Ted Herman – författare

A Functional Start to Computing with Python enables students to quickly learn computing without having to use loops, variables, and object abstractions at the start. Requiring no prior programming experience, the book draws on Python‘s flexible data types and operations as well as its capacity for defining new functions. Along with the specifics of Python, the text covers important concepts of computing, including software engineering motivation, algorithms behind syntax rules, advanced functional programming ideas, and, briefly, finite state machines.Taking a student-friendly, interactive approach to teach computing, the book addresses more difficult concepts and abstractions later in the text. The author presents ample explanations of data types, operators, and expressions. He also describes comprehensions the powerful specifications of lists and dictionaries before introducing loops and variables. This approach helps students better understand assignment syntax and iteration by giving them a mental model of sophisticated data first.Web ResourceThe book‘s supplementary website at http://functionalfirstpython.com/ provides many ancillaries, including:Interactive flashcards on Python language elements Links to extra support for each chapter Unit testing and programming exercises An interactive Python stepper tool Chapter-by-chapter points Material for lectures

A Functional Start to Computing with Python enables students to quickly learn computing without having to use loops, variables, and object abstractions at the start. Requiring no prior programming experience, the book draws on Python’s flexible data types and operations as well as its capacity for defining new functions. Along with the specifics of Python, the text covers important concepts of computing, including software engineering motivation, algorithms behind syntax rules, advanced functional programming ideas, and, briefly, finite state machines.Taking a student-friendly, interactive approach to teach computing, the book addresses more difficult concepts and abstractions later in the text. The author presents ample explanations of data types, operators, and expressions. He also describes comprehensions—the powerful specifications of lists and dictionaries—before introducing loops and variables. This approach helps students better understand assignment syntax and iteration by giving them a mental model of sophisticated data first.Web ResourceThe book’s supplementary website at http://functionalfirstpython.com/ provides many ancillaries, including: Interactive flashcards on Python language elementsLinks to extra support for each chapterUnit testing and programming exercisesAn interactive Python stepper toolChapter-by-chapter points Material for lectures

Self-stabilizationisanestablishedprincipleofmoderndistributedsystemdesign. Theadvantagesofsystemsthatself-recoverfromtransientfailures,temporary- curity attacks,and spontaneousrecon?gurationareobvious.Lessobviousis how the ambitious goal of recovering from the most general case of a transient fault, namelythatofanarbitraryinitialstate,canleadtoasimplersystemdesignthan dealing with particular cases of failures. In the area of mathematical probl- solving, Po 'lya gave the term "the inventors paradox" to such situations, where generalizing the problem may simplify the solution. The dramatic growthof d- tributed systems, peer-to-peer distribution networks, and large grid computing environments confronts designers with serious di?culties of complexity and has motivated the call for systems that self-recover, self-tune, and self-manage. The principlesofself-stabilizationcanbeusefulfor thesegoalsofautonomoussystem behavior. The Symposium on Self-Stabilizing Systems (SSS) is the main forum for - search in the area of self-stabilization. Previous Workshops on Self-Stabilizing Systems (WSS) were held in 1989, 1995, 1997, 1999, and 2001.The previous Symposium on Self-Stabilizing Systems (SSS) took place in 2003. Thirty-three papersweresubmitted toSSS2005byauthorsfromEurope(16),NorthAmerica (8), Asia (4), and elsewhere (5). From the submissions, the program committee selected 15 for inclusion in these proceedings. In addition to the presentation of these papers, the symposium event included a poster session with brief pres- tations of recent work on self-stabilization.

This book constitutes the refereed proceedings of the 6th International Symposium on Self-Stabilizing Systems, SSS 2003, held in San Francisco, CA, USA, in June 2003.The 15 revised full papers presented were carefully reviewed and selected from 27 submissions. The papers address self-stabilization issues for various types of systems and software including communication protocols, sensor networks, biological systems, and directed networks; several new algorithms are presented.