國立虎尾科技大學 |

Computational thinking = first algorithms, then code /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Computational thinking/ by Paolo Ferragina, Fabrizio Luccio.
其他題名:	first algorithms, then code /
作者:	Ferragina, Paolo.
其他作者:	Luccio, Fabrizio.
出版者:	Cham :Springer International Publishing : : 2024.,
面頁冊數:	xii, 197 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Computational Science and Engineering. -
電子資源:	https://doi.org/10.1007/978-3-031-59922-4
ISBN:	9783031599224

Computational thinking = first algorithms, then code /
Ferragina, Paolo.

Computational thinkingfirst algorithms, then code /[electronic resource] :by Paolo Ferragina, Fabrizio Luccio. - Second edition. - Cham :Springer International Publishing :2024. - xii, 197 p. :ill., digital ;24 cm. - Undergraduate topics in computer science,2197-1781. - Undergraduate topics in computer science..

A 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.

A 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.

ISBN: 9783031599224

Standard No.: 10.1007/978-3-031-59922-4doiSubjects--Topical Terms:

670319
Computational Science and Engineering.

LC Class. No.: QA76.9.A43

Dewey Class. No.: 005.1

Computational thinking = first algorithms, then code /
LDR:03306nam a2200349 a 4500 001 1138177
003 DE-He213
005 20241011125743.0
006 m d
007 cr nn 008maaau
008 250117s2024 sz s 0 eng d
020 $a 9783031599224 $q (electronic bk.)
020 $a 9783031599217 $q (paper)
024 7 $a 10.1007/978-3-031-59922-4 $2 doi
035 $a 978-3-031-59922-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.A43
072 7 $a UYA $2 bicssc
072 7 $a COM014000 $2 bisacsh
072 7 $a UYA $2 thema
082 0 4 $a 005.1 $2 23
090 $a QA76.9.A43 $b F368 2024
100 1 $a Ferragina, Paolo. $3 680949
245 1 0 $a Computational thinking $h [electronic resource] : $b first algorithms, then code / $c by Paolo Ferragina, Fabrizio Luccio.
250 $a Second edition.
260 $a Cham : $c 2024. $b Springer International Publishing : $b Imprint: Springer,
300 $a xii, 197 p. : $b ill., digital ; $c 24 cm.
490 1 $a Undergraduate topics in computer science, $x 2197-1781
505 0 $a A 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.
520 $a A 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.
650 2 4 $a Computational Science and Engineering. $3 670319
650 2 4 $a Python. $3 1115944
650 2 4 $a Software Engineering. $3 669632
650 2 4 $a Computer Science Logic and Foundations of Programming. $3 1365757
650 1 4 $a Design and Analysis of Algorithms. $3 1365721
650 0 $a Computer algorithms. $3 528448
700 1 $a Luccio, Fabrizio. $3 1208224
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
830 0 $a Undergraduate topics in computer science. $3 791852
856 4 0 $u https://doi.org/10.1007/978-3-031-59922-4
950 $a Computer Science (SpringerNature-11645)