sutton036

Functional languages require infrastructure that inevitably adds overheads over what can theoretically be attained using assembler by hand. In particular, first-class lexical closures only work well with garbage collection because they allow values to be carried out of scope. Beware of self selection. C acts as a lowest common denominator in benchmark suites, limiting what can be accomplished. If you have a benchmark comparing C with a functional language then it is almost certainly an extremely simple program. Arguably so simple that it is of little practical relevance today. It is not practically feasible to solve more complicated problems using C for a mere benchmark. The most obvious example of this is parallelism. Today, we all have multicores. Even my phone is a multicore. Multicore parallelism is notoriously difficult in C but can be easy in functional languages (I like F#). Other examples include anything that benefits from persistent data structures, e.g. undo buffers are triv...

I want to learn the theory behind garbage collection. How do i go about it? I am also a dabbler interested in garbage collection (to the point that I wrote my own garbage collected VM called  HLVM ). I learned by reading as many research papers on garbage collection as I could get my hands on and by playing with the ideas myself, both raw in my virtual machine and also by writing memory-safe high-level simulations. The obvious answer is - a compiler textbook... The question is, is it necessary to learn lexical analysis, parsing and other stuff that usually precedes garbage collection in a text? The lexical analysis, parsing and other stuff is not relevant to garbage collection. You might get an outdated cursory overview of garbage collection from a compiler book but you need to read research papers to get an up-to-date view, e.g. with regard to multicore. In short, what are the prerequisites to learning about Garbage collection theory? You need to know about basic graph theory, poi...

GCs work by tracing reachable heap blocks starting from a set of global roots (global variables, thread stacks and CPU registers). GCs lie on a sliding scale from snapshot to on-the-fly. Snapshot GCs work from a snapshot of the global roots and heap topology. On-the-fly GCs incrementally update their interpretation of the heap as the mutators run. Wholly snapshot GCs attain high throughput because the collector runs almost entirely independently of the mutators but have high latency because taking a snapshot incurs a pause. Wholly on-the-fly GCs attain low latency because everything is done incrementally but low throughput because of the fine grained communication between the mutators and GC. In practice, all GCs lie somewhere between these two  extremes.  VCGC  is primarily a snapshot GC but it uses a write barrier to keep the collector apprised of changes to the heap topology.  Staccato  was the world's first parallel and concurrent and real-time GC but it sti...

From this Stack Overflow question: If I understand it correctly, functor gives you a new set of functions from a type you provide More generally, functors map modules to modules. Your  Set  example maps a module adhering to the ORDERED_TYPE  signature to a module implementing a set. The  ORDERED_TYPE  signature requires a type and a comparison function. Therefore, your C# is not equivalent because it parameterizes the set only over the type and not over the comparison function. So your C# can only implement one set type for each element type whereas the functor can implement many set modules for each element module, e.g. in ascending and descending order. Even if functors are just generics-for-namespace, what's the significant advantage of that approach? One major advantage of a higher-order module system is the ability to gradually refine interfaces. In OOP, everything is public or private (or sometimes protected or internal etc.). With modules, you can gradua...

Metaprogramming is possible in .NET (see compiler compilers, regular expressions, code DOM, reflection etc.) but C# is not capable of  template  metaprogramming because it does not have that language feature.

You can create cyclic data structures using purely functional programming simply by defining mutually-recursive values at the same time. For example, two mutually-recursive lists in OCaml: let rec xs = 0::ys and ys = 1::xs However, it is possible to define languages that make it impossible to create cyclic structures by design. The result is known as a  unidirectional heap  and its primary advantage is that garbage collection can be as simple as reference counting. Some real languages do prohibit cycles and use reference counting. Erlang and Mathematica are examples. For example, in Mathematica when you reference a value you make a deep copy of it so mutating the original does not mutate the copy: In[1] := xs = {1, 2, 3} Out[1] = {1, 2, 3} In[2] := ys = xs Out[2] = {1, 2, 3} In[3] := xs[[1]] = 5 Out[3] = 5 In[4] := xs Out[4] = {5, 2, 3} In[5] := ys Out[5] = {1, 2, 3}

null  everywhere. const  nowhere. APIs are inconsistent, e.g. mutating an array returns  void  but appending to a  StringBuffer returns the same mutable  StringBuffer . Collection interfaces are incompatible with immutable data structures, e.g.  Add  in  System.Collections.Generic.IList<_>  cannot return a result. No structural typing so you write  System.Windows.Media.Effects.SamplingMode.Bilinear  instead of just  Bilinear . Mutable  IEnumerator  interface implemented by classes when it should be an immutable  struct . Equality and comparison are a mess: you've got  System.IComparable  and  Equals  but then you've also got: System.IComparable<_>  System.IEquatable System.Collections.IComparer  System.Collections.IStructuralComparable  System.Collections.IStructuralEquatable  System.Collections.Generic.IComparer  System.Collections.Generic.IEqualityCo...