SlashData Developer Economics is the leading research programme on mobile, desktop, industrial IoT, consumer electronics, third party app ecosystems, cloud, web, game, AR/VR and machine learning developers, as well as data scientists, tracking the developer experience across platforms, revenues, apps, languages, tools, APIs, segments, and regions.

The 19th Developer Economics global survey wave ran from June to August 2020 and reached more than 17,000 developers in 159 countries. This research report delves into key developer trends for Q3 2020 and beyond.

The report focuses on six major themes - each with its own visualisations, showing how the data lends insight into the developer community.

1. Developers’ extra needs due to COVID-19: Working and performing during a pandemic will leave deep marks behind, both financially and psychologically speaking. In this chapter, we explore COVID-19’s effects on developers’ changing needs in relation to their development activities.

2. Language communities - an update: Programming languages are often the kernels of strong communities and the subject of opinionated debate. 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.

3. Why do developers adopt or reject cloud technologies? In a world where infrastructure can be provisioned and destroyed at will, and where data and server configurations can be transferred easily between homogeneous systems, cloud providers have to find other areas of differentiation in order to compete. Vendor lock-in is much less of an issue for users than it once was, and the rise of the developer as a decision-maker has put even more power into their hands. In this chapter, we look at some of the reasons that developers give for adopting or rejecting different cloud technologies and provide insight into why things are as they are.

4. Who is into DevOps? DevOps is commonly used as a catch-all term to describe a cultural shift within organisations that enables developers to release software faster and more reliably. However, DevOps is not a single, coherent sector or technology, which often creates confusion as to who is considered a DevOps practitioner. In this chapter, we offer a fresh view on who is into DevOps based on the activities developers are involved in. We also look at the specific roles and software sectors that are most associated with the DevOps culture.

5. What do developers value in open source? Based on our research, the use of open-source software (OSS) is ubiquitous in the global developer community. In this chapter, we explore what exactly developers value in using OSS. We also highlight some uncertainties around the future of the open-source movement by presenting trends across geographic regions and software sectors.

6. Emerging technologies: As interest in a technology waxes and wanes, so does its influence. The hot topic of yesterday becomes insignificant in the face of new challenges and opportunities. In our surveys, we have tracked engagement with and adoption of emerging technologies for the past two and a half years. In this chapter, we discuss which technologies have increased and decreased in popularity over the previous twelve months.

Methodology

Developer Economics 19th edition reached 17,000+ respondents from 159 countries around the world. As such, the Developer Economics series continues to be the most global independent research on mobile, desktop, industrial IoT, consumer electronics, third party app ecosystems, cloud, web, game, AR/VR, 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 June and August 2020.

Respondents to the online survey came from 159 countries, including major app and machine learning development hotspots such as the US, China, India, Israel, the UK, and Russia and 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 - Simplified Chinese, Traditional Chinese, Spanish, Portuguese, Vietnamese, Russian, Japanese, and Korean - and promoted by more than 70 leading community and media partners within the software development industry.

Our respondents came from a broad age spectrum, from young coders who are under 18 to the seasoned ones over 55. As software development is still a man’s world, 84% of our respondents were male and 14% female, excluding other options and those who did not specify their gender. Respondents were asked which types of projects they are involved in out of the twelve 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, and apps/extensions for third party 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 weighted the regional distribution across eight regions by a factor that was determined by the regional distribution and growth trends identified in our Developer Economy research. Each of the separate branches: mobile, desktop, industrial IoT, consumer electronics, 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 modeling 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, third party app ecosystems, desktop, cloud, web, games, augmented and virtual reality, and data science and machine learning

For more information on our methodology please visit https://www.slashdata.co/methodology.