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Explain the phase structure of a typical compiler and the role of each phase. Use regular expressions and context-free grammars to describe the syntax of simple programming languages. Illustrate the features and characteristics of different programming paradigms, including procedural, functional, and object-oriented programming. Explain the concepts of binding, scope, block structure, and lifetime, and apply them to resolving variable uses to their binding sites in a variety of languages.
Describe and apply the basic concepts of type systems, including primitive types, compound, and recursive types, abstract data types, and type equivalence models. Describe the strengths and limitations of static and dynamic typing disciplines.
CSCI 3136: Principles of Programming Languages
Describe and apply the basic concepts of data abstraction, encapsulation, object-oriented classes, and modules. Explain basic approaches and applications for the formalization of programming language semantics. Syntax and Semantics 2. Programs that manipulate programs as data.
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Techniques for describing language syntax. Functional programming.
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Object-oriented programming. Type systems. Type checking.
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Front-end involves manipulating what a user sees directly: think of the interface you see when you log in to any web interface. The back-end is all of the magic that happens sight unseen — the way servers process your password and grant you access to all of your data. There are also different types of programming paradigms: different ways to express logic, and different functionalities for each programming language that at an aggregate level, can be summed up into categorical differences. Here is an overview of the major paradigms in programming:.
There are also programming paradigms, mostly a bit outdated or a bit theoretical, that revolve around procedural programming, logic programming, and symbolic programming.
Research those if you have the time, and compare and contrast! Simple is better than complex. Complex is better than complicated. Flat is better than nested. Sparse is better than dense. One of the founding principles of effective programming is a sort of forced simplicity that becomes natural with time and iteration.
Perhaps perfectly summarized in the Zen of Python , simple is better than complex — and complex is better than complicated. Much like good writing, which sometimes requires focusing on the right ideas and cutting out as many unnecessary words as possible, good programming means keeping the underlying logic expressed simply so that it can be readable to others and perhaps most importantly, your future self! Humans are notoriously bad at exponential thinking and programming depends upon that very strand of thought.
A few microseconds of difference in one operation can mean a difference of thousands of hours when extended to a chain of operations that extends past the trillions. There are three concepts here that can help you manage that complexity. Become familiar with the concept of time complexity in programming and specifically big O notation.
Principles of Programming Languages - ANU
Put simply, Big O notation maps out a pattern of how an algorithm will respond to a given set of inputs. A common example of this is the return or print algorithm in most programming languages. A million data points? Expect it to run a million times slower than with just one.