Optimizing compilers through parallel processors and memory performance observing as combined approach

Phases of compilers for tokenizing the input using lexical analysis and regular expression. Abstract syntax tree in the form of parsing.. Abstract might go to error state if it has more than one input. Hence automata uses the phases of compiler with the help of algorithms which is mathematical. Processing of source code which is human readable to machine readable code which is translated at the time of runtime. While translating code should be readable which is done with the help of compilers and interpreters. Therefore it requires less memory because there is no specific code for platform. Taking string input as symbols changes state as per instructions is called finite automata. It uses regular expressions. It recognizes regular expressions. After processing all the state according to instruction it reaches final state and it is known as accepted state. If it is self compiling kind of compiler in any programming language is known as bootstrapping. Using very little part of language we could generate bootstrap compiler is many programming language. For example languages like Pascal, Haskell, C, OCaml, Java etc uses bootstrap compiler. Features containing discrete properties in mathematics like calculus, algebra that includes set theory , matrix and so on. Before runtime occurs in programming language some interpretation happens in some languages, that is translation occurs . Interpreted code can be executed without the help of machine code. It can run in many operating systems. Optimization is good , because they are interpreted as soon as they are interpreted. To one of the problem is inefficiency of compiled programming language. Small talker is of the programming language it is known for most productive for many years. Language complexity is considered seriously. Now a days we using Swift for reducing the complexity of the language.