At the end of the line

PM adopts a clean approach to statement separation. PM statements are formally separated by semicolons. However, these may be omitted if the next statement starts on a new line. This is the only syntactic role for line breaks – statements and expressions may sprawl across as many lines as you wish. For die-hard C/C++/Java programmers, it is also possible to add a semicolon at the end of a statement list.

 a=1; b=2; c=1  
 x = -b + sqrt( b**2 - 4 * a * c) /  
                  2*a  
 print("x="//x)

Semicolons are also used in constructors for two-dimensional data structures: arrays and matrices. Line breaks can be substituted for semicolons here too, enabling you to write something like:

 id_matrix = ( 1,0,0  
               0,1,0  
               0,0,1 )

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Data in, data out

When a program is running over multiple processors or processing cores then it is important to be able to map where data are flowing. One way in which data flows can be translated into programming language semantics is though argument passing to subroutines. In the absence of global variables, data transfer to and from a subroutine straightforwardly can be directly related to communication to and from another processor. In PM, the emphasis is on data parallelism through the for statement. for index in array do index=process(index) endfor So what are the rules governing data flow into and out of this statement? These are primarily based around variable locality. x:= 1 for index in array do y:=func(index) index=process(x,y) endfor Here x is relatively global to the for statement and y is local to it (a variables scope only extends to the end of the statement block in which it is defined). There are two ways t...

Compile time, run time, coffee time

[ Please note that in the following discussion I will be using PM 0.5 notation, which is slightly different to PM 0.4 and also in some flux as PM 0.5 is still in development. ] Many programming languages (and most newly developed ones) include some form of compile-time programming, ranging from simple preprocessors ( #define , #if in C) to fully blown macro systems capable of re-writing the abstract syntax tree during compilation (Rust, Julia, etc .). In line with its philosophy of keeping things as simple as possible, but not simpler, PM takes a middle road with compile-time programming supported primarily through the type system. There is nothing too radical here – this is not an area where the language aims to break new ground. The PM approach centres around the use of compile-time types. Many languages use special types to denote literal values and PM follows this trend. Literal integers, reals, strings and Booleans each have their own types: literal(int) , litera...

The PM Type System

In common with other aspects of PM design, the type system is designed to facilitate the use of flexible programming constructs, such as polymorphism and dynamic dispatch, while emphasising the generation of fast, static, code. In common with many other modern languages, PM also attempts to combine the safety of static typing with the expressivity of dynamically typed languages such as Python . The type of any PM expression may usually be determined by a static examination of the code. Variables take their types from an initialising expression using the ‘:=’ declaration syntax popularised by Go . a:= 100 ! Declare ‘a’ as an integer (int) variable Variables do not change type during the course of their lifetime – polymorphic programming requires the use of special values, described later. Composite values such as structures are generated using specialised expressions rather than through the invocation of type-specific creator functions: b:= struct var_descriptor...

PM Programming Language

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