## 4. Foundation Insights

As a non-profit open source organization, the Foundation plays an indispensable role in promoting the organization, development and collaborative innovation of open source projects and communities. It not only provides a full range of services such as technical support, operation and management, and legal protection for the incubation of open source software, but also provides governance guidance for the construction and operation of the community, becoming a combination of incubator and accelerator, and injecting the power of continuous development into the open source ecology. As an important organizer of the open source ecosystem, foundations play the role of a bridge between developers, enterprises and the community due to their standardized operation mode and resource integration ability. This section analyzes the development of the open source ecology from the dimension of foundations, aiming to reveal the core position and actual contribution of foundations in the open source ecology through data insights.

### 4.1 OpenRank Trend Analysis of Global Foundations

<center>Figure 4.1 OpenRank Trend of Global Foundations</center>
<br>

*Note: The Linux Foundation mentioned here does not include its sub-foundations.

- The OpenAtom Foundation has performed particularly prominently, with its influence continuing to rise rapidly, becoming the highlight of 2024. This reflects its strong ecosystem expansion capabilities and project influence.

- In contrast, the growth momentum of CNCF (Cloud Native Computing Foundation) and Apache Software Foundation has significantly slowed. Although they still maintain a high level of influence, their OpenRank saw a slight decline in 2024, which may reflect the maturation of cloud-native technologies and intensified competition.

- Meanwhile, the Linux Foundation continues to develop steadily, demonstrating strong stability. Foundations such as the OpenJS Foundation and Hyperledger Foundation have shown little fluctuation.

The overall trend in 2024 indicates that rapidly growing foundations are gaining market recognition through innovative technologies and robust community ecosystems, while mature foundations need to find new breakthroughs to cope with increasingly fierce competition while maintaining their existing advantages.

### 4.2 OpenRank Trend Analysis of Global Foundation Projects

<center>Figure 4.2 OpenRank of Global Foundation Projects</center>

* The influence of the OpenHarmony/docs has risen rapidly, with its OpenRank reaching a historic high in 2024, likely due to the expansion of its ecosystem and the promotion of community activities.
* In contrast, the OpenRank of Kubernetes/kubernetes has been declining since 2020, and its influence further weakened in 2024. This may be closely related to a decrease in community activity or the rise of competitors.
* Apache/doris is another project worth noting, as its OpenRank continued to grow steadily in 2024. This indicates that the project's performance in the field of data processing continues to gain recognition from users and the community.
* Meanwhile, some mature projects, such as Cilium/cilium and Envoyproxy/envoy, showed relatively stable performance in 2024, with minimal fluctuations in OpenRank. This suggests that these projects have entered a stable development phase, maintaining their influence at a certain level.

### 4.3 OpenRank Trend Analysis of the Global Foundation's Chinese Projects

<center>Figure 4.3 OpenRank Trends of Chinese Projects Under Foundations
</center>
<br>

In 2024, among the Chinese projects under foundations, top projects experienced rapid growth, while others developed steadily. Chinese open-source projects demonstrated strong influence and growth potential across various technical fields.

* openharmony/docs ranked first, and other core modules of OpenHarmony (such as graphic_graphic_2d, interface_sdk-js, and xts_acts) also ranked high, reflecting the OpenHarmony community's strong emphasis on promoting ecosystem development. This indicates that OpenHarmony has built a mature and active community ecosystem in the operating system field, with its core components gaining widespread attention and participation from developers.
* Chinese projects have also shown significant influence in the database field. In the field of distributed data processing and storage, apache/doris, as a high-performance analytical database project, ranked second, highlighting its importance in big data and analytics scenarios. Additionally, milvus-io/milvus, focused on vector database development, along with apache/flink and apache/shardingsphere, represents the innovative capabilities of domestic developers in real-time computing and distributed database technologies.

* Furthermore, openeuler/kernel, as a core module of openEuler, is a representative project in the domestic operating system field, reflecting continuous progress in foundational software technologies and the achievements of community collaboration. Meanwhile, openharmony-sig/arkcompiler_runtime_core demonstrates that the domestic operating system ecosystem not only focuses on kernel development but also emphasizes breakthroughs in key technologies such as compilers and runtime systems.

### 4.4 OpenRank Trend Analysis of Chinese Projects Under the Linux Foundation

<center>Figure 4.4 OpenRank Trends of Chinese Projects Under the Linux Foundation (Including Sub-Foundations)</center>

As a key organization in the global open-source community, the participation and development of Chinese projects within the Linux Foundation reflect China's influence in the global open-source ecosystem.

The OpenRank of the milvus-io/milvus has grown rapidly. Milvus is an open-source vector database project initiated by Zilliz and contributed to the LF AI & Data Foundation, a sub-foundation of the Linux Foundation. It focuses on the efficient storage and retrieval of unstructured data (such as images, videos, audio, and text), making it particularly suitable for machine learning and artificial intelligence-related scenarios. In 2024, milvus-io/milvus ranked sixth in the Linux Foundation's OpenRank, showcasing China's strong influence in the fields of big data and artificial intelligence.

Overall, the OpenRank of most projects remains relatively low and shows little change. This disparity provides insights for other Chinese projects: by leveraging technological innovation, market adaptation, and community engagement, projects can enhance their competitiveness and vitality, ensuring long-term influence in the open-source ecosystem.

### 4.5 OpenRank Analysis of Projects Under the OpenAtom Foundation


<center>Figure 4.5 OpenRank Trends of Projects Under the OpenAtom Foundation
</center>

* OpenHarmony continues to hold the top position, with its OpenRank metric showing significant growth compared to 2023, increasing by nearly 70%. This demonstrates its strong appeal as a core project. Such growth may be attributed to its widespread application in smart devices and operating systems, as well as the continuous investment and support from its community.

* openEuler follows closely behind, maintaining its growth momentum in 2024 with steady increases in OpenRank. This indicates its expanding influence in the field of open-source operating systems and its further adoption in cloud computing and enterprise applications.

* The performance of Anolis OS and openKylin in 2024 has been relatively stable. Although their growth rates are not as pronounced as the top two, they remain competitive in specific domains. Anolis OS focuses on the enterprise Linux market, while openKylin targets domestic operating systems, both maintaining a certain level of recognition within their target user groups.

* Other projects such as Taro, UBML, and PikwiDB have lower OpenRank values, reflecting their limited ecosystem scale or the fact that their application scenarios have not yet been widely adopted.
<br>

## 5. Technology Insights

The development of technology plays a pivotal role in the open-source ecosystem, with numerous subdomains demonstrating rapid progress and transformation. Operating Systems: Continuously adapting to new architectures and evolving within the open-source community, showcasing strong ecosystem expansion capabilities. Cloud-Native Technologies: Driving enterprise digital transformation, with an active and rapidly growing open-source project ecosystem, becoming a key driver of technological innovation. Databases: As the core infrastructure for data innovation, the widespread adoption of open-source technologies has facilitated breakthroughs in diverse scenarios. Big Data: Leveraging open-source tools to provide robust support for intelligent decision-making, advancing data-driven applications. Artificial Intelligence: Accelerating automation across industries through open-source frameworks, emerging as a critical force in technological transformation. Front-End Technologies: Enhancing interactive experiences and visual design through open-source projects, improving user experience and development efficiency. These fields, characterized by their openness and innovativeness, have attracted significant attention from developers and investors. This section will provide a data-driven analysis of these technology domains based on two key metrics: influence and activity, revealing their development trends and future potential.

### 5.1 Trends in the Technical Subfields over the Past 5 years

<center>Figure 5.1 OpenRank of Technology Category 2020-2024 </center>
<br>

<center>Figure 5.2 Activity of Technology Category 2020-2024 </center>
<br>

From the trends observed in various categories over the past five years, cloud-native technologies have shown a clear advantage, with a relatively higher number of repositories compared to other areas. AI has experienced significant growth in recent years, reflecting its rapid development. Databases, as critical foundational software, have consistently maintained a strong presence due to their high activity levels. The popularity of big data saw a slight decline in 2024. Although the operating systems field has fewer repositories, its influence has been steadily increasing, highlighting the high value of foundational software. Meanwhile, the influence of front-end technologies has been gradually declining.

### 5.2 OpenRank of Top 10 Projects in Each Category over the Past 5 Years

#### Big Data

<center>Figure 5.3 OpenRank of Big data 2020-2024 </center>
<br>

<center>Figure 5.4 Activity of Big data 2020-2024 </center>
<br>

In the big data section, the two key metrics have shown an overall upward trend, with Kibana and Grafana consistently ranking in the top two in terms of influence and activity. Notably, the gap between the two narrowed gradually in 2023, but began to widen again in 2024. Additionally, the competition between Clickhouse and Doris in the big data space is becoming increasingly intense.

Kibana is an open-source data visualization and exploration tool that seamlessly integrates with ElasticSearch, supporting querying, analyzing, and visualizing ElasticSearch data.

Grafana, on the other hand, is a powerful open-source data visualization tool widely used in monitoring and reporting scenarios. It supports multiple data sources, including Prometheus, InfluxDB, and Graphite, and can generate various types of charts and dashboards, providing users with flexible data display and analysis capabilities.

#### Database

<center>Figure 5.5 OpenRank of Database 2020-2024 </center>
<br>

<center>Figure 5.6 Activity of Database 2020-2024 </center>
<br>

ClickHouse database continues stable growth in both metrics, ElasticSearch returns to the top three, and although Doris' growth rate has slowed, its activity metric is now close to the top. It is expected that its overall ranking may surpass ClickHouse in the future. Additionally, YDB has shown significant growth, successfully entering the top ten rankings in 2024.

ClickHouse is an open-source high-performance analytical engine developed by Russia’s Yandex, based on an MPP (Massively Parallel Processing) architecture. Its vectorized execution engine claims to be 100-1000 times faster than traditional transactional databases while offering rich features and high reliability.

Apache Doris, contributed by Baidu, is an open-source MPP analytical database with a simple distributed architecture that is easy to maintain and is widely used in efficient real-time analytical scenarios.

YDB was released as an open-source project in 2020, designed to provide a high-performance distributed database that supports ACID transactions, making it especially suitable for high-concurrency and distributed application scenarios. Initially developed to address Yandex’s internal technical challenges, YDB has gained increasing attention from developers and enterprises since its open-sourcing and has become a part of the modern distributed database landscape.

#### Operating System

<center>Figure 5.7 OpenRank Operating System 2020-2024 </center>
<br>

<center>Figure 5.8 Activity of Operating System 2020-2024 </center>
<br>

It can be observed that multiple repositories under the OpenHarmony project are ranked in the top ten. This analysis incorporates data from the Gitee platform, providing a clearer view of the various advantages of domestic operating systems. Additionally, the OpenEuler Kernel project has also demonstrated strong performance.

#### Cloud Native

<center>Figure 5.9 OpenRank of Cloud Native 2020-2024 </center>
<br>

<center>Figure 5.10 Activity of Cloud Native 2020-2024 </center>
<br>

LLVM-Project has a significant growth rate, ranking first in both indicators; Grafana's growth rate has slowed down, ranking second; Kubernetes's two indicators have declined significantly, and the competition for other projects is fierce.

LLVM is a modular, reusable collection of compiler frameworks and toolchain technologies. It has grown rapidly in activity in the past three years and is deeply loved by developers.

#### Frontend

<center>Figure 5.11 OpenRank of Frontend 2020-2024 </center>
<br>

<center>Figure 5.12 Activity of Frontend 2020-2024 </center>
<br>

Flutter has experienced a gradual decline in both metrics, yet still maintains a clear advantage over Next.js. Next.js, which showed significant growth since 2023, has slightly slowed down in 2024. Meanwhile, projects ranked 3rd to 10th remain highly competitive with narrow differences in rankings.

Flutter: Developed by Google, it enables both front-end and full-stack developers to build cross-platform user interfaces from a single codebase.

Next.js: An open-source framework created by Vercel, based on Node.js and Babel. Designed to complement React, it offers preview mode, fast compilation, and static export features.

#### AI

<center>图5.13 OpenRank of AI 2020-2024 </center>
<br>

<center>图5.14 Activity of AI 2020-2024 </center>
<br>

Since 2020, TensorFlow has been on a steady decline, eventually dropping out of the OpenRank Top 10 by 2024. Meanwhile, PyTorch has been steadily growing, further widening the gap with other projects. It is worth mentioning that LangChain has been ranked in the top three in terms of both indicators since it was open sourced in 2022. Although its popularity has slightly declined in 2024, its influence is still significant. At the same time, vllm has grown significantly, surpassing LangChain to rank second, while the Huggingface/Transformers project has maintained a steady growth in both indicators.

LangChain is an open source project launched by Harrison Chase in October 2022 and has become one of the most popular frameworks in LLM development.

vllm-project/vllm is an efficient and scalable distributed reasoning framework designed for efficient reasoning optimization of large-scale language models (LLMs). It has seen a significant increase in activity in the past three years and is deeply loved by developers.

### 5.3 OpenRank of Top 10 Projects in Each Sub-category

Below is the 2024 OpenRank leaderboard for projects across various categories.
<center>Figure 5.15 OpenRank TOP 10 Projects of Big Data</center>
<br>

<center>Figure 5.16 OpenRank TOP 10 Projects of Database</center>
<br>

<center>Figure 5.17 OpenRank TOP 10 Projects of Operating System </center>
<br>

<center>Figure 5.18 OpenRank TOP 10 Projects of Cloud Native </center>
<br>

<center>Figure 5.19 OpenRank TOP 10 Projects of Frontend </center>
<br>

<center>Figure 5.20 OpenRank TOP 10 Projects of AI </center>
<br>

## 6. Open Source Project Insights

In 2024, open source projects are gradually showing a smooth evolution after the rapid development of AI large models and generative AI, as well as a new vigour after the steady development in the database field. This chapter analyses in-depth multi-dimensional data of the projects from the perspective of open source projects to gain a more comprehensive insight. Statistical analysis of the Topics of open source projects reveals the common points of interest of the global open source community in 2024.

### 6.1 Project Category

This section selects the top 10,000 active GitHub repositories for analysis.

#### 6.1.1 Proportion of Project Categories

<center>
Figure 6.1 Proportion of Project Categories</center>
<br>

**Application Software**: Represented in blue, accounting for 24.3% of the pie chart. This indicates that application software holds a significant proportion in the analyzed dataset, reflecting its importance in the software ecosystem.

**Libraries and Frameworks**: Represented in orange, making up the largest proportion at 31.4%. This highlights the widespread use of libraries and frameworks in software development, as they provide the infrastructure and tools for building applications.

**Non-Software**: Represented in green, accounting for 23.2%. This category may include projects not directly related to software development, such as documentation, design resources, or other non-code assets.

**Software Tools**: Represented in red, making up 18.9%. These tools may include compilers, debuggers, version control systems, etc., which are essential auxiliary tools in the software development process.

**System Software**: Represented in purple, accounting for the smallest proportion at only 2.3%. This may include operating systems, drivers, etc., which form the foundation of computer system operations but have a relatively small share in this dataset.

#### 6.1.2 Proportion of OpenRank Totals by Project Categories

<center>
Figure 6.2 Proportion of OpenRank Totals by Project Categories in 2024
</center>
<br>

From the influence perspective of OpenRank in 2024, the distribution of these categories shows some notable trends:
- The most significant change is that Non-Software projects, despite having a high proportion in terms of active project count, have relatively low influence in 2024.
- System Software projects, although accounting for a small percentage of active projects, have a relatively higher influence in 2024. A similar trend is observed for Software Tools projects.
- Libraries and Frameworks and Application Software categories remain relatively unchanged, both continuing to represent a significant proportion.

#### 6.1.3 Trends in OpenRank Changes for Different Project Types Over the Past 5 Years

<!--  -->

<center>
Figure 6.3 Trends in OpenRank Changes for Different Project Types Over the Past 5 Years
</center>
<br>

From the five-year OpenRank changes above, it is evident that the influence of System Software has been increasing year by year. The influence of Software Tools has slightly declined this year. Libraries and Frameworks and Application Software show an overall downward trend, while the influence proportion of Non Software projects has been decreasing year by year.

### 6.2 Project Topic Analysis

This section also selects the top 10,000 repositories ranked by GitHub OpenRank for analysis and explores the Topic tags within these repositories for deeper insights.

#### 6.2.1 Popular Topics

<!--  -->

<center>
Figure 6.4 Top 10 Most Frequently Occurring Topics
</center>
<br>

The top 10 topics cover multiple domains, reflecting the diverse interests of the open-source community. Among them, hacktoberfest — a GitHub open-source event that encourages developers to contribute code — leads significantly with 1,132 occurrences, showcasing the welcoming nature of many projects toward contributors. Topics such as Python, JavaScript, TypeScript, Java, and Rust highlight the popularity of these programming languages in open-source software development. Additionally, Kubernetes and machine-learning are among the highly recognized topics, indicating strong community interest in these areas.

#### 6.2.2 The Total OpenRank Trend of Popular Topics' Repositories

<center>
Figure 6.5 OpenRank Changes of Repositories Under the Top 10 Most Frequent Occurring Topics (2019 - 2023)
</center>
<br>

- From 2020 to 2024, Hacktoberfest's OpenRank has shown significant growth. The goal of Hacktoberfest is to encourage more people to participate in open-source projects, reflecting the enthusiasm for open-source initiatives, community engagement, and contributions.
- Python and React have steadily risen, indicating their continued popularity. JavaScript and TypeScript have shown stable growth, highlighting the ongoing demand for front-end and application development.
- The growth of Kubernetes and Machine Learning reflects advancements in the fields of cloud computing and artificial intelligence.
- Other technologies, such as Java, Rust, and Android, have experienced moderate growth, indicating stability in mature technology markets.

### 6.3 Database Project Analysis

https://hackmd.io/@2024COSR/r13AvTwq1g/edit

### 6.4 Project Analysis in the Field of Generative AI

After another year of industry development, generative AI has demonstrated new patterns of growth. Overall, the year 2024 has seen a slowdown in the development of the Generative AI (GenAI) field across the board. This is likely due to the fact that advancements in generative AI, particularly in the domain of large models, require massive investments in funding and computational resources. Following the incremental competition of 2022-2023, the AI industry in 2024 has shifted to competing in a saturated market. With the foundational frameworks of various AI products now largely complete, the focus of development has gradually transitioned from expansion to refining and evolving product forms. Additionally, as leading projects mature and find practical applications, we anticipate that the development of generative AI in 2025 will enter a new phase of equilibrium.

#### 6.4.1 Growth Trends of GenAI Categories in the Past Five Years

<center>Figure 6.23 OpenRank of GenAI Category 2020 - 2024</center>
<br>

<center>Figure 6.24 Activity of GenAI Category 2020 - 2024</center>
<br>

+ Across different category classifications, the activity and influence of various generative AI projects have declined to some extent.
+ The influence and activity level of GenAI tool-based open-source projects are significantly higher than those of model-based and application-based projects.
+ The influence of model projects grew rapidly starting in 2022, surpassing infrastructure projects in 2023, marking a breakthrough year for GenAI innovation and application development. However, growth slowed in 2024, possibly indicating that the development of generative AI has stabilized in recent times.

#### 6.4.2 Generative AI Projects: OpenRank and Top 10 Activity Trends

<center>Figure 6.25 OpenRank Changes of GenAI Top 10 Projects in the Past 5 Years</center>
<br>

<center>Figure 6.26 Activity Changes of GenAI Top 10 Projects in the Past 5 Years</center>
<br>

- vLLM ranks first in both influence and activity, drawing significant attention from developers.

- langChain has seen a decline in both influence and activity rankings in the new year but still maintains a relatively high position.

- transformers, as the foundation of modern AI since their inception, continue to enjoy high attention in the latest year. Despite challenges from newer architectures like mamba, transformers remain at the core of large-model AI.

- stable-diffusion-webui showed strong growth momentum in 2023 and was once considered a major challenger to transformers. However, its various metric indicators have declined in 2024, yet it still has not shaken transformers' dominance.

- Langchain-Chatchat, as a locally deployed knowledge repository, has maintained a steadily ascending developmental trajectory into the year 2024.

#### 6.4.3 2024 Top 10 Generative AI Projects by OpenRank and Activity

<center>
Table 6.3 OpenRank Ranking of GenAI Projects
</center>
<br>

| Rank | Project | OpenRank |
| ---- | --------------------------------- | -------- |
| 1 | vllm-project/vllm | 4611 |
| 2 | huggingface/transformers | 4212.26 |
| 3 | langchain-ai/langchain | 4292.13 |
| 4 | ggerganov/llama.cpp | 3110.07 |
| 5 | run-llama/llama_index | 2665.89 |
| 6 | milvus-io/milvus | 1955.52 |
| 7 | facebookincubator/velox | 1641.14 |
| 8 | chatchat-space/Langchain-Chatchat | 1097.79 |
| 9 | microsoft/DeepSpeed | 983.42 |
| 10 | invoke-ai/InvokeAI | 971.2 |

<center>
Table 6.4 Activity Ranking of GenAI Projects
</center>
<br>

| Rank | Project | OpenRank |
| ---- | ------------------------------------ | -------- |
| 1 | vllm-project/vllm | 17556.02 |
| 2 | langchain-ai/langchain | 16413.39 |
| 3 | huggingface/transformers | 14454.74 |
| 4 | ggerganov/llama.cpp | 10599.61 |
| 5 | run-llama/llama_index | 10272.5 |
| 6 | milvus-io/milvus | 6978.76 |
| 7 | facebookincubator/velox | 4832.71 |
| 8 | chatchat-space/Langchain-Chatchat | 4315.73 |
| 9 | AUTOMATIC1111/stable-diffusion-webui | 3782.55 |
| 10 | getcursor/cursor | 3579.97 |

<br>

## 7. Developer Insights

Developers are the core driving force behind the continuous growth of the open-source ecosystem. They are not only the creators and promoters of technological innovation but also serve as a crucial foundation for the collaborative mechanisms within open-source communities. The overall number of developers, their level of contribution activity, and their modes of collaboration have a profound impact on the prosperity and development of open-source projects. This section takes a global perspective, conducting an in-depth analysis of individual developer data and comparing trends across different countries and regions to reveal the distribution patterns and evolving dynamics of open-source developers worldwide.

### 7.1 Developers' Geographical Distribution

The 2024 analysis continues the research methodology of previous studies while incorporating richer and more refined data sources. This study covers a sample of 12 million active developers on GitHub, among whom approximately 2.55 million have accurately provided their geographic location information, accounting for 2% of GitHub’s total registered user base of around 120 million. Although this sample represents only a subset of all registered users, improvements in data quality and the expansion of the sample size provide a more representative and reliable perspective for analyzing the global distribution of developers and regional collaboration patterns.

#### 7.1.1 Geographic Distribution of Active GitHub Developers

From a global perspective, the distribution of active GitHub developers has distinct regional characteristics, as shown in the figure below.

<img width="1195" alt="image" src="https://github.com/user-attachments/assets/668c90c4-f668-4430-bc1b-a7474eebd99d" />
<center>Figure 7.1 2024 Global Developer Distribution Map</center>
<br>

Globally, developers are primarily concentrated in densely populated areas with well-developed internet infrastructure, such as:

* Coastal city clusters in China
* Tech hubs on the East and West coasts of the United * States
* Major economic centers in Europe
* High-tech industry clusters in India
* Metropolitan areas in southeastern Brazil

These regions boast a large pool of technical talent and a well-established tech industry ecosystem, providing strong support for open-source development activities. In contrast, in sparsely populated areas or regions with underdeveloped internet infrastructure—such as deserts, mountainous areas, and polar regions—developers are relatively scarce or even nonexistent. This pattern not only reflects the current global distribution of technological resources but also highlights the imbalance in digital economic development.

Notably, certain regions in emerging economies—such as parts of Southeast Asia and Africa—have seen a growing number of active developers in recent years. With the increasing global internet penetration and the expansion of technology education, open-source development activities are gradually extending beyond traditional tech hubs into emerging markets, injecting new vitality and diversity into the global open-source ecosystem.

<img width="1189" alt="image" src="https://github.com/user-attachments/assets/f28d26f5-07f0-47a6-a571-b18b6252d241" />
<center>Figure 7.2 2024 China Developer Distribution Map</center>
<br>

#### 7.1.2 Active GitHub Developers by Country/Region

<img width="795" alt="image" src="https://github.com/user-attachments/assets/bb313a67-eaf5-4fb4-a6ab-580267f0d2a8" />
<center>Figure 7.3 Global Active GitHub Developer Country/Region Distribution 2024</center>
<br>

**<center>Table 7.1 Global Ranking of Active Developers by Country/Region 2024</center>**

| Rank | Country/Region | 2024 Count | 2023 Count | Growth Count | Growth Rate (%) |
|------|----------------|------------|------------|-----------|------------|
| 1 | United States | 22,233,197 | 18,326,730 | 3,906,467 | 21.32 |
| 2 | European Union | 17,281,528 | 14,086,752 | 3,194,776 | 22.68 |
| 3 | India | 15,209,709 | 11,443,487 | 3,766,222 | 32.91 |
| 4 | China | 9,404,966 | 8,863,326 | 541,640 | 6.11 |
| 5 | Brazil | 4,812,874 | 3,736,602 | 1,076,272 | 28.80 |
| 6 | United Kingdom | 3,796,457 | 3,110,915 | 685,542 | 22.04 |
| 7 | Russia | 3,404,378 | 2,790,032 | 614,346 | 22.02 |
| 8 | Indonesia | 3,321,239 | 2,518,881 | 802,358 | 31.85 |
| 9 | Germany | 3,316,461 | 2,676,735 | 639,726 | 23.90 |
| 10 | Japan | 3,221,378 | 2,471,377 | 750,001 | 30.35 |

From the data, it is evident that the number of active GitHub developers in major countries worldwide has significantly increased in 2024 compared to 2023. This indicates a further rise in global open-source ecosystem activity. Possible driving factors include increased internet penetration, the promotion of technical education, and the growing willingness of both enterprises and individuals to participate in open-source projects. Below is a detailed analysis of each country's performance and key highlights:

1. **Country with the Largest Number of Developers Worldwide: United States**
The United States ranks first globally with **22,233,197 developers**, experiencing a growth of **3,906,467**, representing a growth rate of **21.32%**. As a global leader in technology, the U.S. continues to solidify its central role in the global open-source ecosystem, supported by robust technological infrastructure and a mature open-source culture.

2. **Fastest-Growing Country: India**
India's developer count reached **15,209,709** in 2024, with an increase of **3,766,222**, marking a growth rate of **32.91%**, making it the fastest-growing country in terms of developer population globally. India's rapid rise is attributed to significant improvements in internet penetration, a vast pool of technical talent, and strong support from both the government and private sector for technology education.

3. **Major Country with the Lowest Growth Rate: China**
China ranks fourth with **9,404,966 developers**, but its growth rate is only **6.11%**, the lowest among all major countries, with an increase of **541,640 developers**. Despite maintaining a leading position in total developer numbers, the slowdown in growth is linked to the rise of domestic open-source hosting platforms and the localization trend within the open-source ecosystem.

4. **Standout Region: European Union**
The European Union (EU) ranks second with **17,281,528 developers**, adding **3,194,776 new developers**, representing a growth rate of **22.68%**. As a cluster of multiple developed economies, Europe has long maintained a leading position in open-source technology and collaboration, and its growth in developers continues to reflect the region's strong technological innovation capabilities.

5. **Rapid Growth in Emerging Markets: Brazil and Indonesia**
- **Brazil** ranks fifth with **4,812,874 developers**, a growth rate of **28.80%**, and an increase of **1,076,272 developers**. Brazil's high growth rate highlights the strong potential of Latin American countries in the open-source field.
- **Indonesia** has a relatively small total number, but its growth rate is as high as **31.85%**, with an increase of **802,358 developers**, indicating the rapidly growing participation and influence of Southeast Asian countries in the open-source ecosystem.

6. **Notable Performers: Japan and Germany**
- **Japan** ranks tenth with **3,221,378 developers**, a growth rate of **30.35%**, demonstrating its strong technical culture and continued support for open-source projects.
- **Germany** ranks ninth with **3,316,461 developers**, a growth rate of **23.90%**, further solidifying its leading position in Europe's technology sector.

<img width="743" alt="image" src="https://github.com/user-attachments/assets/dc407c46-92ad-4209-b64d-851f66869b0e" />
<center>Figure 7.4 Regional Distribution of Active GitHub Developers in China 2024</center>
<br>

**<center>Table 7.2 Active Developers by Region in China 2024</center>**

| Rank | Region | 2024 Count | 2023 Count | Growth Count | Growth Rate (%) |
|------|------|---------|---------|---------|----------|
| 1 | Beijing | 38,323 | 24,151 | 14,172 | 58.69 |
| 2 | Shanghai | 28,393 | 18,215 | 10,178 | 55.86 |
| 3 | Guangdong | 24,959 | 16,153 | 8,806 | 54.51 |
| 4 | Taiwan | 15,894 | 8,823 | 7,071 | 80.15 |
| 5 | Zhejiang | 15,816 | 10,927 | 4,889 | 44.74 |
| 6 | Jiangsu | 9,369 | 5,437 | 3,932 | 72.34 |
| 7 | Sichuan | 8,186 | 5,311 | 2,875 | 54.14 |
| 8 | Hongkong | 6,625 | 3,344 | 3,281 | 98.10 |
| 9 | Hubei | 5,732 | 3,273 | 2,459 | 75.13 |
| 10 | Shaanxi | 3,669 | 1,993 | 1,676 | 84.11 |

This table shows the changes in the number of active developers on GitHub in various regions of China between 2023 and 2024, including the total number of developers, the number of increases, and the growth rate. These data reveal the participation of different regions in China in the open source ecosystem and their development speed. The following are the main highlights and trend analysis:

**1. Key Region Analysis**
- **Beijing, Shanghai, and Guangdong** firmly occupy the top three positions, with **38,323**, **28,393**, and **24,959** developers, respectively. As China's core technology and economic hubs, these regions have attracted a large number of technical talents, making them major contributors to the open-source ecosystem.
- **Taiwan** and **Zhejiang** rank fourth and fifth, with **15,894** and **15,816** developers, respectively, highlighting their significant roles in cross-strait technological development.

**2. Highlights in Growth and Growth Rate**

- **Highest Absolute Growth: Beijing**
Beijing added **14,172 developers**, with a growth rate of **58.69%**, maintaining its top position nationwide. This indicates that Beijing, as China's center for technological innovation, continues to rapidly expand its technical talent pool, solidifying its leading role in the open-source ecosystem.

- **Highest Growth Rate: Hong Kong**
Hong Kong's growth rate reached an astonishing **98.10%**, nearly doubling, with an increase of **3,281 developers**. This suggests that Hong Kong's open-source development ecosystem is rapidly emerging, likely due to its enhanced position and resource investment in international technology strategies.

- **Outstanding Performers**
- **Jiangsu**: Added **3,932 developers**, with a growth rate of **72.34%**, showcasing the technological development potential of the Yangtze River Delta region.
- **Hubei**: Added **2,459 developers**, with a growth rate of **75.13%**, demonstrating the rapid rise of technological capabilities in central China.
- **Shaanxi**: Added **1,676 developers**, with a growth rate of **84.11%**, indicating that the western region's technology ecosystem is quickly catching up with national development trends.

**3. Regional Development Trends**

- **North China, East China, and South China: Dominance in Developer Numbers**
Beijing, Shanghai, Guangdong, Zhejiang, and other regions are the most economically developed areas in China and home to the most mature internet industries. These regions provide superior resources and environmental support for open-source development, resulting in significantly higher developer numbers.

- **Central and Western Regions: Impressive Growth Rates**
Although the total number of developers in central and western regions like Hubei and Shaanxi is relatively small, their growth rates exceed **75%**, showcasing the rapid rise of technological capabilities in these areas. This trend indicates that China's open-source ecosystem is gradually extending from coastal regions to inland areas, achieving more balanced regional development.

Overall, the regional distribution of China's open-source ecosystem exhibits a dual characteristic of "stable growth in key regions and rapid rise in emerging regions." With the rapid expansion of technological capabilities in central and western regions and the emergence of international hubs like Hong Kong, China's open-source ecosystem is becoming more diversified and balanced in its regional development.
<br>

### 7.2 Developer Work Time Analysis

This section analyzes the working hours of developers on GitHub and Gitee. The time in this section is based on UTC, which is 8 hours behind the UTC+8 time zone. The data is normalized to the [1-10] range using the min-max scaling method by default. In the time zone charts, the larger the dot area, the higher the value it represents.

#### 7.2.1 Holistic Developer Working Hours Distribution

**1 - GitHub Holistic Developer Working Hours Distribution**

<img width="1003" alt="image" src="https://github.com/user-attachments/assets/a87be22b-c8f0-444b-ad13-1f92e20761e8" />
<center>Figure 7.5 GitHub Holistic Developer Working Hours Distribution</center>
<br>

By analyzing the distribution of working hours of holistic developers in GitHub, we can find that developers’ active hours are mainly concentrated between 6:00 and 21:00, and reach a significant peak at 12:00, which may be related to the triggering of scheduled tasks. In addition, the activity on Saturdays and Sundays is relatively low, indicating that developers’ working frequency on weekends has decreased.

**2 - Gitee Holistic Developer Working Hours Distribution**

<img width="1003" alt="image" src="https://github.com/user-attachments/assets/6bcd76ea-6205-4582-b54a-e76943080666" />
<center>Figure 7.6 Gitee Holistic Developer Working Hours Distribution</center>
<br>

The data clearly indicates that the active hours of developers on the Gitee platform align more closely with the daily routine of the UTC+8 time zone. This characteristic is closely related to the user demographic of Gitee as a domestic code hosting platform in China. Since the majority of Gitee's users are concentrated in China and East Asia, the distribution of developers' active hours reflects the typical work and lifestyle rhythms of this region.

Specifically, the peak working hours for developers generally occur between 9:00 AM and 8:00 PM, which largely coincides with the standard working hours in the UTC+8 time zone. Additionally, there is a slight dip in activity during lunch and dinner times, further indicating that developers' work habits are consistent with the daily routines in East Asia. Moreover, compared to global platforms like GitHub, the decline in developer activity on weekends is more pronounced on Gitee, which may reflect the cultural tendency of Chinese developers to rest or engage in non-work-related activities during weekends.

**3 - Holistic Developer Working Hours Distribution Excluding Bot Data**

<img width="1001" alt="image" src="https://github.com/user-attachments/assets/e371f8d0-a841-46d6-84f0-9c11dfb4daaa" />
<center>Figure 7.7 Holistic Developer Working Hours Distribution Excluding Bot Data</center>
<br>

After filtering out bot data, the distribution of developers' working hours shows a more realistic and natural pattern. The data shows that developers are active mainly between 6pm and 21pm, a time zone where activity is significantly higher and more evenly distributed. This suggests that developers' work habits and actual activity trajectories are more clearly reflected after the interference of automated behaviours is excluded.

This distributional feature is highly consistent with the daily routine of human developers, which usually corresponds to the morning to evening work period. This pattern suggests that the vast majority of developers tend to code, collaborate, and contribute to open source projects during the main working hours of the day, while their activity decreases significantly during the late night and early morning hours. In addition, the even distribution of working hours may indicate that developers process tasks at a smoother pace, avoiding bursts of behaviour that are overly focused on particular points in time.

#### 7.2.2 Project Working Hours Distribution

**1 - Working Hours Distribution for OpenRank Top 4 Global GitHub Repositories**

* [NixOS/nixpkgs](https://github.com/NixOS/nixpkgs)

<img width="1004" alt="image" src="https://github.com/user-attachments/assets/0d99a62a-c89c-49f5-98bc-73cd1d35c872" />

<center>Figure 7.8 NixOS/nixpkgs Commit Activity Graph 2024</center>
<br>

* [llvm/llvm-project](https://github.com/llvm/llvm-project)

<img width="1005" alt="image" src="https://github.com/user-attachments/assets/c303f4b5-6841-4e0e-b22f-cc96859da22e" />

<center>Figure 7.9 llvm/llvm-project Commit Activity Graph 2024</center>
<br>

* [home-assistant/core](https://github.com/home-assistant/core)

<img width="1003" alt="image" src="https://github.com/user-attachments/assets/6eb34367-dffe-4e65-8692-4a68acd8a792" />

<center>Figure 7.10 home-assistant/core Commit Activity Graph 2024</center>
<br>

* [pytorch/pytorch](https://github.com/pytorch/pytorch)

<img width="1004" alt="image" src="https://github.com/user-attachments/assets/27d72c73-6256-4b93-a0b2-fcc1c3cb233f" />
<center>Figure 7.11 pytorch/pytorch Commit Activity Graph 2024</center>
<br>

**2 - Working Hours Distribution for OpenRank Top 4 Chinese GitHub Repositories**

* **openharmony**

<img width="1003" alt="image" src="https://github.com/user-attachments/assets/a52ef9e3-6fbb-4a8e-a19c-402c9e0f00e9" />
<center>Figure 7.12 openharmony Commit Activity Graph 2024</center>
<br>

* **DaoCloud**

<img width="1002" alt="image" src="https://github.com/user-attachments/assets/e98237a7-5e42-4f46-8217-8db6fcde95b4" />
<center>Figure 7.13 DaoCloud Commit Activity Graph 2024</center>
<br>

* **PaddlePaddle**

<img width="1004" alt="image" src="https://github.com/user-attachments/assets/ddc2dab7-afba-4ead-b785-951beafe7105" />
<center>Figure 7.14 PaddlePaddle Commit Activity Graph 2024</center>
<br>

* **Doris**

<img width="1004" alt="image" src="https://github.com/user-attachments/assets/1c333de4-198a-4411-bed1-458c72763852" />
<center>Figure 7.15 doris Commit Activity Graph 2024</center>
<br>

### 7.3 Developer Persona Analysis

This section categorizes GitHub users into four roles based on the events they trigger in open-source repositories: **Explorers**, **Participants**, **Contributors**, and **Committers**. The definitions of these roles are as follows:

**<center>Table 7.3 Four Developer Roles</center>**

| Role | Definition | Description |
|---------------|----------------------------------------------------------------------------|-------------------------------------------------------------------------|
| **Explorer** | Users who have starred a project. | The user has some interest in the project. |
| **Participant** | Users who have created Issues or left Comments in a project. | The user is actively engaging with the project. |
| **Contributor** | Users who have submitted Pull Requests (PRs) in a project. | The user has contributed to the project's CodeBase. |
| **Committer** | Users who have participated in PR reviews or merged PRs. | The user has made deep contributions to the project. |

In general, these four roles form a progressive hierarchy, as illustrated in the diagram below. Based on this role framework, we quantify the top 10 projects by OpenRank across GitHub from three perspectives: role distribution, temporal changes, and developer role evolution, which corresponds to the ranking list in the second section.


<center>Figure 7.16 Developer Role Relationship</center>
<br>

#### 7.3.1 Distribution of the Number of Roles 2024

| Repository | Explorer | Participant | Contributor | Committer |
|-------------------------------------|-------|---------|------|------|
| NixOS/nixpkgs | 4897 | 3606 | 4339 | 3484 |
| llvm/llvm-project | 6789 | 3241 | 2365 | 2092 |
| home-assistant/core | 10596 | 7472 | 1300 | 989 |
| pytorch/pytorch | 12513 | 2599 | 1424 | 823 |
| digitalinnovationone/dio-lab-open-source | 3813 | 4462 | 21276| 224 |
| odoo/odoo | 7659 | 650 | 1035 | 661 |
| microsoft/vscode | 14701 | 12522 | 579 | 388 |
| zephyrproject-rtos/zephyr | 2314 | 1054 | 1276 | 1120 |
| godotengine/godot | 15208 | 3314 | 1072 | 678 |
| elastic/kibana | 1298 | 852 | 437 | 452|
<center>Table 7.4 Distribution of the Number of Developer Roles in the Top 10 Projects in OpenRank</center>
<br>


<center>Figure 7.17 Developer Role Distribution</center>
<br>

The results show that:
- dio-lab-open-source: With the most contributors (21,276), this project is a tutorial course designed for contributing to GitHub projects, which explains the large number of contributors.

- microsoft/vscode has the largest number of explorers (14,701) and participants (12,522), but the number of contributors (579) and committers (388) is relatively small. This shows that the project has a very high level of attention and participation, but the core contributions are still completed by a smaller number of developers, indicating that its development threshold is high or the management is relatively centralized.

- home-assistant/core and godotengine/godot have a large number of explorers (10,596 and 15,208), and a certain scale of participants, but the ratio of contributors to committers is lower (1,300 and 1,072 contributors, 989 and 678 committers, respectively). This distribution suggests that they have some community involvement, but the actual development work is still undertaken by a small number of developers.

### 7.3.2 New Additions by Role in 2024

The new statistical criterion for roles is as follows: If a user was not in role X (e.g., contributor or submitter) before 2024 and became that role in 2024, they are counted as an effective addition to the X role.

For example, A submitted a PR to project B in 2021, but never participated in code review. In 2023, A reviewed a PR in project B, so A is called a new committer.

The detailed role additions are shown in the figure and table below.

| Repository | New Explorer | New Participant | New Contributor | New Committer |
|---------------------------------------|---------|--------|-------|-------|
| NixOS/nixpkgs | 4836 | 2392 | 2187 | 1605 |
| llvm/llvm-project | 6689 | 2191 | 1517 | 1223 |
| home-assistant/core | 10483 | 5502 | 819 | 565 |
| pytorch/pytorch | 12321 | 1938 | 946 | 496 |
| digitalinnovationone/dio-lab-open-source | 3809 | 4455 | 21254 | 224 |
| odoo/odoo | 7559 | 445 | 467 | 239 |
| microsoft/vscode | 14416 | 10614 | 450 | 312 |
| zephyrproject-rtos/zephyr | 2278 | 687 | 690 | 554 |
| godotengine/godot | 14774 | 2216 | 738 | 445 |
|elastic/kibana | 1280 | 472 |155 | 117|

<center>Table 7.5 Distribution of Developer Role Additions in the Top 10 OpenRank Projects</center>
<br>


<center>Figure 7.18 Role Additions in the Open Source Community 2024</center>
<br>

**1. New Explorers**
- microsoft/vscode follows closely, with the number of new explorers reaching 14,416. This reflects its ongoing appeal as one of the most popular code editors globally.

**2. New Participants**
- microsoft/vscode ranked first with 10,614 new participants, demonstrating that its participation and popularity in the open source community continues to remain strong.

**3. New Contributors**
- digitalinnovationone/dio-lab-open-source has 21,254 new contributors, far ahead of other projects. This shows that the project is very attractive to developers at the contribution level, which may be due to its friendly entry threshold for beginners and the support of a large number of teaching resources.
- NixOS/nixpkgs ranks second with 2,187 new contributors, indicating that its community activity and openness are still high.

**4. New Committers**
- NixOS/nixpkgs is the project with the highest number of new committers in 2024, reaching 1,605, indicating that its core maintenance team has further expanded. This shows that its community not only attracts a large number of contributors, but also converts into efficient commit behavior.
- llvm/llvm-project ranks second with 1,223 new committers, reflecting its strong core development capabilities and community activity.

#### 7.3.3 Developer Evolution Perspective

The evolution process of developers is defined as: how many roles in an open source community transition to other roles. In this report, only developers transitioning from one role to a more advanced role were measured. For example, if a user was a participant before 2023 and submitted their first PR in 2023, they transitioned from a participant to a contributor.

| Repository | Contributor -> Committer | Participant -> Contributor | Explorer -> Participant |
|---------------------------------------|-------|------|-------|
| NixOS/nixpkgs | 287 | 188 | 204 |
| llvm/llvm-project | 134 | 289 | 185 |
| home-assistant/core | 66 | 103 | 155 |
| pytorch/pytorch | 82 | 78 | 168 |
| digitalinnovationone/dio-lab-open-source | 0 | 21 | 3 |
| odoo/odoo | 48 | 33 | 28 |
| microsoft/vscode | 23 | 50 | 272 |
| zephyrproject-rtos/zephyr | 62 | 45 | 46 |
| godotengine/godot | 67 | 115 | 242 |
| elastic/kibana | 12 | 26 | 3 |

<center>Table 7.6 Distribution of Developer Role Evolution in the Top 10 OpenRank Projects</center>
<br>


<center>Figure 7.19 Developer Role Evolution Diagram</center>
<br>

- From the data in the tables and charts, we can observe the evolution trends of developer roles across communities in 2024. It continues to reflect a typical funnel model, where developers transition from explorers to participants, from participants to contributors, and eventually to core committers. This trend aligns with the natural progression of open-source community members from initial exploration to deep engagement.
- In various communities, we can still observe the typical funnel model, the evolution path from explorers to participants, and then to contributors and committers. Taking godotengine/godot as an example, in 2024, 242 explorers successfully transformed into participants, 115 participants transformed into contributors, and 67 contributors evolved into committers. This trend is also reflected in other communities, showing the natural development process of members from initial participation to deep contribution.
- In the NixOS/nixpkgs community, we observed a high number of conversions from contributors to committers, reaching 287, which further shows its openness to core contributions and high code review requirements, which helps to improve code quality and project stability.
- In addition, for projects like microsoft/vscode and godotengine/godot, the transformation from explorers to participants is quite significant, with 272 and 242 explorers completing the role transformation respectively. This shows that these communities are more attractive to new developers and provide a relatively low threshold for participation.
- In contrast, the role transformation of digitalinnovationone/dio-lab-open-source is still relatively small, especially the former has less evolution data, indicating that the community is still in the early stages of development. Similarly, elastic/kibana also has less evolution data, but this project is a mature project. It can be seen that when the project is developed and improved, its developers will also tend to be stable.

### 7.4 Bot Account Perspectives
Bot accounts are accounts that have been manually labeled and recognized for their contributions to the community. Currently, there are 1,410 bot accounts, with 181 additions compared to last year. Among these, 965 bot accounts were active in 2024, with **930 on the GitHub platform** and 35 on the Gitee platform. We analyzed all events in the repositories where these bots participated to study the changes in bot-related activities. By comparing the events generated by bot accounts with all events, we can assess the significance of bot accounts. Through comparative charts of different event types and their change rates, we can understand the reasons behind the changes in the number of bot-related events in 2024. Finally, by examining the 7x24-hour activity heatmap of bot accounts, we can gain insights into the working hours of these bots.

#### 7.4.1 Bot Account Event Changes
<center>Figure 7-8 Annual Comparison Chart of Events Generated by Bot Accounts vs. Total Events in Repositories</center>
<br>

From Figure 7-8, it can be observed that the number of events generated by bot accounts has significantly increased over the past few years. Particularly, starting from 2020, the number of bot-related events has shown a rapid upward trend. In contrast, the number of events involving human developers, while also increasing, has grown at a relatively slower pace, with a more stable trend over time.

To elaborate further, between 2016 and 2024, the number of events generated by bot accounts grew from nearly zero to over 400 million, while the total number of events increased from approximately 100 million to over 700 million. The growth rate of bot-related events has significantly outpaced that of overall events, indicating that the role and influence of bot accounts in the community are continuously strengthening.

This growth is likely driven by the increasing adoption of bots in automating tasks, code reviews, continuous integration, and other areas, thereby reducing the workload on human developers and improving overall efficiency. Although the level of human developer participation has remained relatively stable, the rapid growth of bot accounts has compensated for this, ensuring a consistent rise in the total number of events.

In 2024, bot-related events accounted for 43% of all events, while events involving human developers made up 57%. This proportion further underscores the importance of bot accounts in the community. Not only has the number of bot-related events grown significantly, but their share of overall events has also increased, highlighting the increasingly critical role bots play in the community.

#### 7.4.2 Analysis of Bot Account Event Changes

<center>Figure 7-10: Annual Comparison of Event Types for Bot Accounts (2016-2024)</center>
<br>

From Figure 7-10, we can observe the distribution of different event types across the years. Since bot accounts do not participate in MemberEvent, WatchEvent, ForkEvent, PublicEvent, or GollumEvent, these events have been excluded. Below are some key observations:

- PushEvent and PullRequestEvent are the most dominant event types, with their numbers far exceeding other event types.
- PushEvent reached a new peak in 2024, with the number of events approaching 300 million.
- The number of PullRequestCommentEvent has been steadily increasing.
- However, PullRequestEvent has been gradually decreasing.

The significant increase in the activity of bot accounts in code submission indicates that developers are increasingly relying on automated tools to submit code. At the same time, the number of PullRequestEvent is gradually decreasing, probably because the optimization of automated tools and processes has reduced the need for manual pull requests. The number of PullRequestCommentEvent and IssueCommentEvent continues to rise, indicating that robot accounts are more involved in code review and issue management. In addition, the number of other event types (such as CreateEvent, DeleteEvent, etc.) has also increased, reflecting the diverse activities of bot accounts in project management and maintenance.

<center>Figure 7-11 Change Rate of Each Event in 2024 and 2023</center>
<br>

Figure 7-11 shows the change rate of each event type between 2024 and 2023:

- IssuesEvent has the highest growth rate, reaching 783.5%, an increase of 19,333,491 times. This shows that the robot's activity in handling issues has increased significantly.
- PullRequestReviewCommentEvent and PushEvent have growth rates of 60.1% and 56.1%, respectively, with an increase of 1,786,717 times and 105,177,443 times.
- GollumEvent and DeleteEvent also show growth, 49.0% and 24.3%, respectively.
- CommitCommentEvent and ForkEvent show significant decreases, decreasing by 90.2% and 72.3%, respectively.

These change rates indicate that bot accounts have become more active in certain types of events, especially in handling issues (IssuesEvent) and code submissions (PushEvent). At the same time, the decrease in certain event types (such as CommitCommentEvent and ForkEvent) may indicate that these tasks are more manually handled by developers or that there is less demand for automation of these tasks.

#### 7.4.3 Bot Account 7x24 Hour Activity Heatmap


From the 24-hour activity heatmap, we can observe distinct patterns in the distribution of bot account activities throughout the day. Below are some key observations:

- Peak Hours: Bot account activity reaches its peak at 12:00 PM (noon) each day. This suggests that most bot events are scheduled tasks, typically programmed to run at midday.
- All-Day Activity: Although noon is the peak activity period, bot accounts maintain a certain level of activity throughout the 24-hour cycle. This indicates that bots operate around the clock, handling various automated tasks.
- Weekdays vs. Weekends: The heatmap shows that activity levels are slightly higher on weekdays (Monday to Friday) compared to weekends (Saturday and Sunday). This is likely due to increased development activity on weekdays, triggering more bot events.

This activity pattern highlights the critical role bot accounts play in automating tasks, particularly in areas like scheduled tasks and continuous integration. By executing tasks at fixed times, bots effectively reduce the workload on developers and enhance overall productivity.

## 8. Commercial Open Source Insights

### 8.1 Definition of Commercial Open Source

Commercial open source refers to a model in which companies profit commercially by providing value-added services, technical support and customised solutions based on open source software. Commercial open source is about reducing software bugs and enriching software features through the participation of more people, while at the same time preventing a few people from leaving inappropriate backdoors in the software. Companies can directly gain economic benefits through the open source business model, and open source software will eventually feed back into the economy, allowing commercial companies to provide better products for users. The main difference between it and traditional open source is that traditional open source is primarily designed to promote the free use, modification and distribution of software, and tends to be community-driven to drive technological progress. But while commercial open source also follows the principles of open source, its main purpose is still to make a profit.

### 8.2 Analysis of Commercial Open Source Companies


<center>Figure 8-1 Commercial Open Source Companies - OpenRank Top 20 </center>
<br>

Grafana Labs, which has the Top 1 OpenRank thanks to the widespread adoption and community activity of its core product Grafana, closed a funding round in 2024 that valued the company at $6 billion.

HashiCorp holds a significant position in the open-source domain, but its funding amount is relatively low at $349.2 million. This may be due to the fact that HashiCorp's business model and monetization approach differ from those of other companies. It primarily commercializes by offering enterprise-level support, services, and commercial editions of its open-source tools.

### 8.3 Analysis of Commercial Open Source Projects


<center> Figure 8-2 Commercial Open Source Projects - OpenRank Top 20</center> <br>

Odoo, as the world's No. 1 free and open source PLM management system, has the highest OpenRank and a high funding amount, probably because Odoo has strong community support and activity, as well as a wide range of enterprise application modules, giving it a high degree of influence and market recognition among open source projects.

Despite its technical recognition, oven-sh/bun's funding amount is relatively low, probably because the project is still at an early stage, the business model is not fully mature, or the market is still waiting to assess its business potential. As the project matures and market recognition increases, Oven's funding is expected to increase and its influence in the open source community is likely to continue to grow.

### 8.4 OpenRank Trends of Commercial Open Source Projects in the Last 5 Years


<center>Figure 8-3 OpenRank Trends of Commercial Open Source Projects in the Last 5 Years</center>
<br>

OpenRank for commercial open source projects has been on an overall growth trend over the past five years, with a rapid increase from 2020 to 2023, thanks to the prosperity of the open source ecosystem and corporate support; and a slowdown from 2023 to 2024, likely due to market saturation, project maturity and increased competition.

### 8.5 OpenRank Trends for Commercial Open Source Companies over the Last 5 Years


<center>Figure 8-4 OpenRank Top5 Commercial Open Source Companies Trends in the Last 5 Years</center>
<br>

* HashiCorp's OpenRank grows steadily from 2020 to 2023, peaking and then dropping slightly in 2024.
* Grafana Labs grows significantly, gradually rising from a low ranking in 2020 to essentially tie HashiCorp in 2024.
* Vercel grows significantly, moving up from a mid-tier ranking in 2020, peaking in 2023 and then dropping back slightly.
* GitHub maintains steady growth, reflecting its importance as a core platform in the open source ecosystem.
* Armory's performance is more volatile, declining slightly from 2020 to 2021, but rebounding quickly in 2022, peaking in 2023 and then declining rapidly.
<br>

### 8.6 Case Studies

In this section，we take Hangzhou FIT2CLOUD Information Technology Co., Ltd. (hereinafter referred to as FIT2CLOUD) as an example to introduce an enterprise's open source commercialization practices. FIT2CLOUD's open source commercialization practice is to leverage open source to achieve efficient “**Product & Business**” co-innovation, make good software products and keep selling them. FIT2CLOUD's business model is a freemium model based on open source, and the establishment of this business model needs to solve two things at the same time: 1、Continuously expanding the number of free installations；2、Continuously improving the conversion rate of paid users.

<center>Figure 8-6: Open Source Freemium Model</center>
<br>

FIT2CLOUD's product philosophy is that "Good software is iterated." FIT2CLOUD leverages open source for efficient distribution, gets lots of feedback, and iteratively releases its products on a monthly basis. FIT2CLOUD's business philosophy is "Our products are bought, not sold." End-users are becoming key decision-makers in purchasing tool software products,and FIT2CLOUD enables online customer acquisition, sells standard products, and continues to increase cross-sell rates through a strong product portfolio. This cycle of "Open source attracts users - User feedback drives iteration - Iterated products attract more users - More users lead to more customers - More revenue leads to greater R&D investment" is the key to the true flywheel effect of the FIT2CLOUD business model.

<center> Figure 8-7: FIT2CLOUD's Open Source Commercialization Practices</center>
<br>

FIT2CLOUD's milestones in open source commercialisation can be verified by four figures:
1. **OpenRank Open Source Activity** ：FIT2CLOUD ranks 10th among Chinese enterprises and 47th globally in terms of OpenRank open source activity.
2. **OpenRank Open Source Influence**：FIT2CLOUD ranks 9th among Chinese enterprises and 42nd globally in terms of OpenRank open source influence.
3. **Number of paying enterprises**: By the end of 2024, FIT2CLOUD has served more than 3,000 enterprise customers in various industries such as finance, manufacturing, energy, transport, medical care, communications, media, real estate, Internet, education, and so on.
4. **Healthy Cash Flow** : In 2024, FIT2CLOUD recorded 2,511 cash transactions from open source commercialization products, with annual cumulative revenue exceeding CNY 100 million (≈$14.29 million USD).

## 9. Open Source Insights for Higher Education

The [Open Source Promotion Plan (OSPP) 2024](https://summer-ospp.ac.cn/), as a significant platform for deep interaction between universities and open source communities, has achieved remarkable results this year, effectively promoting the development of open-source technologies and the cultivation of talent in higher education. Since the inaugural OSPP, the X-lab Open Laboratory has been deeply involved. This year, we conducted the following data analysis on the relevant data for OSPP 2024.

### 9.1 OSPP Macro Analysis

- **Overview of OSPP 2024**: This year's OSPP brought together **168 open-source communities** from various fields, including but not limited to operating systems, programming languages, artificial intelligence, and more. As shown in Figure 9.1, **2,537 students** from universities worldwide launched **561 open-source projects**, with **455 outstanding projects** completed.


<center>Figure 9.1 Overview of Event Participation</center>
<br>

- **Number of Communities**: Since the inaugural OSPP, the number of communities participating in the event has shown remarkable growth each year. By 2024, the number of communities surged to **168**, representing a significant increase compared to 2023. This growth trend can be attributed to several factors. On the one hand, more developers and project teams have recognized the powerful potential of open-source collaboration, attracting more communities to join the OSPP initiative. On the other hand, universities have increasingly emphasized the importance of open-source education, strengthening their collaboration with open-source communities to provide students with practical platforms.
- **Number of Students and Universities**: From 2020 to 2023, the number of student participants steadily increased, thanks to the gradual penetration of open-source culture in universities and the growing influence of the OSPP initiative. However, in 2024, the number of student participants slightly decreased to 2,537. This decline may be attributed to the moderate adjustments in project difficulty and requirements this year, as well as the diversion of some potential participants due to competition from other similar open-source events. As for the number of participating universities, since the launch of the event, its trend has largely mirrored that of student participation. That is, it steadily increased from 2020 to 2023 but saw a slight decline in 2024, for reasons similar to those affecting the number of student participants.
- **Number of Projects**: In the 2024 OSPP event, the total number of participants slightly decreased, but the number of projects still reached 561. In terms of project completion, 455 projects were successfully concluded, with the completion rate jumping from 70% last year to 81%. This outstanding completion rate can be attributed to several factors. First, the organizers optimized the project management process. At the initial stage of the projects, they provided students and mentors with more detailed and targeted guidance manuals and training courses, covering everything from project planning to overcoming technical challenges. Second, community mentors played a more active and critical role this year. They not only provided students with professional technical guidance but also shared valuable insights on time management, team collaboration, and more. Lastly, students have shown increasing dedication and commitment to open-source projects, enabling them to efficiently complete project development tasks. This has significantly contributed to the notable improvement in the project completion rate.

### 9.2 OSPP Annual Student-College-Related Distribution Analysis

- **Geographical Distribution of Universities**: The geographical distribution of participating universities in the Summer of Open Source 2024 is shown in Figure 9.2, while a comparison with the 2023 distribution is provided in Figure 9.1. In 2023, a total of 592 universities participated, including 489 domestic universities and 103 foreign universities, with foreign universities accounting for 17.4% of the total. By 2024, the total number of participating universities had decreased to 498, with domestic universities dropping to 399 and foreign universities slightly decreasing to 99. However, the proportion of foreign universities increased to 19.9%. This change indicates that while the overall scale of university participation has shrunk, the relative proportion of international collaboration has grown. As the international influence of OSPP continues to expand, it has attracted more attention from foreign universities. Despite fluctuations in absolute numbers, the rising proportion reflects a deepening trend in international cooperation. This shift is significant for fostering global open-source technology exchanges and promoting the international integration of talent cultivation. It also suggests that in OSPP’s future development, international collaboration will become a key growth driver and a distinctive highlight.


<center>Figure 9.2 Distribution of Participating Universities in OSPP 2024</center>
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| OSPP Year | Total Universities | Domestic Universities | Foreign Universities | Percentage of Foreign Universities |
| --------- | -------- | ------------ | ------------ | ------------ |
| 2024 | 498 | 399 | 99 | 19.9% |
| 2023 | 592 | 489 | 103 | 17.4% |
<center>Table 9.1 Changes in the Distribution of Domestic and Foreign Universities in OSPP from 2023 to 2024</center>
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- **Educational Background Distribution of Students**: The educational background distribution of students participating in OSPP 2024 is shown in Figure 9.3, while a comparison with 2023 is provided in Table 9.2. It can be observed that, in addition to a large number of outstanding students from China, many students from various countries around the world also took part in the program. Among all participants, the majority were undergraduate and master's students, with a smaller proportion being doctoral students. Specifically, a comparison of the educational background distribution of OSPP students in 2023 and 2024 shows that the overall structure has remained relatively stable. The changes in distribution reflect that the dynamic development trend of the OSPP program among students of different academic levels remains steady, with its primary target audience still being undergraduate and master's students.


<center>Figure 9.3 Educational Background Distribution of Students Participating in OSPP 2024</center>
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| OSPP Year | Total Students | Undergraduate/Associate Percentage | Master Percentage | Doctor Percentage |
| --------- | -------- | ----------------- | ------------ | ------------ |
| 2024 | 2537 | 56% | 42% | 2% |
| 2023 | 3475 | 57% | 41% | 2% |

<center>Table 9.2 Changes in the Educational Background Distribution of Students in OSPP from 2023 to 2024</center>

### 9.3 Contribution Analysis of OSPP by Year

Based on the above statistical data, a detailed analysis of the contribution levels of participating universities and students involved in various communities over the past two years of OSPP has been conducted. This analysis integrates the annual contribution data and the community OpenRank algorithm to provide deeper insights.

### 9.3.1 University Contribution

The annual ranking of university contributions, calculated using the OpenRank algorithm, is shown in Figures 9.4 and 9.5. Figure 9.4 presents the top 20 universities with the most significant contributions in OSPP 2024, while Figure 9.5 displays the corresponding university rankings for OSPP 2023.

In the 2024 rankings, Xi'an University of Posts and Telecommunications topped the list with an OpenRank score of 85.13, involving 15 students, with an average OpenRank of 5.68 per student. Not only did its OpenRank score see a significant increase, but the number of participating students was also considerable, indicating a substantial overall contribution to OSPP. Longdong University ranked second with an OpenRank score of 61.37, but it had only one participating student, resulting in an exceptionally high per-student OpenRank of 61.37. This suggests that the student possessed unique technical expertise or innovation capabilities, allowing them to independently complete high-value project tasks. Similarly, Shanghai University secured third place with an OpenRank score of 42.21, with only two students participating in the program.

In the 2023 rankings, the top three universities were Huazhong University of Science and Technology, Zhejiang University, and Beijing University of Posts and Telecommunications. It can be observed that these universities had relatively high overall contributions to OSPP. Among them, although Huazhong University of Science and Technology did not have the highest number of participating students, its outstanding per-student OpenRank performance allowed it to achieve the highest total OpenRank score. On the other hand, universities like Fudan University, Longdong University, Wuhan University, and Chengdu University of Information Technology may not have had the largest number of students, but the high contributions of individual students helped these universities secure higher final rankings.

- **OSPP University Contribution Ranking 2024**:

<center>Figure 9.4 OSPP University Contribution Ranking 2024</center>
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- **OSPP University Contribution Ranking 2023**:

<center>Figure 9.5 OSPP University Contribution Ranking 2023</center>
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By comparing the university contribution rankings in 2023 and 2024, the changes in the rankings from multiple perspectives, such as ranking place and contribution, were also analyzed.

First, in terms of ranking changes, Xi'an University of Posts and Telecommunications and Longdong University have risen significantly. The former has risen from sixth place in 2023 to first place in 2024, making a huge leap. This ranking improvement reflects the school's rapid development and aggressiveness in open source project practice; while the latter has risen from twelfth place in 2023 to second place in 2024, and its ranking increase is also remarkable. Although only one student from the university participated in the project in 2024, the student made a very high contribution.

### 9.3.1 Student Contribution

This section will provide a detailed analysis of the student contribution ranking data for OSPP 2023 and 2024, along with the changes observed. From the perspective of participating communities, the open-source communities students engaged in were highly diverse. These communities included a range of types, such as Apache Hadoop, MatrixOne, Spring Cloud Alibaba, and more. This reflects the broad technical scope of the OSPP project, offering students opportunities to engage in open-source practice across different areas. The specific rankings are shown in Figures 9.6 and 9.7.

- **OSPP Student Contribution Rankings 2024**:

<center>Figure 9.6 OSPP Student Contribution Rankings 2024</center>
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- **OSPP Student Contribution Rankings 2023**:

<center>Figure 9.7 OSPP Student Contribution Rankings 2023</center>
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By comparing the student contribution rankings of 2024 and 2023, it can be observed that universities such as Longdong University, Shanghai University, and Xi'an University of Finance and Economics had students who ranked high in 2024. This indicates that in open-source projects, it is not only students from traditionally dominant universities who can achieve high contribution levels; students from relatively lesser-known universities, if they have sufficient skills and commitment, can also stand out in the rankings.

Regarding the communities participated in, this year's OSPP situation is similar to 2023, with students still engaging in a diverse range of communities. However, in some specific communities, such as Spring Cloud Alibaba and MindSpore, there has been a significant increase in student contributions. This could be related to the project demands and development directions of these communities in 2024, as well as growing student interest in related technologies. On the other hand, the concentration of contributions in this year's OSPP has changed. While there are still some students with OpenRank scores far above the average, the overall gap has narrowed compared to 2023. This could be due to the promotion and development of the OSPP project, where more students have acquired effective methods for participating in open-source projects, thereby improving their contributions. As a result, competition among high-contribution students has become more intense.