Why New Programming Languages Are No Longer Being Created
The article analyzes why the explosion of new programming languages has stalled, citing long product lifecycles, entrenched C‑centric ecosystems, hiring and training costs, and real‑world case studies like a Rust‑based embedded project that failed, while noting the limited success of Go and Rust when they solve genuine gaps.
Programming language concentration
Since the 1980s dozens of languages appeared, but the TIOBE index for the past 20 years shows only C, Java, Python, C++, C#, and JavaScript dominate.
Case study: 2015 automotive project
Technical selection chose C for low‑level drivers, C++ for the application layer, and Python for scripting without evaluating alternatives.
Factors limiting adoption of new languages
Product lifetimes of ten years or more make it risky to adopt a language whose compiler or ecosystem is immature; loss of maintenance would require a costly rewrite.
The embedded ecosystem is built on C: ARM CMSIS library, vendor SDKs, and RTOS APIs are all written in C. Re‑implementing these components in a new language would be overwhelming.
Recruitment and training costs: niche language expertise (e.g., Kotlin Native) yields few resumes, while C/C++ expertise is abundant; a learning curve can consume months of a team’s capacity.
Concrete failure: Rust in embedded firmware (2018)
A startup attempted to rewrite firmware in Rust for memory safety and performance. After three months the project was abandoned because essential components—CAN‑bus stack, Modbus library, and bootloader—had no Rust implementation or were of poor quality, forcing a return to C.
Ecosystem as decisive factor
Java’s longevity is tied to Spring and enterprise frameworks; Python’s rise is linked to NumPy and TensorFlow; JavaScript dominates front‑end thanks to npm’s millions of packages. New languages must justify abandoning these mature ecosystems.
Successful newer languages
Go has gained foothold in cloud‑native environments; Rust has established a niche in systems programming. Both solve problems that existing languages struggle with and receive sustained investment from large companies or open‑source communities.
Conclusion
Stability, a mature ecosystem, and team familiarity constitute the primary criteria for language selection; reducing the number of languages can lead to a healthier development ecosystem.
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转自 良许Linux（ID：liangxulinux）
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