Programming Languages: Principles and Paradigms (Undergraduate Topics in Computer Science) 2010th Edition

It amazes me as a software patent evaluator how many "job interview -- coding practice" books get lost in the details of hash tables and trees, and often miss the point of systems overview completely. The bottom line of this fine text in my opinion-- aim high! Four of the hottest career areas in IT AREN'T in coding (so much of it is being outsourced to India, China and Russia)-- they are in management of: 1. Data Science 2. Embedded Systems 3. Networking 4. Sploits.There even is a new "CTO" type job-- CDSO, for "Chief Data Science Officer." These management, team leadership and high level positions don't require you to create a list prioritization algorithm on the whiteboard in C# in half an hour, but they DO require you to understand how systems from the machine and network levels relate to solutions in choice of languages, software and --especially-- paradigms.In talking with programmers and engineers all day who submit new software for patents, I'm astonished at how many got all the way through even grad school (including Stanford and MIT) without taking a paradigm class! They can generally tell you which apps work better with trees vs. arrays, but at a high level, why to choose functional vs. imperative is often really foggy.This book thoroughly dispels the mist. The only requirement is familiarity with ANY language (and yes, for you old time engineers, it can even be C, and you don't have to be up on OOP). The publishers and marketing hype state that it is "undergrad" level, but... well, no. It starts there and explains with pedagogic excellence (typical of Springer) the basics, but rapidly gets to a level of detail that I'd characterize either as grad or as specialized undergrad (eg software engineering, including machine level interfaces).In the real world, we don't deal with "perfect" systems-- we've got o/s issues, legacy issues, and software solutions chosen by others that match imperative to big data apps that should be functional, or OOP to multiprocessor apps that should be concurrent process oriented, or embedded in Python that should be in LISP. This text takes you out of those myriad trees to see the forest-- and it's a real eye opener!Yes, if you're a teacher, this would definitely make a much needed course text. But more importantly for "my" Amazon shoppers and library clients-- I heartily recommend it for self study as well. This isn't one of those "I'm the biggest jock" show off books like demos of unhygenic lisp macros-- the authors aren't trying to show off their magnificence, but truly present a LOT of today's paradigm choices that are easily missed in coding courses, at a very easy to grasp level. Don't take this to mean there is no detail-- we get right down to stacks and registers-- but the 30,000 foot piece relates to real life practical solutions that should be made BEFORE finding out that memory is an issue (for example), including very current things like R vs. Excel and C vs. Python, as well as, yes, functional/lisp and their place in big data, etc. If you want to differentiate yourself from the "coding interview" jocks-- get this! You might surprise yourself and leapfrog them to a management - integrator - engineer - administrator "dream" job!Library Picks reviews only for the benefit of Amazon shoppers and has nothing to do with Amazon, the authors, manufacturers or publishers of the items we review. We always buy the items we review for the sake of objectivity, and although we search for gems, are not shy about trashing an item if it's a waste of time or money for Amazon shoppers. If the reviewer identifies herself, her job or her field, it is only as a point of reference to help you gauge the background and any biases.