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Our interactive rankings of the preferred programming languages was first created by knowledge journalist Nick Diakopoulos in 2013. The present model is maintained by IEEE Spectrum senior editor Stephen Cass with improvement help from Prachi Patel and Michael Novakovic. As no-one can look over the shoulders of each programmer, now we have chosen metrics that we imagine are affordable proxies of recognition. By combining metrics to synthesize a single rating we hope to even out statistical fluctuations, and by altering the weights given to completely different metrics as they’re mixed lets us to emphasis completely different facets, equivalent to what’s fashionable with employers in our Jobs rating. Information is gathered by means of a mixture of handbook assortment and APIs, and mixed utilizing an R script.
We initially began with a listing of over 300 programming languages gathered from GitHub, we appeared on the quantity of outcomes discovered on Google after we looked for every one utilizing the template “X programming” the place “X” is the title of the language. We filtered out languages that had a really low variety of search outcomes after which went by means of the remaining entries by hand to slender them all the way down to probably the most fascinating. Since then, annually we evaluate the checklist as new languages discover their footing and different languages slip into obscurity.
Our last set of 57 languages contains names acquainted to most laptop customers, equivalent to Java, stalwarts like Cobol and Fortran, and languages that thrive in niches, like Haskell. The Processing language was dropped from our rankings this yr as a result of it is title is a typical phrase even inside programming (not like, say, Python, which is a typical phrase typically, however almost all the time refers back to the language inside a programming context). This makes it onerous to separate out when the phrase “processing” is referring to the language, and the end result was a rating that appeared artificially excessive for a distinct segment language. We hope to assault this downside in subsequent yr’s rankings.
We gauged the recognition of languages utilizing the next sources for a complete of 9 metrics.
Table of Contents
Google Search
We measured the variety of hits for every language through the use of seek for the template “X programming.” This quantity signifies the quantity of on-line data assets about every programming language. We took the measurement in August 2022, so it represents a snapshot of the Internet at that individual second in time. This knowledge was gathered manually.
We measured the variety of hits on Twitter for the template “X programming” for the 7.5 months from January 2022 to mid-August 2022 utilizing the Twitter Search API. This quantity signifies the quantity of chatter on social media for the language and displays the sharing of on-line assets like information articles or books, in addition to bodily social actions equivalent to hackathons.
Stack Overflow
Stack Overflow is a well-liked web site the place programmers can ask questions on coding. We measured the variety of questions posted that point out every language for the 12 months ending August 2022. Every query is tagged with the languages beneath dialogue, and these tags are used to tabulate our measurements utilizing the Stack Exchange API.
Reddit is a information and knowledge web site the place customers put up hyperlinks and feedback. On Reddit we measured the variety of posts mentioning every of the languages, utilizing the template “X programming” from September 2021 to August 2022 throughout any subreddit on the positioning. We collected knowledge utilizing the Reddit API.
IEEE Xplore Digital Library
IEEE maintains a digital library with over 3.6 million convention and journal articles overlaying a variety of scientific and engineering disciplines. We measured the variety of articles that point out every of the languages within the template “X programming” for the years 2021 and 2022. This metric captures the prevalence of the completely different programming languages as used and referenced in scholarship. We collected knowledge utilizing the IEEE Xplore API.
IEEE Jobs Website
We measured the demand for various programming languages in job postings on the IEEE Job Site. The IEEE Jobs Website has numerous non-US listings. As a result of a few of the languages we monitor may very well be ambiguous in plain textual content—equivalent to D, Go, J, Ada, and R—we looked for job listings with these phrases within the job description after which manually examined listings. When the variety of listings returned was higher than 500, 200 of the listings have been examined as a pattern, and the end result used to calculate the full variety of matching jobs. The search was carried out in August 2022.
CareerBuilder
We measured the demand for various programming languages on the CareerBuilder job web site. CareerBuilder listings have been these supplied inside the United Acknowledged. As a result of there isn’t any publicly obtainable API, we manually looked for listings together with every language. As a result of a few of the languages we monitor may very well be ambiguous in plain textual content—equivalent to Go, J, and R—we manually inspected itemizing to take away false positives (for instance, listings searching for expertise with the People with Disabilities Act slightly than the Ada programming language.). When greater than 200 outcomes have been returned, 200 of the listings have been examined as a pattern, and the end result used to calculate the full variety of matching jobs. The search was carried out in August 2022.
Github
Github is a public repository for a lot of volunteer-driven open supply software program tasks, and so signifies what languages coders select to work in once they have a private alternative. We use checked out two metrics from Github: repositories which have been “starred” by customers, which displays long run pursuits, and the variety of pull requests, which signifies present exercise. We used knowledge gathered by GitHut 2.0, which measures the highest 50 langauges utilized by variety of repositories tagged with that language and attracts from GitHub’s public API. The information covers the primary quarter of 2022.
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