Our top programming languages try to deal with the problem of estimating the popularity of a language in search of interactive proxy signals. We do this by creating remedies for popularity from different types of data sources that we think are good proxy for active interest for each programming language. Overall, we identify 64 Programming language. We then weigh each data source To create a holistic index of popularityExcept for some of the lowest scorer. Below, we describe the sources of data that we use to achieve measures, and the waiting scheme we use to produce overall indices.
By popularity, we mean that we are trying to rank languages that are in active use, including activity from maintaining heritage systems. We look at three different aspects of popularity: In active use between specific IEEE members and working software engineers (“spectrum” rankings), languages, languages that are in demand by employers (“jobs” rankings), and languages that are in zeetist (“trending” ranking.
We discovered the popularity of languages using the following sources for a total of seven matrix (see below). We collected information for all matrix in July – August 2025. In the past we trusted a lot on the API to collect data from sources, but now the data is manually assembled for the difficulty of keeping the data with the API changes and the end, and the end, and the end, and the end, and the end, and the end, and, and Because many names (C ++, scheme) of programming language were crashed into research papers and general words found in job advertisements or pars to pars for search engines. When a large number of search results individually made it impractical to solve the ambiguities by examining all the results, we used a sample of each data source, and 95 percent determined the related sample size based on estimating the right mean. All data sources do not have information for each programming language and we explain this information because the programming language “no hit” (ie is not popular).
The results of each metric are generalized to produce a relative popularity score between 0 and 1. The individual matrix is then rebuilt to produce a weight factor, joint, and result to produce an overall popularity score.In collecting matrix, we expect to compensate for statistical quirks that can distort the popularity scores of language in a particular source of data. Separating weight factors allows us to make different results for spectrum, jobs and trending rankings. We fully accept that, while these loads are subjective, they are based on our understanding of sources and our former coverage of software subjects. Separating weight factors allows us to emphasize various types of popularity and produce different ranks. We then added each weighted data source to each program and then rejuvenated the resulting frequency to produce an overall popularity score.
Top programming languages were originally created by data journalists Nick diacopolosOur statistical functioning is advisor Hillary waitingAlthough all real data is collected and calculated by us. Calculated using ranking R,
Google The world is the leading search engine, which is an ideal fit to assess the popularity of the language. We recorded the number of hits for each language by searching on the template, “X programming language” (with quotation marks) (with quotation marks) and recorded the number of results refunded by manually searching. We measured in July 2025. We like this remedy because it indicates the amount of online information resources about each programming language.
stack Overflow
stack Overflow There is a popular site where programmers can ask questions about coding. We recorded the number of questions tagged in each program within last week before our discovery (August 2025). For Mathematica/Wolfram Language, we trusted sister “Stack” for Mathematic Platform And prolong the number of programming-related questions asked in the last week. These data were collected manually. This remedy indicates what programming languages are currently going on.
IEEE makes a maintenance Digital library A wide range of scientific and engineering subjects with millions of conferences and journal articles were covered. We discovered the journal, magazine and early access articles, which refer to each language in the template “X programming” for 2025 years-by year. For thousands of articles returned search results, we identified the right sample size for 95 percent confidence interval (usually slightly more than 300) and pulled that number of articles. We sampled for each language, we identified the share of articles that use the programming language and then multiply the total number of articles by this share to have the total number of articles that refer to a given programming language. We conducted this discovery in August 2025. This metric captures the spread of various programming languages as is used and referred to in engineering scholarship.
IEEE Jobs Site
Career builder
We measured the demand for various programming languages Careerbuilder job site. We discovered the “developer” jobs given within the United States, as it is the most popular job title for the programmer. We sampled 400 job ads and manually examined them which language has been mentioned by employers in the posting. The discovery was held in August 2024. We prefer a career builder site to identify the popularity of programmer jobs among US-based companies
Github Many volunteer-powered open-sources are a public repository for software projects. we used Githb list It is one of the top 50 programming languages, such as filtering entries for things Doocker configuration script, The data covers the first quarter of 2025. This measured provides a strong indication that when they have a personal option, which language select to work in the code.
Trinity College Dublin Library
Trinity College Dublin Library Ireland and the United Kingdom are one of the six legal deposits libraries. A copy should be deposited with a library of any printed material published or distributed in Ireland, and any UK publisher or distributor will also have to submit a book at request. We discovered all the books published in the year, which corresponds to the names of the programming languages and examined the consequences of false positivity. The discovery was held in July 2025. We prefer this library collection because it mainly represents a large and classified sample of tasks, in the English language.
Strings
Discord is a popular chat-room platform where many programmers exchange information. We counted the number of tags to suit each language. In the case of languages that can also be the names of non-irregular disciplines (many nonprogram-related subjects are also dedicated disorder servers; for example, “Julia” can mention “Julia” Programming language Or Sesame Street Puppet), The results were manually examined. Disobord Was discovered in August 2025. The disboard lists several public discord servers and many young coders use site, which make a separate demographic contribution of coders.
