Introduction

Linux Statistics: Linux, being an open-source operating system, has become a significant factor in computing. It serves as the energy source for everything from personal gadgets like mobile phones to enormous servers located within data centers. As we move toward 2024, demand for Linux remains on the steep rise, particularly in cloud computing, web hosting, and even personal computers. In other words, Linux has become more important as companies seek to cut down costs, boost their efficiency, and enhance security.

By 2024, about 45% of the global server operating system market will still be held by Linux due to its flexibility, security, and affordability. For instance, there has been a tremendous increase in the use of Linux for cloud computing. A lot of companies like AWS, Google Cloud, and Microsoft Azure use a number of their services based on servers running on Linux platforms.

This paper analyses some key Linux statistics related to the use of Linux through 2024, which includes but is not limited to the share market growth rate across different sectors' economic impact and the introduction of new distributions that are likely to determine its destiny as an OS.

Introduction

Fedora Statistics: Fedora is a very popular operating system based on Linux, which is cutting-edge and has very good community support. However, at the end of December 2024, Fedora did not have much market penetration as far as web server deployment was concerned.

According to W3Techs, out of all the websites whose operating system is known, less than 0.1% use Fedora, while 55.2% of these websites are powered by Linux as a whole. This article will show the trends in Fedora statistics.

Cuckoo Sandbox is the leading open sourceautomated malware analysis system. You can throw any suspicious file atit and in a matter of seconds Cuckoo will provide you back some detailedresults outlining what such file did when executed inside an isolatedenvironment.

Cuckoo Sandbox is free software that automated the task of analyzing any malicious file under Windows, OS X, Linux, and Android.

What can it do?

Cuckoo Sandbox is an advanced, extremely modular, and 100% open source automated malware analysis system with infinite application opportunities. By default it is able to:


Analyze many different malicious files (executables, office documents, pdf files, emails, etc) as well as malicious websites under Windows, Linux, Mac OS X, and Android virtualized environments.
Trace API calls and general behavior of the file and distill this into high level information and signatures comprehensible by anyone.
Dump and analyze network traffic, even when encrypted with SSL/TLS. With native network routing support to drop all traffic or route it through InetSIM, a network interface, or a VPN.
Perform advanced memory analysis of the infected virtualized system through Volatility as well as on a process memory granularity using YARA.


Due to Cuckoo s open source nature and extensive modular design one may customize any aspect of the analysis environment, analysis results processing, and reporting stage. Cuckoo provides you all the requirements to easily integrate the sandbox into your existing framework and backend in the way you want, with the format you want, and all of that without licensing requirements.

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The statistic shows distribution of operating systems used by Internet of Things developers, according to a survey conducted in 2016. At that time, 73.1 percent of respondents indicated that they were using Linux for working on IoT devices.

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As of September 2023, the most frequently used OS by users of the gaming platform Steam was Windows at almost 97 percent. Linux followed in second place, with 1.6 percent, ahead of OSX with 1.43 percent share.

The Linux-based Network Operating System (NOS) market has increasingly established itself as a crucial element of modern IT infrastructure, providing robust solutions that cater to the ever-evolving needs of businesses across various sectors. Renowned for its open-source nature, which promotes flexibility and custom

The Linux-based Network Operating System (NOS) market is experiencing robust growth, driven by increasing demand for software-defined networking (SDN) and network function virtualization (NFV) solutions. The open-source nature of Linux, coupled with its flexibility and cost-effectiveness, is attracting enterprises seeking to modernize their network infrastructure and reduce operational expenses. This shift away from proprietary NOS solutions is particularly pronounced in data centers, cloud environments, and service provider networks, where scalability and agility are paramount. Key drivers include the need for increased automation, improved network programmability, and the desire for vendor lock-in avoidance. While the market is still relatively nascent compared to traditional NOS vendors, its Compound Annual Growth Rate (CAGR) is estimated to be around 25% between 2025 and 2033, leading to substantial market expansion. This growth is further fueled by advancements in containerization technologies like Docker and Kubernetes, enhancing the deployment and management of network services. The major players—Cumulus Networks, IP Infusion, Pica8, Pluribus Networks, Big Switch Networks, Mellanox, SnapRoute, Kaloom, and Arrcus—are actively innovating to meet this escalating demand, contributing to the overall dynamism of the market. However, challenges remain, including the need for enhanced security features and the complexity associated with integrating Linux-based NOS into existing network environments. Despite these challenges, the long-term outlook for Linux-based NOS remains positive. The market's inherent advantages, including cost savings, flexibility, and enhanced scalability, are attracting a growing number of adopters. The continued development of open-source communities and industry collaborations will further drive innovation and ecosystem growth. As enterprises increasingly embrace cloud-native architectures and DevOps methodologies, the demand for Linux-based NOS solutions will only intensify, propelling the market towards substantial growth in the coming years. The estimated market size in 2025 is $2 billion, projected to reach $8 billion by 2033 based on a conservative 25% CAGR. This growth is expected across various segments, including data centers, cloud providers, and telecommunications.

The global monitoring software market, valued at $314.9 million in 2025, is projected to experience robust growth, driven by the increasing adoption of cloud-based solutions, the expanding Internet of Things (IoT) ecosystem, and the rising demand for real-time data analytics across diverse industries. The market's 7.5% CAGR signifies a consistent upward trajectory through 2033, fueled by the need for enhanced operational efficiency, proactive maintenance, and improved risk management. Key application segments, such as real-time and web-based software, are witnessing significant traction due to their flexibility and accessibility. The prevalence of diverse operating systems (Windows, macOS, Linux, and web browsers) ensures broad compatibility, further boosting market expansion. While the market faces potential restraints such as high initial investment costs and the complexity of integrating monitoring systems with existing infrastructure, the continuous innovation in software capabilities and the development of user-friendly interfaces are mitigating these challenges. The North American market currently holds a significant share, owing to strong technological advancements and early adoption of monitoring solutions. However, the Asia-Pacific region is poised for substantial growth, driven by rapid industrialization and increasing digital transformation initiatives in countries like China and India. The competitive landscape is characterized by a blend of established players and emerging technology providers. Companies such as 3M, Mitsubishi, and GE leverage their existing industrial expertise to offer integrated monitoring solutions. Meanwhile, specialized software developers like Kisters AG and InfinityQS are focusing on niche applications and advanced analytics. The presence of a diverse range of companies reflects the market's maturity and the opportunities for innovation across different segments and geographic regions. Future growth will be shaped by factors such as the integration of artificial intelligence (AI) and machine learning (ML) for predictive maintenance, the development of more sophisticated data visualization tools, and the increasing demand for cybersecurity solutions within monitoring systems. The market's expansion will likely be most pronounced in industries with stringent regulatory requirements and a high reliance on operational uptime, such as manufacturing, energy, healthcare, and transportation.

ABSTRACT In this paper, a new software for Statistical Process Control (SPC) is proposed. The system, the so-called CEP Online, was developed based on statistical computing resources of well-known free softwares, such as HTML, PHP, R and MySQL under an online server with operating system Linux Ubuntu. The main uni and multivariate SPC tools are available for monitoring and evaluation of manufacturing and non-manufacturing production processes over time. Some advantages of the new software are: (i) low operational cost, since it is cloud-based, only needing a computer connected to the Internet; (ii) easy to use with great interaction with the user; (iii) it does not require investment in any specific hardware or software; (iv) real time reports generation on process condition monitoring and process capability. Thus, the CEP Online offers for SPC practitioners fast, efficient and accurate SPC procedures. Therefore, CEP Online becomes an important resource for those who have no access to non-free softwares, such as SAS, SPSS, Minitab and STATISTICA. To the best of our knowledge, the CEP Online is unique with respect to its characteristics.

The High Availability Server market is experiencing robust growth, projected to reach a significant market size with a Compound Annual Growth Rate (CAGR) of 16% from 2025 to 2033. This expansion is fueled by several key drivers. Increasing reliance on mission-critical applications across diverse sectors, such as IT & Telecommunications, BFSI (Banking, Financial Services, and Insurance), and Healthcare, demands uninterrupted uptime. The growing adoption of cloud-based solutions and the rise of big data analytics further contribute to market growth. Businesses are increasingly investing in high-availability servers to ensure data integrity, minimize downtime, and enhance operational efficiency. While on-premise deployments remain prevalent, the shift towards cloud-based solutions is gaining momentum, driven by scalability, cost-effectiveness, and enhanced disaster recovery capabilities. The market is segmented by operating system (Windows, Linux, and others), deployment (cloud-based and on-premise), and end-user industry, reflecting the diverse applications of high-availability servers. Competitive landscape analysis indicates major players such as Dell, Oracle, Cisco, IBM, and Amazon Web Services are actively shaping market dynamics through innovation and strategic partnerships. The market's growth trajectory is not without challenges. Potential restraints include the high initial investment costs associated with implementing high-availability solutions, the complexity of managing such systems, and the need for specialized expertise. However, ongoing technological advancements, increasing awareness of data security risks, and the rising adoption of virtualization and containerization technologies are expected to mitigate these challenges and further propel market expansion. The Asia Pacific region is anticipated to show significant growth, driven by rapid technological advancements and increasing digitalization across various sectors. North America and Europe are expected to maintain strong market positions owing to the mature IT infrastructure and high adoption rates of advanced technologies within these regions. The forecast period, 2025-2033, presents significant opportunities for market players to capitalize on the growing demand for robust and reliable server solutions. Key drivers for this market are: , High Adoption Rate of High Availability Server Across BFSI Sector; Growing Demand for Modular & Micro Data Center with the Increasing Application of IoT Devices. Potential restraints include: , High Adoption Rate of High Availability Server Across BFSI Sector; Growing Demand for Modular & Micro Data Center with the Increasing Application of IoT Devices. Notable trends are: BFSI Sector is Expected to Have a Significant Growth Rate.

Replication package of incivility in code review discussions of rejected patches in the Linux community.

Web application as free reference manager and academic social network to organize your research, collaborate with others online, and discover the latest research. Automatically generate bibliographies, Collaborate easily with other researchers online, Easily import papers from other research software, Find relevant papers based on what you're reading, Access your papers from anywhere online, Read papers on the go with the iPhone app. The software, Mendeley Desktop, offers: * Automatic extraction of document details * Efficient management of your papers * Sharing and synchronization of your library (or parts of it) * Additional features: A plug-in for citing your articles in Microsoft Word, OCR (image-to-text conversion, so you can full-text search all your scanned PDFs), etc The website, Mendeley Web, complements Mendeley Desktop by offering these features: * An online back up of your library * Statistics of all things interesting * A research network that allows you to keep track of your colleagues' publications, conference participations, awards etc * A recommendation engine for papers that might interest you.

This dataset contains the data platform for the research project "OwnReality. To Each His Own Reality". During the course of the project, data was gathered and entered into a database. In general, this platform allows the integration of that data into web based systems such as content management systems. To be independent of the target technology, the integration is implemented with a set of customized html tags with no assumptions on lower layers. An API-only web application retrieves the data from an elasticsearch instance and relays to the widgets. A README in this dataset serves as documentation. It aims to provide information on: the requirements to run the application how to set up the API-application importing the data from the included json documents importing the additional image data building the javascript integration asset how to integrate the widgets on a third-party page Requirements linux (not a requirement but the howto in documentation assumes linux) elasticsearch (2.2.3) ruby (2.2.5) nodejs (4.4.4), only for building

The global sales tracking software market is experiencing robust growth, driven by the increasing need for businesses of all sizes to optimize sales processes, enhance revenue generation, and gain a competitive edge. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $40 billion by 2033. This growth is fueled by several key factors. The widespread adoption of cloud-based solutions offers scalability, accessibility, and cost-effectiveness, attracting a broader range of users. Furthermore, the integration of advanced analytics and artificial intelligence (AI) within these platforms provides valuable insights into sales performance, enabling data-driven decision-making and improved forecasting accuracy. The rising demand for sales automation tools and improved customer relationship management (CRM) capabilities also contributes significantly to market expansion. Segmentation reveals strong demand across various applications (Mac, Windows, Linux), deployment types (on-premise, cloud-based, web-based), and geographic regions, with North America and Europe currently dominating the market. However, the market also faces certain challenges. The high initial investment cost for some enterprise-grade solutions can be a barrier for small and medium-sized businesses (SMBs). Concerns around data security and privacy, particularly with cloud-based solutions, also need to be addressed. Despite these restraints, the continued innovation in sales tracking technologies, the growing adoption of digital sales strategies, and the expanding use of mobile-optimized platforms are expected to propel market growth throughout the forecast period. The competitive landscape is highly fragmented, with a mix of established players and emerging startups vying for market share. This dynamic environment encourages innovation and offers a diverse range of solutions to meet the evolving needs of businesses across various industries.

The Server Operating System (OS) market, valued at $18.05 billion in 2025, is projected to experience robust growth, driven by the increasing adoption of cloud computing, the proliferation of data centers, and the rising demand for high-performance computing across various industries. The market's Compound Annual Growth Rate (CAGR) of 10.87% from 2025 to 2033 indicates a significant expansion in market size over the forecast period. Key drivers include the need for enhanced security, improved scalability and reliability, and the growing adoption of virtualization technologies. Trends like the increasing use of containerization and serverless computing are further shaping the market landscape. While factors such as the high initial investment costs associated with server OS implementations and the complexity of managing diverse operating systems may act as restraints, the overall market outlook remains positive. The market is segmented by deployment model into on-premises and cloud solutions, with the cloud segment expected to dominate owing to its flexibility, cost-effectiveness, and ease of scalability. Leading players like Microsoft, Linux distributors (e.g., Red Hat, SUSE), and other vendors are competing aggressively through strategic partnerships, product innovations, and competitive pricing strategies. Regional growth is anticipated across North America, Europe, and Asia-Pacific, driven by technological advancements and increasing digital transformation initiatives in these regions. The competitive landscape is characterized by the presence of both established players and emerging niche vendors. Companies are focusing on offering robust security features, enhanced management tools, and seamless integration with other cloud services to gain a competitive edge. The market's future hinges on the continued adoption of cloud-based solutions, the growth of edge computing, and the increasing demand for AI and machine learning capabilities within server environments. The continued evolution of open-source operating systems and the ongoing development of containerization technologies will also play a crucial role in shaping the market's future trajectory. The success of individual companies will depend on their ability to adapt to these evolving market dynamics and deliver innovative solutions that meet the ever-changing needs of enterprises and businesses of all sizes.

A web-based browser for Gene Ontology terms and annotations, which is provided by the UniProtKB-GOA group at the EBI. It is able to offer a range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation. The software for QuickGO is freely available under the Apache 2 license. QuickGO can supply GO term information and GO annotation data via REST web services.

The dataset contains source code and data relevant for the paper "Combining Model Learning and Model Checking to Analyze TCP Implementations".Paper url: https://link.springer.com/chapter/10.1007/978-3-319-41540-6_25PDF url: http://www.sws.cs.ru.nl/publications/papers/fvaan/FJV16/main.pdfRamon Janssen's Master's thesis url: http://www.ru.nl/publish/pages/769526/z_thesis_ramon_janssen.pdfIn this work, we use automata learning with abstraction to infer models of 3 TCP client and server implementations (Windows, Linux, FreeBSD). We then verify properties on these models using the NuSMV model checker. The dataset comprises the software components of our experimental setup apart from the actual implementations, some useful scripts and the learned models and associated experimental logs.In more concrete terms, the dataset contains:- the learner (setup) implementation - Java code for the setup built around LearnLib to perform learning with abstraction over sockets. Abstraction is provided by a mapper, described in a mapper language described in the Master's thesis.- the mapper library - Java code for loading mappers written in the mapper language and executing them in both directions (from abstract to concrete and from concrete to abstract)- the network adapter - crafts packets from strings or messages ("SYN(0,10)") and sends them to a TCP entity, receives packets and turns them back to strings- mappers - the mappers defined for the three operating systems learned- experimental data - Mealy Machine models for 6 TCP client/server implementations (BitVise, OpenSSH, DropBear) accompanied by other experimental data (statistics, input configuration ...)- model checking setup - project comprising bash scripts and Java libraries used to perform model checking on the learned models, model checking is mostly automatedWhat can be re-used:- the learner setup (connect to the learner through the mapper to a different system over sockets), note that there are some limitations of the mapper language- the mapper adapter, again note the limitations which fit the TCP case study but may not fit other case studies- the network adapter, can be adapted to learn other lower layer protocols or can be tweaked to include more information from packets in strings- model checking setup, this cannot really be reused outside of the TCP case study but it may serve as inspiration for one who wants to perform model checking of concretized abstract models (the mappers used to learn the models were also used to concretize them during model checking) or of interactions between two parties- beautifying Java library (if one wants to make complex .dot files more readable)Also, the dataset is suitable for one who wants to try out/expand learning for TCP. Learning and model checking can be done with minimal adaptation (perhaps slight changes in the mapper and adapting the model checking scripts).Paper Abstract: We combine model learning and model checking in a challenging case study involving Linux, Windows and FreeBSD implementations of TCP. We use model learning to infer models of different software components and then apply model checking to fully explore what may happen when these components (e.g. a Linux client and a Windows server) interact. Our analysis reveals several instances in which TCP implementations do not conform to their RFC specifications.