After years of using Python for AI and data science, the author examines its flexibility drawbacks and argues that Go+, with its static typing and concise syntax, can address Python’s limitations, offering comparable ease for tensor operations, potential for a new deep‑learning front‑end language.
After mastering basic software testing, this article analyzes why learning a programming language—especially Java or Python—is essential for test automation engineers, compares their strengths, career prospects, and practical usage, and offers guidance on choosing the right language for beginners and career transitions.
The June 2020 TIOBE Index reveals Rust entering the top‑20 for the first time, highlights shifts among the top ten languages, presents rankings for positions 1‑20 and 21‑50, and includes historical trends and a “celebrity” list of languages from 2003‑2019.
The 2023 Stack Overflow Developer Survey reveals global trends in programming language popularity, developer roles, experience levels, education, gender diversity, salary distribution, employment status, and work habits, highlighting the impact of the pandemic and the growing importance of DevOps and AI-related technologies.
The 2020 Stack Overflow Developer Survey, with nearly 65,000 respondents, reveals trends in developer occupations, experience, education, most used programming languages, web frameworks, databases, platforms, favorite versus dreaded technologies, and salary insights across roles and regions.
Based on responses from nearly 65,000 developers worldwide, the 2020 Stack Overflow Developer Survey highlights shifting popularity of languages like Rust and TypeScript, rising DevOps salaries, preferred frameworks, database choices, work habits, and demographic insights, offering a comprehensive snapshot of the current software development landscape.
The article examines the historical development of PC and mobile operating systems, explains why China has not produced a mainstream OS or programming language, and argues that future opportunities will depend on aligning technological timing, geographic advantages, and human resources within China's growing IT ecosystem.
This tutorial walks you through using Python to crawl the TIOBE index from 2001 to the present, clean the data into a nested dictionary, and create dynamic visualizations that reveal how programming language popularity has shifted over two decades.
This article examines seven modern programming languages—Rust, Go, Kotlin, TypeScript, Swift, Dart, and Julia—detailing their key features, typical use cases, popularity trends, and why developers should consider learning them to stay competitive in today's software landscape.
The 2020 developer internet survey reveals that Go tops the list of languages developers want to learn, data science dominates interest areas, security and IoT follow, and remote/online work and learning are increasingly preferred, while experienced developers show limited expertise in machine learning.
This article presents a data-driven analysis of programming language popularity and salary distribution in the Chinese job market, featuring a detailed table of average and median wages, headcount, and percentage share for each language, along with a pie‑chart visualization.
The May 2020 TIOBE index shows C reclaiming the top spot over Java, while languages like Rust, MATLAB, and Scratch rise, R remains stable, and Objective‑C continues to fall, reflecting pandemic‑driven shifts toward embedded, data‑science, and educational programming.
The April 2020 TIOBE index reveals Scratch topping the list, rapid growth for SQL, Go, Swift and R, while Delphi drops out of the top 20, highlighting shifting trends in programming language popularity and the rising importance of visual coding for children.
A recent open‑source vulnerability report reveals that C accounts for over 30% of reported flaws while PHP’s share surged to 27%, highlighting the prevalence of XSS attacks and emphasizing the need for better coding practices across all languages.
The article predicts the demise of several once‑popular programming languages—Perl, Ruby, Visual Basic.NET, Adobe Flash/AIR, and Delphi’s Object Pascal—by examining their historical rise, current decline, and providing sample "Goodbye World" code snippets to illustrate their fading relevance.
This article ranks the seven most popular programming languages for test automation in 2020—Python, Java, JavaScript, C#, Ruby, PHP, and SmashTest—detailing their strengths, community support, and key frameworks to help you select the best language for your automation projects.
RedMonk’s Q1 2020 programming language rankings, based on GitHub and Stack Overflow activity, show Python climbing to the top two, TypeScript entering the top ten, R jumping ahead, Rust stalling, Go barely moving, and Dart surging thanks to Flutter’s popularity.
The article forecasts that Perl, Ruby, Visual Basic.NET, Adobe Flash/AIR (ActionScript), and Delphi's Object Pascal are each facing extinction as developers shift toward newer, more supported programming languages, illustrating the decline with code examples and historical context.
The 2020 HackerRank Developer Skills Report, the largest of its kind, surveys over 116,000 developers worldwide, revealing hiring preferences for bootcamp graduates, demand for full‑stack and backend talent, top programming languages, salary disparities, and developers’ work‑life habits.
The TIOBE Programming Community Index, updated monthly, measures programming language popularity using data from global engineers, courses, and major search engines, helping developers assess skill relevance and choose appropriate languages, while emphasizing that the ranking reflects popularity rather than language quality.
An overview of ten influential programming languages—from Java and C to Python and JavaScript—detailing their origins, key designers, and lasting impact on software development, illustrating why these languages have endured and continue to dominate various domains such as web, systems, and data processing.
This article chronicles Anders Hejlsberg's remarkable career—from creating Turbo Pascal and Delphi to designing C# and TypeScript—highlighting his influence on programming language design, IDE development, and the evolution of modern software engineering.
Dice Insights analyzed TIOBE, RedMonk rankings and its own job database to highlight five programming languages—Swift, Kotlin, Python, Groovy, and TypeScript—that are projected to experience rapid growth and increased adoption in the coming years.
This article forecasts the 2020 software development landscape, highlighting the rise of cloud adoption, Kubernetes, micro‑services, Python, Java, emerging languages like Rust and Kotlin, JavaScript frameworks, API standards, SQL dominance, big‑data engines Spark and Flink, and the growing impact of WebAssembly.
This article analyzes the 2019 programming language popularity by combining TIOBE, PYPL, and Stack Overflow data, highlighting the top languages, emerging trends such as Go and Kotlin, and discussing market demand and salary implications for developers.
An overview of five emerging programming languages—Elm, Kotlin, Rust, Elixir, and Crystal—highlighting their key features, advantages, and potential impact on software development, illustrating how they address modern development needs and may shape the future of the industry.
November 2019’s PYPL and TIOBE indexes show Python retaining the top spot, Java slipping, while emerging languages like Kotlin, TypeScript, Go and Rust gain momentum, and the latest database system rankings highlight shifting preferences across the development ecosystem.
Analyzing eleven years of Stack Overflow data for the eleven most popular programming languages, this article uncovers the most frequent questions, dominant frameworks, libraries and data types that trouble developers, showing how language popularity and pain points have shifted over time.
The latest TIOBE index shows C almost overtaking Java, Swift breaking into the top ten, and Rust soaring to its highest rank ever, while the overall top‑5 languages remain stable and several older languages continue to hold niche positions.
The 2019 programming language trends report analyzes the adoption stages of languages such as Elixir, Rust, Swift, .NET Core, and emerging infrastructure DSLs like Ballerina and Pulumi, offering insights for technology leaders and developers on where to invest their learning and development resources.
This article examines C's unmatched hardware efficiency, its safety trade‑offs, the rise of higher‑level languages focused on developer productivity, and why C remains essential for embedded, real‑time, and AI systems despite shifting popularity trends.
The 2019 Stack Overflow Developer Survey of over 90,000 respondents reveals the most popular programming languages, frameworks and tools, typical work hours, industry distribution, job‑change frequency, age and experience demographics, and how language choice and seniority affect developer salaries worldwide.
The report presents September 2019 salary statistics for programmers across major Chinese cities, compares programming language earnings, highlights algorithm engineer and architect pay, and analyzes the 90‑post‑1990s programmer job market including average monthly salaries near 20 K, gender distribution, city preferences, and top‑desired companies such as ByteDance, Tencent and Alibaba.
The September 2019 TIOBE and PYPL programming language rankings show Python surging to third place, Java holding first, C++ slipping, while detailed analysis highlights trends, salary expectations, and the evolving popularity of languages such as Java, C, C++, Rust, Go, and Kotlin across the industry.
An overview comparing Python and PHP highlights Python’s readability, rapid development, and broad applicability versus PHP’s server‑side strengths, detailing each language’s limitations, advantages, typical use cases, and why developers increasingly favor Python for diverse projects.
This article explains why popular programming language rankings such as TIOBE and PYPL often show conflicting results, describes how each index calculates popularity, and offers guidance on interpreting these lists when choosing a language to learn or use.
This article reviews the evolution of front‑end programming languages, discusses why extreme attitudes toward language choice hinder productive discussion, explains how platform constraints shape language selection, examines the strengths and weaknesses of JavaScript, Java, and Objective‑C, and predicts increasing convergence and cross‑platform trends among modern front‑end languages.
The May 2019 TIOBE Programming Community Index shows a stable top‑ten lineup, highlights Python's surge, R's unexpected drop from the top‑20, and provides insight into shifting popularity across languages such as Swift, Go, and PHP.
RedMonk's Q1 2019 language ranking, based on GitHub and Stack Overflow data, reveals JavaScript topping the list, modest shifts among the top 20, and highlights notable moves such as TypeScript's rise and Kotlin's surge into the top‑20.
The article examines why many consider Java outdated and inflexible, discusses its ecosystem, JVM strengths, comparisons with newer languages, and ultimately argues that despite its age Java remains a viable backbone for large‑scale software development.
This article explains the fundamental concepts of blockchain, outlines its three-layer architecture (protocol, extension, application), reviews typical language‑specific implementations, and presents a knowledge‑map that helps developers systematically study and build blockchain‑based products.
This article provides a comprehensive overview of blockchain technology, covering its fundamental concepts, layered architecture (protocol, extension, and application layers), implementation details across various programming languages, and a knowledge map to help developers understand and build blockchain-based products.
The April PYPL (Popularity of Programming Language) report presents four rankings—programming languages, IDEs, online IDEs, and databases—based on Google search frequency, highlighting Python’s 5.2% market share rise, Visual Studio’s dominance, Oracle’s decline, and the emergence of Cloud9, JSFiddle and Repl.it among online IDEs.
This article explores blockchain programming fundamentals, compares public and permissioned chains, reviews major development platforms, and evaluates the top five languages—C++, JavaScript, Python, Go, and Solidity—highlighting their strengths, weaknesses, and real‑world blockchain applications.
Dennis Ritchie, the creator of the C programming language and co‑developer of Unix, transformed modern computing through his pioneering work at Bell Labs, his collaboration with Ken Thompson, and the lasting influence of his innovations on operating systems, programming practices, and today’s software ecosystem.
In 2018 the TIOBE index crowned Python as the top programming language, highlighting its rapid 3.62% rise and dominance across academia, AI, scripting, web development, and scientific computing, while also showing notable shifts for other languages such as Kotlin, Rust, and TypeScript.
The article examines the popularity of five open‑source programming languages—PHP, Python, JavaScript, Ruby, and Go—by evaluating their community size, typical use cases, dominant frameworks, and career prospects, helping developers choose the most suitable language for web, backend, or emerging applications.
December’s TIOBE Index shows Java, C, Python, C++ and Visual Basic.NET holding the top five spots, with Visual Basic.NET surprisingly climbing to rank above C# and JavaScript, while languages like Go slip to 15, and SQL reappears after a long absence, highlighting shifting industry trends.
This article introduces blockchain as a secure data‑block structure and presents a concise overview of five popular programming languages—C++, Java, Python, Ruby, and Solidity—highlighting why each is suited for building blockchain applications.
The article reviews the October 2018 TIOBE programming language rankings, highlighting shifts such as Go moving into the top ten, SQL’s re‑entry, Rust’s slight decline, and provides a historical top‑10 trend chart while explaining the index’s methodology and its relevance for developers.
This article compares employer‑driven and developer‑driven rankings of programming languages, explains why Java, JavaScript, Python, and others dominate the job market, and advises which languages developers should learn next to maximize employability.
GitHub’s 2018 Octoverse report uncovers global developer habits, highlighting the most chatty nations, favorite emojis, peak activity hours, top programming languages, fastest‑growing topics like AI, and major platform updates such as GitHub Actions and Connect, offering a comprehensive snapshot of the open‑source ecosystem.
This article summarizes a 2018‑2019 global software development survey, highlighting the most popular programming languages, tools, hiring challenges, outsourcing attitudes, and performance metrics that shape today’s fast‑changing development landscape.
This article presents concise biographies of ten influential computer scientists, highlighting their groundbreaking algorithms, programming language innovations, award recognitions, and lasting impact on the fields of algorithms, data structures, and computer science fundamentals.
This article explores five notoriously obscure esoteric programming languages—Malbolge, Cow, Brainfuck, INTERCAL, and Whitespace—detailing their origins, unique characteristics, and providing Hello World code examples that illustrate just how unreadable and unconventional they are.
July’s TIOBE Programming Language Index reveals TypeScript’s rise to #50, sustained dominance of C and Java, the re‑entry of SQL, and notable shifts for languages like Objective‑C, Lua, F# and Haskell, offering a comprehensive snapshot of current developer preferences.
The JetBrains 2018 Developer Ecosystem report surveyed over 6,000 developers, revealing Java as the most popular language, JavaScript as the most used, Go as the most promising, IDEs as the top tools, and a clear shift toward major cloud providers for hosting applications.
Drawing from years of experience at startups, Twitter, and Google, the author contrasts dynamic languages like Ruby and JavaScript with static languages such as Java and Haskell, highlighting how type systems affect readability, tooling, and code maintenance in large‑scale software development.
The article advises beginners that the specific programming language matters less than learning core concepts, recommending Python, Java, Ruby, and JavaScript as strong entry points while emphasizing flexibility, job prospects, and the importance of not getting stuck on a single language.
This article chronicles GitHub’s ten‑year journey from its 2008 launch to becoming the world’s largest code‑hosting platform, highlighting key milestones such as the migration of Rails, the rise of Bitcoin, Node.js, Docker, Python, TensorFlow, and the platform’s impact on open‑source culture and future technology trends.
The article argues that automatic formal verification of Ethereum smart contracts using deep learning and Hoare Logic is fundamentally impossible because pre‑ and post‑conditions must be manually specified, and it further critiques the overall concept of smart contracts as an overengineered and unnecessary feature of blockchain systems.
This article compares Python, C++, Java, Lisp, and Prolog, outlining their strengths and weaknesses for artificial intelligence projects to help beginners decide which language to start with.
The 2017 Python roundup highlights its surge as the leading language for AI, data science, and software development, covering its dominance in hiring, migration to GitHub, academic recognition, educational adoption, and major ecosystem updates such as Django 2.0 and the Tangent library.
Based on Stack Overflow's Developer Story tags and Kaggle's 2017 data science survey, this article reveals the programming languages and technologies developers dislike most, examines growth versus dislike rates, and highlights key trends and recommendations for aspiring data scientists.
The November TIOBE index shows Python climbing to fourth place, surpassing C#, while other script languages slip down the top‑20, prompting analysis of Python's rapid growth, Java's decline, and the performance challenges facing scripting languages in large‑scale software.
The article examines why PHP is often labeled the worst mainstream language, highlighting its chaotic function naming, inconsistent APIs, lack of async I/O and multithreading, historical design flaws, community attitudes, and recent improvements like PHP 7, while acknowledging its early deployment advantages.
The 2017 GitHub Octoverse report reveals the platform’s massive growth and ranks the top fifteen programming languages, highlighting Python’s surge, JavaScript’s dominance, and the rising influence of AI‑related projects such as TensorFlow.
A recent Realm survey of around 100,000 developers shows Kotlin’s rapid rise in Android apps, predicting it will surpass Java as the primary language by the end of 2018, driven by Google’s official support and Kotlin’s modern, concise syntax.
This article presents an in‑depth interview with Chris Lattner, covering his education, the creation of LLVM, the birth of Swift, his management philosophy, ABI stability, and the future of Swift across platforms, offering valuable insights into modern compiler and language design.
This article presents a side‑by‑side comparison of three major blockchain platforms—Bitcoin, Ethereum, and Hyperledger Fabric—detailing their required cryptocurrencies, network types, permission models, consensus algorithms, smart‑contract support, and primary programming languages, and typical use cases.
A recent Eclipse Foundation survey of 713 developers reveals the most popular programming languages and operating systems across constrained IoT devices, gateways, and cloud platforms, highlighting C/C++ dominance, Java's rise, and Linux's prevalence in the IoT ecosystem.
Python is favored for data‑mining algorithms because its clear syntax, built‑in advanced data structures, easy text handling, extensive libraries, and widespread community support outweigh its slower execution speed compared to Java or C, allowing rapid development and seamless integration with high‑performance code when needed.
The article compares Swift and Kotlin, highlighting their similarities and differences for developers familiar with either language, and argues that programming languages are merely tools that should be chosen based on platform needs rather than personal bias.
The May 2023 TIOBE Index ranks the top 20 programming languages, showing notable declines for Java and C, while presenting detailed trend charts for languages such as Python, JavaScript, Go, and Swift, and explains how the index aggregates data from major web sources.
The article examines recent trends showing Python’s rapid rise against Java’s declining popularity, compares their core differences in typing, syntax, performance, and ecosystem, and discusses why programmers should understand these shifts across web, cloud, mobile, and data science domains.
The article examines the ongoing debate about Java's relevance versus Python's rising popularity, presenting recent job market statistics, usage trends, and a detailed comparison of the two languages' characteristics, performance, cross‑platform capabilities, and roles in modern IT domains.
This article compares R, Python, Scala, and Java for big‑data projects, outlining each language’s strengths and weaknesses, and offers guidance on selecting the most suitable language based on project requirements, team expertise, and production needs.
The article reviews the major software development trends of 2016—including progressive web apps, chatbots, evolving front‑end frameworks, cloud adoption, and machine‑learning breakthroughs—while highlighting key programming languages, databases, tools, and technologies to watch in 2017.
The article argues that mastering a wide range of programming languages deepens understanding of universal language models, improves tool selection, and expands career opportunities, and it provides a step‑by‑step roadmap—including meta‑learning, choosing prototype languages, and focused practice—supported by recommended resources and real‑world examples.
This article summarizes the 2016 Stack Overflow Developer Survey and other popularity indexes, presenting usage percentages, favorite and dreaded languages, and the technologies developers most want to learn, while discussing the limitations of such data and offering practical advice for continuous learning.
Based on data from TIOBE, PYPL, StackOverflow, GitHub, Indeed, Glassdoor and other sources, this article examines which programming languages are most popular worldwide and most in demand by industry, highlighting trends such as Java’s dominance, the rise of Python, JavaScript’s prevalence, and emerging languages for 2017.
The article presents the latest TIOBE programming language rankings, highlighting Haskell's position at 23, notable moves for MQL4, Hack, and Elixir, and provides visual trend charts for the top 10 languages along with a disclaimer about the data's scope and limitations.
The article reflects on how developers often become zealots for particular languages or tools, compares this to religious wars, and argues that abandoning blind loyalty in favor of an open, pragmatic approach leads to broader skill sets, better career decisions, and more innovative solutions.
Based on GitHub and RedMonk statistics, this article reviews the most popular programming languages in 2016, explains why JavaScript, Java, Python, Ruby, PHP, C++, and others rank highly, and offers guidance on choosing a language that fits individual career goals and project needs.
This article explores the evolution of programming languages, compares their core features such as syntax, error handling, and concurrency, and offers practical guidance on selecting and learning a language that will remain relevant for years, emphasizing historical context and hands‑on practice.
An overview of the front‑end, back‑end programming languages and databases employed by major web services such as Google, YouTube, Facebook, Amazon and others, illustrating the diverse technology stacks that power large‑scale websites.
This article traces the evolution of programming languages from the early 1950s regional assembly language to modern languages like Go and Dart, highlighting key milestones, influential predecessors, and the continual innovation that has produced over 250 distinct languages.
This article provides a comprehensive, curated overview of the most influential open‑source software across the full technology stack—including operating systems, web servers, programming languages, frameworks, databases, big‑data tools, and development utilities—offering practical insights for engineers seeking to understand and adopt proven solutions.
The author compares Rust and Go using a series of micro‑benchmarks across common algorithms, presenting CPU time, elapsed time, memory usage and code size, and concludes that while Rust is roughly 30 % faster, Go produces about 30 % less code, making it a better choice for enterprise applications.
This article profiles ten influential computer scientists and innovators—from Donald Knuth and Edsger Dijkstra to John Backus and Tony Hoare—highlighting their groundbreaking contributions, awards, and lasting impact on algorithms, programming languages, and the evolution of computer science.
This article reveals how many sci‑fi films showcase actual code snippets—ranging from C++ and assembly to HTML and Lua—sourced from blogs, manuals, and open‑source projects, offering a fascinating glimpse into the authentic programming behind cinematic tech scenes.
The article examines how early‑stage startups can evaluate less‑common programming languages—Python, Ruby, Node.js, and Go—by weighing their disadvantages such as dynamic typing challenges, limited community support, hiring difficulties, and performance constraints, and explains why a mixed Python‑Go stack may balance rapid development with long‑term stability.
The article argues that claims of mastering programming in a few days are misleading, presents research showing a decade is typically needed to achieve expertise, and offers practical advice on how to become a competent programmer through sustained practice, collaboration, and thoughtful language selection.
In a series of interviews, the creators of Node.js, Python, Ruby, Kotlin, Scala, C++, Dart, Julia, and Clojure discuss each language's core strengths, design goals, and the contexts in which developers should choose them, offering a panoramic view of modern programming language evolution.
The author, a programmer with 32 years of experience, argues that continuous self‑education and staying abreast of emerging technologies are personal responsibilities, not the employer’s, illustrating this through a series of career anecdotes spanning from early microcomputers to modern mobile and web development.
A recent study analyzes startup technology choices, revealing the most popular programming languages, frontend frameworks, databases, mobile platforms, infrastructure services, DevOps tools, search technologies, API integrations, and advanced big‑data solutions across different performance tiers.
The October TIOBE Programming Language Index shows Java climbing past 20% market share, highlights rapid shifts for languages like OpenEdge ABL, VBScript and Go, and explains how the ranking—based on search engine data—can guide developers in skill assessment and language selection for new projects.
This tongue‑in‑cheek chronicle traces the evolution of programming languages—from the 1801 Jacquard loom’s punched‑card instructions and Ada Lovelace’s theoretical algorithm, through Turing’s universal machine, the birth of FORTRAN, Lisp, COBOL, C, Java, and up to modern JavaScript—mixing factual milestones with satirical commentary.
An analysis of 2015 job market data reveals the most in‑demand programming languages, their average salaries, and key factors such as enterprise hiring practices, multi‑skill requirements, and the limitations of using past trends to predict future technology popularity.
A recent study analyzes startup technology choices across programming languages, front‑end, databases, mobile, infrastructure, DevOps, APIs, advanced tech, and big‑data tools, revealing the most popular options and how they differ between ordinary, good, and excellent companies.
