SlashData’s Developer Nation survey is the leading research programme on mobile, desktop, industrial IoT, consumer electronics, embedded, third-party app ecosystems, cloud, web, games, AR/VR and machine learning developers, as well as data scientists, tracking developers’ experiences across platforms, technologies, programming languages, app and API categories, revenue models, segments, and regions.

The 24th edition of the Developer Nation global survey ran from December 2022 to February 2023 and reached close to 26,000 developers from 166 countries. This research report delves into key developer trends for Q1 2023 and beyond. The report focuses on six major topics - each with its own visualisations - showing how the data lends insight into the developer community. 

1. Emerging technologies that capture developers’ imagination: With AI powering many of the most controversial and transformational emerging technologies, the rate of technological advancement is increasing, and developers are no safer than artists and authors from the effects. In this chapter, we explore how developers are involved with different emerging technologies, from Generative AI and AI-assisted software development to Wi-Fi Sensing.
2. How well-paid do developers feel?: Studying wages can offer insights into the supply and demand of various skill sets in an employment market. In this chapter, we explore the software developer compensation landscape. We look at the total annual compensation that developers report, both globally and across regions. We also examine whether developers consider their current compensation fair, and we discuss the factors that are associated with believing that they are under-or overpaid.
3. Language communities-An update: Programming languages are often the kernels of strong communities and the subject of opinionated debates. In this chapter, we provide updated estimates of the number of active software developers using each of the major programming languages, across the globe and across all kinds of programmers.
4. What makes up a high-quality API?: With third-party APIs, developers can leverage the power of external expertise to enhance the functionality of their applications. However, to ensure success, they must carefully evaluate the quality of APIs before incorporating them into their applications. The aim of this chapter is to investigate the key characteristics that make third-party APIs high-quality, according to developers.
5. On the role of female coders in software development: Since the beginning of computing, women have continually played a pivotal role in software development that has been frequently overlooked. Today, important efforts are being made across the software development ecosystem to address these historical biases. In this chapter, we look at how strong the representation of female coders is across various developer segments, and how this has evolved over time.
6. Embedded software development- An overview: Embedded software refers to computer programs that are designed to perform specific functions in systems or on hardware devices that are not traditionally considered personal computers. These necessary systems are found in all kinds of devices, from thermostats and security cameras to medical equipment and cars. In this final chapter, we offer insights into the markets that embedded developers target with their applications, as well as into the types of projects they work on. 

The 24th edition of the Developer Nation survey reached nearly 26,000 respondents from 166 countries around the world. As such, the Developer Nation series of surveys continues to be the most global independent research on mobile, desktop, industrial IoT, consumer electronics, embedded, third-party app ecosystems, cloud, web, game, augmented and virtual reality, and machine learning developers and data scientists combined, ever conducted. The report is based on a large-scale, online developer survey designed, produced, and carried out by SlashData over a period of ten weeks between December 2022 and February 2023.

Respondents to the online survey came from 166 countries, including major app and machine learning development hotspots such as the US, China, India, Israel, the UK, and Russia, even stretching all the way to Kenya, Brazil, and Jordan. The geographic reach of this survey is truly reflective of the global scale of the developer economy. The online survey was translated into eight languages in addition to English, namely simplified Chinese, traditional Chinese, Spanish, Portuguese, Vietnamese, Russian, Japanese, and Korean, and was promoted by more than 100 leading community and media partners within the software development industry.

Our respondents came from a broad age spectrum, from young coders and creators who are under 18 to the seasoned ones over 55. Respondents were asked which types of projects they are involved in out of the 13 under study, namely web apps / SaaS, mobile apps, desktop apps, backend services, augmented reality, virtual reality, games, data science, machine learning / artificial intelligence, industrial IoT, consumer electronics devices, embedded software, and apps/extensions for third-party app ecosystems. They also told us if they are into their areas of involvement as professionals, hobbyists, or students- or as any combination of these - and how many years of experience they have in each.

To eliminate the effect of regional sampling biases, we first weighted to correct for over-represented individual countries within regions. We then weighted the regional distribution across nine regions by a factor that was determined by the regional distribution and growth trends identified in our Developer Nation research. Each of the separate branches: mobile, desktop, Industrial IoT, consumer electronics, embedded software, third-party app ecosystems, cloud, web, games, augmented and virtual reality, and data science and machine learning, were weighted independently and then combined.

To minimise other important sampling biases across our outreach channels, we weighted the responses to derive a representative distribution for technologies used and developer segments. Using ensemble modelling methods, we derived a weighted distribution based on data from independent, representative channels, excluding the channels of our research partners, to eliminate sampling bias due to respondents who were recruited via these channels. Again, this was performed separately for each of mobile, industrial IoT, consumer electronics, embedded software, third-party app ecosystems, desktop, cloud, web, games, augmented and virtual reality, and data science and machine learning.