases are Omni-channel API Server, Mobile Backend as a Service (mBaaS) or Next Generation Enterprise Service Bus. Key functionality include built in enterprise connectors, ORM, Offline Sync, Mobile and JS SDKs, Isomorphic JavaScript and Graphical API creation tool.
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This presentation describes the approach that I developed for Kaggle's WISE 2014 challenge. The challenge was about multi-label classification of printed media articles to topics. The main ingredients of my solution was a plug-in rule approach for F1 maximization, feature selection using a chi squared based criterion, feature normalization and a multi-view ensemble scheme.
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Modern HTML & CSS Coding: Speed, Semantics & Structure
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Exploratory Study of Slack Q&A Chats as a Mining Source for Software Engineer...
The document describes an exploratory study of mining information from Slack Q&A chat logs to support software engineering tools. The researchers analyzed conversations from several Slack communities to address how prevalent useful information is for tools (RQ1) and what challenges automatic mining faces (RQ2). Results found that while Slack contains similar information as Stack Overflow, identifying accepted answers is difficult. Future work is proposed to link Slack and Stack Overflow and mine conversations for insights.
Automatic Identification of Informative Code in Stack Overflow Posts
Despite Stack Overflow’s popularity as a resource for solving coding problems, identifying relevant information from an individual post remains a challenge. The overload of information in a post can make it difficult for developers to identify specific and targeted code fixes. In this paper, we aim to help users identify informative code segments, once they have narrowed down their search to a post relevant to their task. Specifically, we explore natural language- based approaches to extract problematic and suggested code pairs from a post. The goal of the study is to investigate the potential of designing a browser extension to draw the readers’ attention to relevant code segments, and thus improve the experience of software engineers seeking help on Stack Overflow.
01.intro
This document provides an overview of the ICS 314 and 613: Software Engineering course taught by Philip Johnson. It outlines the instructor's background and contact information, goals of the course, what constitutes "quality" software, open source development principles, standards and feedback, course structure, prerequisites, grading, differences between 314 and 613, lectures and labs, quizzes, engineering log requirements, developing a professional persona, collaboration vs. cheating policies, and lessons learned from past students.
Programming for Problem Solving
18 css101j pps unit 1
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This document provides an overview of a course on operating systems. It includes sections on course organization, objectives, outline, laboratories, assessments, exams, policies, and an introduction to key topics covered in the course like OS types, multiprogramming, scheduling algorithms like FCFS, SJF, and round robin. The course aims to provide a comprehensive tour of major OS components and concepts through lectures, labs, assignments, and exams.
Information-Rich Programming in F# with Semantic Data
Programming with rich data frequently implies that one
needs to search for, understand, integrate and program with
new data - with each of these steps constituting a major
obstacle to successful data use.
In this talk we will explain and demonstrate how our approach,
LITEQ - Language Integrated Types, Extensions and Queries for
RDF Graphs, which is realized as part of the F# / Visual Studio-
environment, supports the software developer. Using the extended
IDE the developer may now
a. explore new, previously unseen data sources,
which are either natively in RDF or mapped into RDF;
b. use the exploration of schemata and data in order to
construct types and objects in the F# environment;
c. automatically map between data and programming language objects in
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Devry CIS 355A Full Course Latest
Just Click on Below Link To Download This Course:
https://www.devrycoursehelp.com/product/devry-cis-355a-full-course-latest/
Go to a job posting site (CareerBuilder, Dice, ComputerJobs, etc.) or use search engines to find Java developer or Java programmer positions. Copy and paste the job posting into the Discussion area. Briefly explore all the topics that you will learn in this class this session. What are the skills you will learn in this course that are also requirements for the positions you see posted by you and your classmates?
Introduction to OpenSees by Frank McKenna
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This document provides an overview and introduction to a course on principles of compiler design. It discusses the motivation for studying compilers, as language processing is important for many software applications. It outlines what will be covered in the course, including the theoretical foundations and practical techniques for developing lexical analyzers, parsers, type checkers, code generators, and more. The document also describes the organization of the course with lectures, programming assignments, and exams.
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It covers RE tasks to which NLP is applied, an overview of a recent systematic mapping study on the topic, and a hands-on tutorial on using transfer learning for requirements classification.
Please find the links to the colab notebooks here:
https://colab.research.google.com/drive/158H-lEJE1pc-xHc1ISBAKGDHMt_eg4Gn?usp=sharing
https://colab.research.google.com/d rive/1B_5ow3rvS0Qz1y-KyJtlMNnm gmx9w3kJ?usp=sharing
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Seamless semantics - avoiding semantic discontinuity
Invited Talk at Summer School on Semantic Web, Bertinoro, 2015
Abstract:
Two decades ago one has discussed how to build seamless digital workflows
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and digital, because each transcription from one to another medium would
be laborious and cost-inefficient. Thus, the issue was avoiding *medium discontinuities*.
Today, we have all-digital data workflows, but we have still plenty of *semantic discontinuities*.
In this talk, I want first to describe reasons for this discontinuities including: autonomy of
data providers, need for agility and flexibility, or decentralized organizations in
the world-wide data spaces.
Then I want to describe several semantics discontinuities and some efforts to
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A New Hiring Paradigm
A successful startup requires the best possible talent. Great people are out there, but how do you find them? And how do you make them want to work for you? This session focuses on identifying the positions necessary for your startup to scale, attracting the best talent using limited resources, and making sure you have a plan in place to find the right people for the job.
Texas.gov Presents: Battle of Programming Languages
Software technology is evolving quickly. Platforms, programming languages, and frameworks are created at a pace faster than ever before. New techniques, processes, and standards are also emerging that can impact your organization, especially if you’re not prepared. There are times, though, that these same technologies also fade fast. Catching up with and staying abreast of new technologies is as important as knowing which technologies will yield long term results.
How can your organization's technology strategy keep up with all the changes? Join us for a light-hearted yet informative look at the “Battle of the Programming Languages” and our take on how to keep up with emerging technologies and techniques, and how you can align your organization's technology goals with the ever moving software industry.
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This document discusses competitive programming and compares several competitive programming websites. It finds that Codeforces has the most programming questions overall and hosts weekly programming contests. Codeforces also uniquely makes all participant code public and uses a rating system similar to chess ratings. While other sites like Hackerrank and Hackerearth have additional topics, Codeforces focuses solely on programming contests and exposes participants to a wide range of languages and problem types. The document shows Codeforces has the most questions in most categories like sorting and dynamic programming. It also finds Python is mostly used for simpler implementation questions while other languages may be better for more complex categories.
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原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
原件一模一样【微信：bwp0011】《(Humboldt毕业证书)柏林大学毕业证学位证》【微信：bwp0011】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
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留信网认证的作用:
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2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
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Convolutional Neural Network used for image classification
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Stack Overflow slides Data Analytics
- 1. What StackOverflow Tells Us About Programming Languages Rahul Thankachan Nada Aldarrab Prathmesh Gat University of Southern California 1
- 2. 2 Agenda
- 3. Agenda 1. Introduction 2. Problem Statement 3. Temporal Based Trend Analysis 4. Topic Analysis 5. Predicting Time To Answer 6. Summary and Q&A 3
- 5. Introduction • Dataset Used : Stackoverflow - Internet Archive. • Why? It is one of the largest developer focused open collaborative platform currently. • Through our study we intend to answers some interesting questions • Study the rise and fall of popular programming languages • Can be used to predict future enhancements • Study effectiveness of Stack Overflow model 5
- 6. Problem Definition • Basic Analysis: What are the most popular programming languages? • What are the trends in programming languages? • What are the most popular topics discussed in a programming language? • Can we accurately predict the time it takes until a questioner gets an answer? 6
- 7. Related Work Miltiadis Allamanis and Charles Sutton. 2013. Why, When and What: Analyzing Stack Overflow Questions by Topic, Type & Code In 10th Working Conference on Mining Software Repositories. Mining Challenge. IEEE, pages 53- 56. • Topic modeling analysis • Used Latent Dirichlet Allocation (LDA) • Modeled Java Topics of Questions • Can evaluate the orthogonality of different languages • Stack Overflow questions are about the code and are not application domain specific 7
- 8. Related Work V. Bhat, A. Gokhale, R. Jadhav, J. Pudipeddi, and L. Akoglu. Min (e) d your tags: Analysis of question response time in stackoverflow. In Proceedings of ASONAM 2014, pages 328–335. IEEE, 2014. • Two linear classifiers: logistic regression and SVM with linear kernel • Two non- linear classifiers: decision tree (DT) and SVM with radial basis function kernel 8
- 10. 10 Basic Analysis & Temporal Trends
- 11. StackOverFlow Activity 11 Approx. 45% of all programming languages in world are discussed on StackOverflow!
- 12. Post Type 12
- 15. Answer Count 15
- 22. Approach Following attributes selected for study: 1. Tag (Only top 10 programming languages) 2. Creation Month 3. Body Length 4. Tag Length 5. Introduced new Nominal class - Time_Answer 6. (less6, bet6and20, 20andmore) 22
- 23. Approach Tools Weka - Weka is a collection of machine learning algorithms for data mining tasks. Data Preprocessing: Challenging! 23
- 24. Approach(Data Pre -processing) 1. Parse all the answers and link first answer’s creation time to creation time of question. We called this field delta-answer. 2. Remove all the Questions which had delta answer negative or zero 3. We developed a Python script which develops .arff file On the fly (Wish to contribute this file) 24
- 25. Evaluation • Subset Size: 4490947 - Subset - 449000 • Classify response time into 3 types: less than 6 minutes, between 6 and 20 minutes, 20 minutes and more. • 10-fold cross-validation • Results are obtained using different feature combinations and different classifiers 25
- 26. Evaluation Results of classifier J48 (all Attributes) 26
- 27. Evaluation 27 Results of classifier (body_length/ tag_length)
- 28. Summary • We were successfully able to find interesting temporal trends for major programming languages • Using tag based topic analysis we were able to find major discussion topics and to some extent the difficult topics in a programming language • Using machine learning techniques we were successfully able to predict - time to answer with good accuracy 28
- 29. Future Scope of Work • Contribute the .arff on the fly generator script. • Adding Parts of speech as an attribute • Showcasing the results on a website 29
- 30. Questions? 30