Being a Mentor in open source projects

Mentoring is a well-known way to help newcomers to Open Source Software (OSS) projects overcome initial contribution barriers. Through mentoring, newcomers learn to acquire essential technical, social, and organizational skills. Despite the importance of OSS mentors, they are understudied in the literature. Understanding who OSS project mentors are, the challenges they face, and the strategies they use can help OSS projects better support mentors’ work. In this paper, we employ a two-stage study to comprehensively investigate mentors in OSS. First, we identify the characteristics of mentors in the Apache Software Foundation, a large OSS community, using an online survey. We found that less experienced volunteer contributors are less likely to take on the mentorship role. Second, through interviews with OSS mentors (n=18), we identify the challenges that mentors face and how they mitigate them. In total, we identified 25 general mentorship challenges and 7 sub-categories of challenges regarding task recommendation. We also identified 13 strategies to overcome the challenges related to task recommendation. Our results provide insights for OSS communities, formal mentorship programs, and tool builders who design automated support for task assignment and internship.

Being a Mentor in Open Source Projects

A well-known way to help newcomers overcome initial contribution challenges is mentoring. This strategy has proven effective in offline and online communities, and to some extent has been employed in Open Source Software (OSS) projects. Through mentoring, newcomers are trained to acquire the technical, social, and organizational skills they need. Despite the importance of OSS mentors, they are under studied in the literature. Understanding who mentors in OSS projects are, the challenges they face, and the strategies they use can help OSS projects better understand and support mentors' work. In this paper, we investigate the OSS mentors' perspectives by employing a two-stage study. First, we understand the characteristics of the mentors in a large OSS community through a large-scale online survey in the Apache Software Foundation. We found that contributors who are volunteers and less experienced are less likely to take on the role of mentoring. Second, we identify the challenges that mentors face and how they mitigate these challenges through interviews with OSS mentors (n=18). In total, we identified 25 general mentorship challenges and 7 sub-categories of challenges regarding task recommendation. We also identified 13 strategies to overcome these challenges. Our results provide insights for OSS communities, formal mentorship programs like Outreachy, and tool builders who design automated support for task assignment and internship.

The research of social processes at the university using big data

The volume of information in the 21st century is growing at a rapid pace. Big data technologies are used to process modern information. This article discusses the use of big data technologies to implement monitoring of social processes. Big data has its characteristics and principles, which reflect here. In addition, we also discussed big data applications in some areas. Particular attention in this article pays to the interactions of big data and sociology. For this, there consider digital sociology and computational social sciences. One of the main objects of study in sociology is social processes. The article shows the types of social processes and their monitoring. As an example, there is implemented monitoring of social processes at the university. There are used following technologies for the realization of social processes monitoring: products 1010data (1010edge, 1010connect, 1010reveal, 1010equities), products of Apache Software Foundation (Apache Hive, Apache Chukwa, Apache Hadoop, Apache Pig), MapReduce framework, language R, library Pandas, NoSQL, etc. Despite this, this article examines the use of the MapReduce model for social processes monitoring at the university.

Perangkat Lunak Enterprise Resource Planning (ERP) Berbasis Open Source Menggunakan Apache OFBiz

Apache OFBiz adalah produk open source yang dirancang khusus untuk otomatisasi proses perusahaan yang mencakup komponen kerangka kerja dan aplikasi bisnis untuk ERP (Enterprise Resource Planning), CRM (Customer Relationship Management), E-Business / E-Commerce, SCM (Supply Chain Management), MRP (Manufacturing Resource Planning), MMS/EAM (Maintenance Management System/Enterprise Asset Management). Proyek Apache OFBiz adalah bagian dari The Apache Software Foundation dan dilisensikan di bawah Apache License Version 2.0. Awalnya OFBiz berdiri untuk terbuka untuk bisnis " Open For Business." Apache OFBiz menyediakan fondasi sistem dan titik awal untuk solusi perusahaan yang andal, aman, dan skalabel. Perusahaan dapat menggunakannya, menyesuaikannya atau menggunakannya sebagai kerangka untuk mengimplementasikan kebutuhan bisnis mereka. Dengan OFBiz, sebuah organisasi dapat segera dimulai tanpa biaya penyebaran dan pemeliharaan besar untuk sistem otomatisasi perusahaan tradisional. Seiring pertumbuhan bisnis, mereka dapat memperluas fungsi untuk memenuhi kebutuhan mereka yang lebih canggih. Apache OFBiz menawarkan banyak fungsi bisnis, termasuk: e-commerce, manajemen katalog yang efisien, promosi & manajemen harga, manajemen pesanan aman untuk penjualan & pembelian, manajemen pelanggan (bagian dari manajemen pihak umum), manajemen gudang total, mencakup bagian seperti pemindahan stok secara otomatis, pemilihan batch, dan pengemasan & pengiriman, akuntansi untuk berbagai tujuan seperti faktur, akun pembayaran & penagihan, dan aset tetap, manajemen manufaktur lengkap, manajemen usaha yang umum mencakup bidang utama seperti acara, tugas, proyek, dan permintaan serta pengelolaan konten aman yang mencakup area seperti konten produk, situs web, konten umum, blog, dan forum.

Hadoop History and Architecture

As the name indicates, this chapter explains the evolution of Hadoop. Doug Cutting started a text search library called Lucene. After joining Apache Software Foundation, he modified it into a web crawler called Apache Nutch. Then Google File System was taken as reference and modified as Nutch Distributed File System. Then Google's MapReduce features were also integrated and Hadoop was framed. The whole path from Lucene to Apache Hadoop is illustrated in this chapter. Also, the different versions of Hadoop are explained. The procedure to download the software is explained. The mechanism to verify the downloaded software is shown. Then the architecture of Hadoop is detailed. The Hadoop cluster is a set of commodity machines grouped together. The arrangement of Hadoop machines in different racks is shown. After reading this chapter, the reader will understand how Hadoop has evolved and its entire architecture.