Top 10 Hardest Programming Languages – Full Guide!

Hardest Programming Languages

Programming languages come in many types, from basic drag-and-drop interfaces to complicated, text-based code. While all have complex parts, some languages are harder to learn than others for new programmers. 

Languages that need managing memory usage, dealing with pointers, and understanding advanced computer science ideas tend to have high barriers. Of course, finding something difficult is also personal – what clicks easily for one developer may confuse another. 

Still, some stalwart languages have gained reputations for being tricky to master, even among experienced coders. 

This article highlights 10 of the most hardest programming languages for beginning developers to learn based on factors like complicated syntax, strict frameworks, and steep learning curves around advanced features. 

While they may demand diligence and patience, overcoming one of these languages unlocks exciting capabilities for ambitious programmers.

Factors In Determining The Difficulty Of A Programming Language

Here are some factors responsible for determining a programming language’s difficulty. 

Complicated syntax – Languages with dense, confusing syntax full of braces, brackets, and punctuation tend to have steeper learning curves. Keeping track of when and where symbols need to go takes practice.

Steep learning of concepts – Understanding key programming ideas like object-oriented, functional, and reactive requires wrapping your head around new ways of coding. Grasping these high-level concepts challenges beginners.

Strict frameworks – Frameworks that enforce very specific project and code structures add additional rules beginners must follow. This reduces flexibility and freedom when starting.

Wordiness – Writing a lot of code to achieve basic tasks makes it harder for new coders to gain traction and momentum. More concise languages help minimize overwhelm.

Memory management – Manually handling memory usage/freeing up takes a heavy toll on unseasoned developers already struggling with other aspects of coding. Languages that abstract this away help ease the burden.

Limited resources/community – When languages have small stacks of learning content, beginner-friendly tutorials, and communities available, it cuts down on support for those looking to self-teach. More mainstream options tend to have richer ecosystems.

Note: Also read this blog on the topic “Top 99+ Passion Project Ideas For You – Discover Your Passion

Top 10 Hardest Programming Languages 

Here is a list of the top 10 hardest programming languages based on their syntax and real-world experience. 

  1. C++ 

C++ is considered one of the most difficult programming languages to master due to its immense complexity. It has highly advanced object-oriented programming features like multiple inheritance, templates, overloading, exception handling, and memory management, requiring new and delete for allocation/deallocation.

The complexity arises from supporting multiple programming paradigms, including procedural, OOP, and generic programming. This makes the language extremely versatile but more complex, as a developer needs to know which technique to use and when.

  1. Haskell 

Haskell incorporates extremely advanced mathematical abstractions like lazy evaluation, purity, monads, type classes and currying into a functional programming language. Developers must completely retrain thinking to use infinite data structures, recursion over loops, and reasoning about side-effect-free code.

The pervasive use of functions as first class members and esoteric type system signatures takes Haskell to a high level of abstraction very foreign to most programmers.

  1. Lisp

The unique syntax of Lisp, composed of S-expressions in the form of nested lists, distinguishes it significantly from popular curly brace languages. Developers must adopt recursive thinking to process these data structures combined with heavy use of higher-order functions and macros to manipulate code at runtime.

Lisp’s flexibility and metaprogramming facilities come at the cost of mastering these fundamentally different concepts, including closures and dynamism.

  1. Rust 

Rust’s strict rules around ownership, borrowing, and lifetimes for memory safety make the language complex, as developers have to learn an entirely new system oriented around resource management that the compiler enforces.

New Rust programmers easily get lost juggling pointers and references, leading to compile-time errors that can be challenging to debug in large systems.

  1. Scala 

As a multi-paradigm language merging object-oriented and functional programming, Scala has enormous sophistication and advanced features that take significant time to master properly.

To appreciate the elegance and capability, developers must navigate its heavyweight type system, including complexity around implicit, path-dependent types, self-types and mixin-based inheritance.

  1. Perl 

Perl has immense syntax flexibility, allowing common tasks to be accomplished in various ways leading to obfuscation. Developer proficiency depends on mastering regexes, trailing variables, contextual flow control, slicing and advanced data structures like hashes natively alongside minimal OOP support.

Due to its brevity and context sensitivity, it can be easy to write unmaintainable Perl without the deepest understanding that comes only with experience.

  1. Standard ML 

Standard ML delivers a well-developed modular programming architecture with powerful type inference capabilities rivaling dependently typed languages. The module system allows abstraction boundary enforcement while strong static polymorphic typing explicitly removes the burden of specifying types.

Concepts like functors, recursive modules and monomorphization make it challenging to advance from basics to metaprogramming mastery in ML with a long-term perspective.

  1. APL 

As an array programming language centered around manipulating vectors/matrices as first-class citizens, APL requires practitioners to shift their mindset away from scalar values and loops.

Everything centers on data structures and powerful operators indicating actions in cryptic glyphs that allow astonishing expressivity and concision unmatched by most languages once grasped. Adapting a thought from stepwise procedural execution to data transformation chains is the hardest challenge entry-level APLers face.

  1. Assembly Language 

By exposing the underlying architecture directly, assembly languages force developers to keep track of CPU registers, flags, jump targets and memory pointers/addresses requiring thinking at the machine level.

Understanding the von Neumann execution model, including the intricacies of calling conventions, stacks, parameters passing, and instruction sets, provides a rare perspective transcending higher-level languages. The increased likelihood of subtle errors and crash-prone bugs adds to the overall complexity factor for mastery.

While C is modest in features offered compared to newer languages, the need for manual memory management using pointers subject to buffer overflows combined with little runtime safety makes C notoriously difficult to master.

With low-level control inherently, complexity follows, as developers have to grasp concepts like deterministic destruction, memory leaks, dereferencing, and volatile variables alongside architecture specifics tightly for reliable system programming without room for slips in understanding; C asks for peak precision, introducing challenges to newcomers.

Challenges And Benefits Of Learning The Hardest Programming Languages

The “hardest languages” means C/C++, Haskell, Rust etc. These languages have:


  • The rules for writing them are complicated and confusing for beginners
  • They require managing memory and pointers at a low level which adds complexity
  • The error messages don’t explain problems making fixing issues difficult
  • They don’t have standard libraries that make easier languages simpler to start with
  • There are fewer learning resources available compared to popular languages


  • They are perfect for systems programming where you need speed and control
  • Mastering them builds strong basic programming skills
  • They make your resume look better and prepare you for more types of jobs
  • You appreciate easier languages more after dealing with these challenging ones

The subheading contrasts the major frustrations and challenges of learning very complex programming languages with some of the big career benefits it can provide. But without the full blog post for context, it’s hard to explain more specifically. Let me know if you need any clarification or have additional questions!

Strategies For Learning Difficult Programming Languages

Here are some strategies for learning difficult programming languages. 

  • Don’t beat yourself up if you don’t understand something at first. Programming can be confusing stuff. It takes time and practice to wrap your head around
  • Find a solid beginner tutorial or online course and stick with it. Jumping around between different learning materials gets messy quick
  • Write a bunch of little practice programs as you learn. Doesn’t have to be anything fancy, the point is to get the hands-on reps in
  • Connect with other beginners in forums and group chats. Other folks struggling alone can relate and sometimes explain concepts in simpler ways
  • Embrace the Google Searches. No shame in looking stuff up when you get errors or don’t know how something works
  • Be patient and kind to yourself! Again, this stuff is hard. Give it time to click before getting frustrated

Wrapping Up 

And there you have it, folks – 10 programming languages known to make even seasoned coders sweat. Brutal learning curves ahead with these bad boys! But just ’cause something like C++ or Haskell is complex, AF doesn’t mean it’s impossible to pick up. It’ll just take time, patience, and many Google searches. The payoff of mastering one of these beastly languages is worth it, though. You’ll be able to write kickass software and laugh in the face of boring beginner languages.

For real, though, if you’re struggling through one of these, don’t beat yourself up about it! We’ve all been there, staring at errors for hours, unable to make heads or tails of advanced syntaxes and concepts. 

Lean on online forums, YouTube tutorials, and microscopy chats – whatever helps it click! Set small goals and celebrate the tiny wins towards fluency. With that “I think I can” mindset, hard things become more manageable. 

Even the gnarliest languages like Malbolge (look that one up, it’s wild). Anyway, stick with it, and you’ll get there!

How’s that? I aimed for a conversational vibe with some light humor thrown in. Let me know if you want me to modify the tone or push it even more casual!


Is it worth learning difficult programming languages?

Learning difficult programming languages can expand your skill set, enhance problem-solving abilities, and open new opportunities in specialized fields. However, weighing the benefits against the time and effort required for mastery is essential.

How long does it take to learn a difficult programming language?

The time required to learn a difficult programming language varies depending on factors such as prior experience, learning pace, and the complexity of the language. It can take anywhere from several months to several years to achieve proficiency.

Are there easier alternatives to difficult programming languages?

Several programming languages, such as Python, JavaScript, and Ruby, offer a gentler learning curve for beginners. These languages prioritize simplicity and readability, making them more accessible to newcomers.

What resources can help me learn difficult programming languages?

Online tutorials, textbooks, coding bootcamps, and community forums are valuable resources for learning difficult programming languages. Additionally, practicing coding challenges, attending workshops, and working on real-world projects can aid comprehension and mastery.