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010   $a3-031-59922-5
024 7 $a10.1007/978-3-031-59922-4
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035   $a(DE-He213)978-3-031-59922-4
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100   $a20241011d2024      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aComputational Thinking $eFirst Algorithms, Then Code /$fby Paolo Ferragina, Fabrizio Luccio
205   $a2nd ed. 2024.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2024.
215   $a1 online resource (204 pages)
225 1 $aUndergraduate Topics in Computer Science,$x2197-1781
311   $a3-031-59921-7 
327   $aA Brief Historical Outline -- A Problem with Which to Begin -- Algorithms and Coding -- The Tournament -- A Financial Problem -- Secret Messages -- Putting Things in Order -- "Easy" and "Difficult" Problems -- Search Engines -- Data Compression -- Recursion.
330   $aA topic important to pre-university as well as to university curricula for computing and various other disciplines, computational thinking examines processes in the mind engaged in addressing problems such that answers/solutions can be formulated as computational increments and then, algorithms. This revised and updated textbook/guide offers a gentle motivation and introduction to computational thinking, in particular to algorithms and how they can be coded to solve significant, topical real problems from domains such as finance, cryptography, web search, data compression and bioinformatics. Although the work assumes only basic mathematical knowledge, it still upholds the scientific rigor indispensable for transforming general ideas into executable algorithms, giving several solutions to common tasks, taken from topics of our everyday world. Topics and features: Provides a readily accessible introduction, suitable for undergraduate and high-school students, as well as for self-study Organizes content neatly and conveniently by application or problem area Offers a helpful supporting website with Python code that implements the algorithms in the book Anchors the content practically, examining an excellent variety of modern topics in a concise volume Assumes knowledge of only basic computing skills as a prerequisite Written by highly experienced lecturers, as well as researchers of world renown A unique and reader-friendly textbook/reference, the title is eminently suitable for undergraduate students in computer science, engineering, and applied mathematics, university students in other fields, high-school students with an interest in STEM subjects, and professionals who want an insight into algorithmic solutions and the related mindset. Paolo Ferragina is professor of computer science at the Sant?Anna School of Advanced Studies, Italy, and Fabrizio Luccio is an emeritus professor of computer science at the University of Pisa, Italy.
410  0$aUndergraduate Topics in Computer Science,$x2197-1781
606   $aAlgorithms
606   $aComputer science
606   $aSoftware engineering
606   $aPython (Computer program language)
606   $aMathematics$xData processing
606   $aDesign and Analysis of Algorithms
606   $aComputer Science Logic and Foundations of Programming
606   $aSoftware Engineering
606   $aPython
606   $aComputational Science and Engineering
615  0$aAlgorithms.
615  0$aComputer science.
615  0$aSoftware engineering.
615  0$aPython (Computer program language).
615  0$aMathematics$xData processing.
615 14$aDesign and Analysis of Algorithms.
615 24$aComputer Science Logic and Foundations of Programming.
615 24$aSoftware Engineering.
615 24$aPython.
615 24$aComputational Science and Engineering.
676   $a005.1
700   $aFerragina$b Paolo$066343
701   $aLuccio$b Fabrizio$01245
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910896528103321
996   $aComputational Thinking$94211458
997   $aUNINA