IEEE websites place cookies on your device to give you the best user experience. By using our websites, you agree to the placement of these cookies. To learn more, read our Privacy Policy.
The methodology behind our rankings
Our interactive ranking of the most popular programming languages was first created by data journalist Nick Diakopoulos in 2013. The current version is maintained by IEEE Spectrum senior editor Stephen Cass with development support from Preeti Kulkarni and Michael Novakovic. As no one can look over the shoulders of every programmer, we have chosen metrics that we believe are reasonable proxies of popularity. By combining metrics to synthesize a single ranking we hope to even out statistical fluctuations, and changing the weights given to different metrics as they’re combined lets us emphasize different aspects, such as what's popular with employers in our Jobs ranking. Data is gathered through a combination of manual collection and APIs and combined using an R script.
We originally started with a list of over 300 programming languages gathered from GitHub. We looked at the volume of results found on Google when we searched for each one using the template “X programming” where “X” is the name of the language. We then filtered out languages that had a very low number of search results, and followed that by going through the remaining entries by hand to narrow them down to the most interesting. Since then, each year we review the list as new languages find their footing and others slip into obscurity.
Our final set of 57 languages includes names familiar to most computer users, such as Java, stalwarts like Cobol and Fortran, and languages that thrive in niches, like Haskell. The Processing language was dropped from our rankings this year because its name is a common word even within programming. Its generic name makes it hard to separate out when the word “processing” is referring specifically to the language (unlike, say, Python, which is a common word generally but nearly always refers to the language within a programming context). Before we scrubbed it from the list, Processing’s score, and thus its ranking, seemed artificially high for a niche language. We hope to attack this problem in next year’s rankings.
We gauged the popularity of languages using the following sources for a total of nine metrics.
We measured the number of hits for each language by using search for the template “X programming.” This number indicates the volume of online information resources about each programming language. We took the measurement in August 2022, so it represents a snapshot of the Web at that particular moment in time. This data was gathered manually.
We measured the number of hits on Twitter for the template “X programming” for the 7.5 months from January 2022 to mid-August 2022 using the Twitter Search API. This number indicates the amount of chatter on social media for the language and reflects the sharing of online resources like news articles or books, as well as physical social activities such as hackathons.
Stack Overflow is a popular site where programmers can ask questions about coding. We measured the number of questions posted that mention each language for the 12 months ending August 2022. Each question is tagged with the languages under discussion, and these tags are used to tabulate our measurements using the Stack Exchange API.
Reddit is a news and information site where users post links and comments. On Reddit, we measured the number of posts mentioning each of the languages during the period spanning September 2021 and August 2022, using the template “X programming” across any subreddit on the site. We collected data using the Reddit API.
IEEE maintains a digital library with over 3.6 million conference and journal articles covering a wide array of scientific and engineering disciplines. We measured the number of articles that mention each of the languages in the template “X programming” for the years 2021 and 2022. This metric captures the prevalence of the different programming languages as used and referenced in scholarship. We collected data using the IEEE Xplore API.
We measured the demand for different programming languages in job postings on the IEEE Job Site. The IEEE Jobs Site has a large number of non-U.S. listings. Because some of the languages we track could be ambiguous in plain text—such as D, Go, J, Ada, and R—we searched for job listings with those words in the job description and then manually examined listings. When the number of listings returned was greater than 500, 200 of the listings were examined as a sample, and the result was used to calculate the total number of matching jobs. The search was conducted in August 2022.
We measured the demand for different programming languages on the CareerBuilder job site. CareerBuilder listings were those offered within the United States. Because there is no publicly available API, we manually searched for listings that included each language. Some of the languages we track could be ambiguous in plain text—such as Go, J, and R—so we manually inspected each listing to remove false positives (for example, listings looking for experience with the Americans With Disabilities Act rather than the Ada programming language.). When more than 200 results were returned, 200 of the listings were examined as a sample, and the result was used to calculate the total number of matching jobs. The search was conducted in August 2022.
GitHub is a public repository for many volunteer-driven open-source software projects, and so indicates what languages coders choose to work in when they have a personal choice. We use looked at two metrics from GitHub: repositories that have been “starred” by users, which reflects long-term interests, and the number of pull requests, which indicates current activity. We used data gathered by GitHut 2.0, which measures the top 50 languages used by number of repositories tagged with that language and draws from GitHub's public API. The data covers the first quarter of 2022.
Stephen Cass is the special projects editor at IEEE Spectrum. He currently helms Spectrum's Hands On column, and is also responsible for interactive projects such as the Top Programming Languages app. He has a bachelor's degree in experimental physics from Trinity College Dublin.
A cautionary tale of NFTs, Ethereum, and cryptocurrency security
On 4 September 2018, someone known only as Rabono bought an angry cartoon cat named Dragon for 600 ether—an amount of Ethereum cryptocurrency worth about US $170,000 at the time, or $745,000 at the cryptocurrency’s value in July 2022.
It was by far the highest transaction yet for a nonfungible token (NFT), the then-new concept of a unique digital asset. And it was a headline-grabbing opportunity for CryptoKitties, the world’s first blockchain gaming hit. But the sky-high transaction obscured a more difficult truth: CryptoKitties was dying, and it had been for some time.
Dragon was never resold—a strange fate for one of the most historically relevant NFTs ever. Newer NFTs such as “The Merge,” a piece of digital art that sold for the equivalent of $92 million, left Dragon behind as the NFT market surged to record sales, totaling roughly $18 billion in 2021. Has the world simply moved on to newer blockchain projects? Or is this the fate that awaits all NFTs?
To understand the slow death of CryptoKitties, you have to start at the beginning. Blockchain technology arguably began with a 1982 paper by the computer scientist David Chaum, but it reached mainstream attention with the success of Bitcoin, a cryptocurrency created by the anonymous person or persons known as Satoshi Nakamoto. At its core, a blockchain is a simple ledger of transactions placed one after another—not unlike a very long Excel spreadsheet.
The complexity comes in how blockchains keep the ledger stable and secure without a central authority; the details of how that’s done vary among blockchains. Bitcoin, though popular as an asset and useful for money-like transactions, has limited support for doing anything else. Newer alternatives, such as Ethereum, gained popularity because they allow for complex “smart contracts”—executable code stored in the blockchain.
“Before CryptoKitties, if you were to say ‘blockchain,’ everyone would have assumed you’re talking about cryptocurrency”—Bryce Bladon
CryptoKitties was among the first projects to harness smart contracts by attaching code to data constructs called tokens, on the Ethereum blockchain. Each chunk of the game’s code (which it refers to as a “gene”) describes the attributes of a digital cat. Players buy, collect, sell, and even breed new felines. Just like individual Ethereum tokens and bitcoins, the cat’s code also ensures that the token representing each cat is unique, which is where the nonfungible token, or NFT, comes in. A fungible good is, by definition, one that can be replaced by an identical item—one bitcoin is as good as any other bitcoin. An NFT, by contrast, has unique code that applies to no other NFT.
There’s one final piece of the blockchain puzzle you need to understand: “gas.” Some blockchains, including Ethereum, charge a fee for the computational work the network must do to verify a transaction. This creates an obstacle to overworking the blockchain’s network. High demand means high fees, encouraging users to think twice before making a transaction. The resulting reduction in demand protects the network from being overloaded and transaction times from becoming excessively long. But it can be a weakness when an NFT game goes viral.
Launched on 28 November 2017 after a five-day closed beta, CryptoKitties skyrocketed in popularity on an alluring tagline: the world’s first Ethereum game.
“As soon as it launched, it pretty much immediately went viral,” says Bryce Bladon, a founding member of the team that created CryptoKitties. “That was an incredibly bewildering time.”
Sales volume surged from just 1,500 nonfungible felines on launch day to more than 52,000 on 10 December 2017, according to nonfungible.com, with many CryptoKitties selling for valuations in the hundreds or thousands of dollars. The value of the game’s algorithmically generated cats led to coverage in hundreds of publications.
Each CryptoKitty is a token, a set of data on the Ethereum blockchain. Unlike the cryptocurrencies Ethereum and Bitcoin, these tokens are nonfungible; that is, they are not interchangeable.
Dapper Labs
What’s more, the game arguably drove the success of Ethereum, the blockchain used by the game. Ethereum took off like a rocket in tandem with the release of CryptoKitties, climbing from just under $300 per token at the beginning of November 2017 to just over $1,360 in January 2018.
Ethereum’s rise continued with the launch of dozens of new blockchain games based on the cryptocurrency through late 2017 and 2018. Ethermon, Ethercraft, Ether Goo, CryptoCountries, CryptoCelebrities, and CryptoCities are among the better-known examples. Some arrived within weeks of CryptoKitties.
This was the break fans of Ethereum were waiting for. Yet, in what would prove an ominous sign for the health of blockchain gaming, CryptoKitties stumbled as Ethereum dashed higher.
Daily sales peaked in early December 2017, then slid into January and, by March, averaged less than 3,000. The value of the NFTs themselves declined more slowly, a sign the game had a base of dedicated fans like Rabono, who bought Dragon well after the game’s peak. Their activity set records for the value of NFTs through 2018. This kept the game in the news but failed to lure new players.
Today, CryptoKitties is lucky to break 100 sales a day, and the total value is often less than $10,000. Large transactions, like the sale of Founder Cat #71 for 60 ether (roughly $170,000) on 30 April 2022, do still occur—but only once every few months. Most nonfungible fur-babies sell for tiny fractions of 1 ether, worth just tens of dollars in July 2022.
CryptoKitties’ plunge into obscurity is unlikely to reverse.Dapper Labs, which owns CryptoKitties, has moved on to projects such as NBA Top Shot, a platform that lets basketball fans purchase NFT “moments”—essentially video clips—from NBA games. Dapper Labs did not respond to requests for an interview about CryptoKitties. Bladon left Dapper in 2019.
One clue to the game’s demise can be found in the last post on the game’s blog (4 June 2021), which celebrates the breeding of the 2 millionth CryptoKitty. Breeding, a core mechanic of the game, lets owners pair their existing NFTs to create algorithmically generated offspring. This gave the NFTs inherent value in the game’s ecosystem. Each NFT was able to generate more NFTs, which players could then resell for profit. But this game mechanism also saturated the market. Xiaofan Liu, an assistant professor in the department of media and communication at City University of Hong Kong who coauthored a paper on CryptoKitties’ rise and fall, sees this as a flaw the game could never overcome.
“The price of a kitty depends first on rarity, and that depends on the gene side. And the second dimension is just how many kitties are on the market,” Liu says. “With more people came more kitties.”
More players meant more demand, but it also meant more opportunities to create supply through breeding new cats. This quickly diluted the rarity of each NFT.
Bladon agrees with that assessment of the breeding mechanism. “I think the criticism is valid,” he says, explaining that it was meant to provide a sense of discovery and excitement. He also hoped it would encourage players to hold on to NFTs instead of immediately selling, as breeding, in theory, provided lasting value. 
The CryptoKitties blockchain game involves collecting, selling, and breeding nonfungible felines. The example here assumes your kitty is female.Dapper Labs
The sheer volume of CryptoKitties caused another, more immediate problem: It functionally broke the Ethereum blockchain, which is the world’s second most valuable cryptocurrency by market capitalization (after Bitcoin). As explained earlier, Ethereum uses a fee called gas to price the cost of transactions. Any spike in transactions—buying, siring, and so on—will cause a spike in gas fees, and that’s exactly what happened when CryptoKitties went to the moon.
“Anything that was emblematic of CryptoKitties’ success was aped. Anything that wasn’t immediately visible was mostly ignored.”—Bryce Bladon
“Players who wanted to buy CryptoKitties incurred high gas fees,” Mihai Vicol, market analyst at Newzoo, said in an interview. “Those gas fees were anywhere from $100 to $200 per transaction. You had to pay the price of the CryptoKitty, plus the gas fee. That’s a major issue.”
The high fees weren’t just a problem for CryptoKitties. It was an issue for the entire blockchain. Anyone who wanted to transact in Ethereum, for any reason, had to pay more for gas as the game became more successful.
This dynamic remains a problem for Ethereum today. On 30 April 2022, when Yuga Labs released Otherdeeds—NFTs that promise owners metaverse real estate—it launched Ethereum gas fees into the stratosphere. The average price of gas briefly exceeded the equivalent of $450, up from about $50 the day before.
Although CryptoKitties’ demands on the network subsided as players left, gas will likely be the final nail in the game’s coffin. The median price of a CryptoKitty in the past three months is about 0.04 ether, or $40 to $50, which is often less than the gas required to complete the transaction. Even those who want to casually own and breed inexpensive CryptoKitties for fun can’t do it without spending hundreds of dollars.
The rise and fall of CryptoKitties was dramatic but gave its successors—of which there are hundreds—a chance to learn from its mistakes and move past them. Many have failed to heed the lessons: Modern blockchain gaming hits such as Axie Infinity and BinaryX had a similar initial surge in price and activity followed by a long downward spiral.
“Anything that was emblematic of CryptoKitties’ success was aped. Anything that wasn’t immediately visible was mostly ignored,” says Bladon. And it turns out many of CryptoKitties’ difficulties weren’t visible to the public. “The thing is, the CryptoKitties project did stumble. We had a lot of outages. We had to deal with a lot of people who’d never used blockchain before. We had a bug that leaked tens of thousands of dollars of ether.” Similar problems have plagued more recent NFT projects, often on a much larger scale.
Liu isn’t sure how blockchain games can curb this problem. “The short answer is, I don’t know,” he says. “The long answer is, it’s not just a problem of blockchain games.”
World of Warcraft, for example, has faced rampant inflation for most of the game’s life. This is caused by a constant influx of gold from players and the ever-increasing value of new items introduced by expansions. The continual need for new players and items is linked to another core problem of today’s blockchain games: They’re often too simple.
“I think the biggest problem blockchain games have right now is they’re not fun, and if they’re not fun, people don’t want to invest in the game itself,” says Newzoo’s Vicol. “Everyone who spends money wants to leave the game with more money than they spent.”
The launch of CryptoKitties drove up the value of Ether and the number of transactions on its blockchain. Even as the game's transaction volume plummeted, the number of Ethereum transactions continued to rise, possibly because of the arrival of multiple copycat NFT games.
That perhaps unrealistic wish becomes impossible once the downward spiral begins. Players, feeling no other attachment to the game than growing an investment, quickly flee and don’t return.
Whereas some blockchain games have seemingly ignored the perils of CryptoKitties’ quick growth and long decline, others have learned from the strain it placed on the Ethereum network. Most blockchain games now use a sidechain, a blockchain that exists independently but connects to another, more prominent “parent” blockchain. The chains are connected by a bridge that facilitates the transfer of tokens between each chain. This prevents a rise in fees on the primary blockchain, as all game activity occurs on the sidechain.
Yet even this new strategy comes with problems, because sidechains are proving to be less secure than the parent blockchain. An attack on Ronin, the sidechain used by Axie Infinity, let the hackers get away with the equivalent of $600 million. Polygon, another sidechain often used by blockchain games, had to patch an exploit that put $850 million at risk and pay a bug bounty of $2 million to the hacker who spotted the issue. Players who own NFTs on a sidechain are now warily eyeing its security.
The cryptocurrency wallet that owns the near million dollar kitten Dragon now holds barely 30 dollars’ worth of ether and hasn’t traded in NFTs for years. Wallets are anonymous, so it’s possible the person behind the wallet moved on to another. Still, it’s hard not to see the wallet’s inactivity as a sign that, for Rabono, the fun didn’t last.
Whether blockchain games and NFTs shoot to the moon or fall to zero, Bladon remains proud of what CryptoKitties accomplished and hopeful it nudged the blockchain industry in a more approachable direction.
“Before CryptoKitties, if you were to say ‘blockchain,’ everyone would have assumed you’re talking about cryptocurrency,” says Bladon. “What I’m proudest of is that it was something genuinely novel. There was real technical innovation, and seemingly, a real culture impact.”
This article was corrected on 11 August 2022 to give the correct date of Bryce Bladon's departure from Dapper Labs.
This article appears in the September 2022 print issue as “The Spectacular Collapse of CryptoKitties.”
