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MASARYKOVA UNIVERZITA }w¡¢£¤¥¦§¨ FAKULTA INFORMATIKY !"#$%&'()+,-./012345<yA| Programovacı´jazyky pro vy´uku programova´nı´na SSˇ DIPLOMOVA´ PRA´ CE Bc. Luka´sˇRy´dlo Brno, 2012 Prohla´sˇenı´ Prohlasˇuji, zˇe tato diplomova´pra´ce je my´m pu˚vodnı´m autorsky´m dı´lem, ktere´ jsem vypracoval samostatneˇ. Vsˇechny zdroje, prameny a literaturu, ktere´jsem prˇi vypracova´nı´pouzˇı´val nebo z nich cˇerpal, v pra´ci rˇa´dneˇcituji s uvedenı´m u´plne´ho odkazu na prˇı´slusˇny´zdroj. Vedoucı´pra´ce: doc. RNDr. Toma´sˇPitner, Ph.D. iii Podeˇkova´nı´ Ra´d bych podeˇkoval vedoucı´mu sve´pra´ce, doc. RNDr. Toma´sˇi Pitnerovi, Ph.D. za ochotu ve´st me´te´ma, nevsˇednı´vstrˇı´cnost a trpeˇlivost i konkre´tnı´tipy. v Abstrakt Pra´ce prˇina´sˇı´zhodnocenı´ru˚zny´ch programovacı´ch jazyku˚, metodik a prostrˇedı´ pro potrˇeby vy´uky na strˇednı´ch sˇkola´ch. V u´vodnı´kapitole jsou popsane´teoreticke´ koncepty, formy vy´uky, analy´za metodik v oblasti vy´uky programova´nı´, vhodnost jednotlivy´ch paradigmat. Druha´kapitola prˇina´sˇı´prˇehled za´kladnı´ch metod graficke´ho popisu algoritmu, jejich vhodnost a vyuzˇitelnost prˇi vy´uce. Trˇetı´kapitola zacˇı´na´na´vrhem metodiky hodnocenı´programovacı´ch jazyku˚pro potrˇeby vy´uky a jejich prˇehledem. Dalsˇı´ka- pitola hodnotı´pro zmeˇnu ru˚zna´vy´vojova´prostrˇedı´, at’uzˇpouzˇı´vana´v beˇzˇne´praxi nebo urcˇena´prˇı´mo pro vy´uku. Za´veˇr pra´ce je veˇnova´n vy´ukovy´m materia´lu˚m pro semina´rˇz programova´nı´na gymna´ziu v jazyce Java metodou objects first, resp. model first (viz kapitola 1.5). Abstract This thesis is focused on teaching programming at secondary level schools, in the way of choosing languages, methodics, paradigms and development environment useful for educational process as well as real life. First chapter contains theoretical concepts, teaching methods, paradigm analy- sis. Second chapter briefly describes graphical representation of algorithms. Third chapter begins with language comparison methodics and then compares selected lan- guages with description. Next chapter compares development environments, both used in real work and specialized on teaching purposes. Last part brings teaching materials for programming course on high school, in or- der to support teaching Java and object oriented programming/modeling in objects- first way. This thesis is written in Czech language. Klı´cˇova´slova vy´uka programova´nı´, programovacı´jazyky, didaktika informatiky, strˇednı´sˇkoly, IDE, teaching programming, high school, paradigms vi Obsah 0 U´ vod .........................................1 1 Teoreticky´za´klad ..................................3 1.1 Koho budu ucˇit .................................3 1.2 Forma vy´uky ..................................5 1.3 Co a procˇbudu ucˇit ...............................6 1.4 Paradigmata ...................................8 1.4.1 Funkciona´lnı´.............................8 1.4.2 Logicke´.................................9 1.4.3 Imperativnı´strukturovane´.....................9 1.4.4 Objektoveˇorientovane´........................ 10 1.4.5 Uda´lostmi rˇı´zene´........................... 11 1.4.6 Multiparadigmaticke´jazyky.................... 11 1.5 Zarˇazenı´paradigmat do vy´uky ......................... 12 1.6 Jak budu ucˇit – obecna´metodika ........................ 14 2 Graficky´popis algoritmu˚ ............................. 21 2.1 Vy´vojove´diagramy ............................... 21 2.2 Kopenogram ................................... 24 2.3 Nassi-Shneidermannu˚v diagram ........................ 26 2.4 UML ...................................... 26 3 Jazyky ........................................ 35 3.1 Metodika volby jazyka ............................. 35 3.1.1 Kriteria hodnocenı´jazyku˚...................... 36 3.2 Prˇehled vybrany´ch jazyku˚ ........................... 39 3.2.1 Pascal................................. 39 3.2.2 C.................................... 41 3.2.3 C++................................... 42 3.2.4 C# (.NET)............................... 44 3.2.5 Visual Basic.............................. 45 3.2.6 Java................................... 46 3.2.7 PHP.................................. 48 3.2.8 JavaScript (resp. ECMAScript)................... 50 3.2.9 Perl................................... 51 3.2.10 Python................................. 53 3.2.11 Ruby.................................. 54 3.2.12 Karel.................................. 56 vii 4 Vy´vojova´a vy´ukova´prostrˇedı´ .......................... 57 4.1 Robot Karel ................................... 57 4.2 Lego Mindstorms ................................ 58 4.3 Arduino ..................................... 59 4.4 Baltı´k ...................................... 59 4.5 Scratch ..................................... 61 4.6 Alice 3D ..................................... 61 4.7 BlueJ ....................................... 62 4.8 Greenfoot .................................... 62 4.9 Dev-C++ .................................... 63 4.10 MS Visual Studio Express ........................... 63 4.11 Netbeans .................................... 64 5 Prˇı´pravypro semina´rˇprogramova´nı´ ....................... 65 1. lekce – Terminologie a algoritmizace...................... 66 2. lekce – Algoritmizace.............................. 70 3. lekce – Za´klady OOP............................... 75 4. lekce – Atributy a datove´typy......................... 77 5. lekce – Metody, API Greenfootu........................ 78 6. lekce – Podmı´nky a vy´jimky.......................... 79 7. lekce – Cykly................................... 80 8. lekce – Procvicˇova´nı´............................... 81 9. lekce – Testy a TDD, BlueJ............................ 82 10. a 11. lekce – Pole, kolekce, itera´tory...................... 83 12. lekce – Souborovy´vstup/vy´stup....................... 84 Dalsˇı´navrhovane´lekce............................... 85 6 Shrnutı´ ........................................ 89 viii Kapitola 0 U´ vod Jizˇneˇkolik let docha´zı´ke zmeˇna´m v prˇı´stupu k vy´uce programova´nı´na vysoky´ch sˇkola´ch, byt’v Cˇeske´republice k tomu docha´zı´s mı´rny´m zpozˇdeˇnı´m vu˚cˇi za´padnı´mu sveˇtu. Meˇnı´ se nabı´dka programovacı´ch jazyku˚ i metody vy´uky, zacˇı´na´ se kla´st du˚raz i na ru˚zne´ metodiky vy´voje software, nejen na pouhou znalost syntaxe a se´mantiky konkre´tnı´ho jazyka, neˇktere´jazyky se opousˇtı´(jazyk symbolicky´ch adres – neprˇesneˇnazy´vany´assembler), jine´se dosta´vajı´do poprˇedı´za´jmu a dalsˇı´se teprve prosazujı´(naprˇ. Ruby). Podobneˇdocha´zı´k diskusı´m a postupne´mu vy´voji i ve vy´uce informatiky na strˇednı´ch sˇkola´ch, v soucˇasne´dobeˇprˇedevsˇı´m dı´ky sta´tnı´maturiteˇ. Prˇesto na mnohy´ch strˇednı´ch sˇkola´ch v Cˇeske´republice se programova´nı´sta´le ucˇı´ stary´mi metodami a v „osveˇdcˇeny´ch“ jazycı´ch jako je Pascal nebo VisualBasic. Zmeˇna veˇtsˇinou za´visı´na samotny´ch vyucˇujı´cı´ch informatiky,protozˇe zavedenı´m RVP 1 dosˇlo k prˇevedenı´zodpoveˇdnosti za volbu na´plneˇvy´uky na sˇkoly. Nemalou roli ve volbeˇprogramovacı´ho jazyka pro vy´uku hraje jisteˇi setrvacˇnost vyucˇujı´cı´ch a prˇedevsˇı´m absence mozˇnosti efektivnı´cestou se novy´jazyk naucˇit. Pro mnohe´je ota´zkou „Ktery´je ten spra´vny´?“, protozˇe neexistuje v cˇesˇtineˇdostupne´shrnutı´dnes pouzˇı´vany´ch jazyku˚a jejich vhodnosti. Ve zmeˇti knih ru˚zny´ch u´rovnı´na´rocˇnosti, kvality a cı´love´skupiny cˇtena´rˇu˚se lze teˇzˇko orientovat. Acˇkoliv Ra´mcovy´vzdeˇla´vacı´program pro gymna´zia [2, str. 63] deklaruje vy´chovu zˇa´ku˚k algoritmicke´mu mysˇlenı´, vyucˇujı´cı´postra´dajı´ucˇebnice a metodiku, ktera´by takovou abstraktnı´proklamaci aplikovala do prakticke´vy´uky. Lepsˇı´situace nenı´ ani prˇi vy´beˇru ucˇebnic. Nabı´dka je sice sˇiroka´, ale pomeˇrneˇma´lo knih je vhodny´ch jako ucˇebnice pro strˇednı´sˇkoly – veˇtsˇinu z nich lze doporucˇit spı´sˇe jako doplneˇk vy´uky pro samostudium. Pedagogicka´opora ve formeˇsbı´rek prˇı´kladu˚k procvicˇenı´ opeˇt neexistuje, stare´sbı´rky veˇtsˇinou nelze pouzˇı´t, protozˇe obsahujı´prˇeva´zˇneˇu´lohy matematicke´, ktere´ dnesˇnı´ zˇa´ky nemotivujı´ a svy´m zameˇrˇenı´m na strukturovane´ paradigma se nehodı´prˇi vy´uce objektove´ho programova´nı´. V te´to diplomove´pra´ci si kladu za cı´l jednak analyzovat nabı´dku programovacı´ch a skriptovacı´ch jazyku˚z hlediska jejich vhodnosti pro vy´uku programova´nı´, ale take´ prˇehledneˇprˇine´st na´vrhy k alternativnı´m forma´m vy´uky programova´nı´a algoritmi- zace prˇedevsˇı´m v prostrˇedı´strˇednı´ch sˇkol, respektive na vysˇsˇı´m stupni za´kladnı´ch sˇkol. V pra´ci se pokusı´m zohlednit te´meˇrˇtrˇı´letou praxi ve vy´uce strukturovane´ho 1. RVP – Ra´mcovy´vzdeˇla´vacı´program, popisuje pouze obecna´te´mata a vı´ceme´neˇabstraktnı´cı´love´ dovednosti (tzv. klı´cˇove´kompetence) na rozdı´l od drˇı´ve pouzˇı´vany´ch pomeˇrneˇkonkre´tnı´ch osnov. To umozˇnˇuje sˇkola´m prˇizpu˚sobit svu˚j SˇVP – sˇkolnı´vzdeˇla´vacı´program – a odlisˇit se od jiny´ch sˇkol. 1 0. U´ VOD programova´nı´v jazyce C na gymna´ziu a ra´d bych touto pracı´prˇispeˇl k sˇirsˇı´diskusi a zmeˇneˇ, jaka´probeˇhla naprˇ. v Neˇmecku [6]. Pocˇı´tacˇova´gramotnost ve smyslu schopnosti ovla´dat pocˇı´tacˇv beˇzˇny´ch zˇivotnı´ch situacı´ch informacˇnı´spolecˇnosti jako je komunikace prˇes internet, vyhleda´va´nı´infor- macı´nebo jejich zpracova´nı´v ru˚zny´ch programech, je pro dnesˇnı´mla´dezˇnaprostou nezbytnostı´a jako takovou ji lze srovna´vat s prima´rnı´gramotnostı´. Je pravdeˇpo- dobneˇ jen ota´zkou cˇasu, kdy vy´uka vyhleda´va´nı´ na internetu nebo typografie a psanı´v textovy´ch procesorech prˇejde
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    What's New in the LLVM Compiler Session 402 Evan Cheng Sr. Manager, Compilation Technologies These are confidential sessions—please refrain from streaming, blogging, or taking pictures Focused on Providing Best-in-Class Tools Focused on Providing Best-in-Class Tools Support for latest hardware Focused on Providing Best-in-Class Tools Support for latest hardware Improving performance Focused on Providing Best-in-Class Tools Support for latest hardware Improving performance Improving developer productivity Support for Latest Hardware armv7s Architecture • Architecture for Apple A6 processor ■ iPhone 5 and new iPads • Extensive tuning and optimization in the compiler ■ Uses instructions only available in armv7s armv7s Architecture • Architecture for Apple A6 processor ■ iPhone 5 and new iPads • Extensive tuning and optimization in the compiler ■ Uses instructions only available in armv7s Important for achieving max performance! armv7s Architecture • Already part of the standard architectures for iOS apps Intel AVX • 256-bit floating-point vector computation ■ Twice as wide as SSE vectors ■ Supported in Sandy Bridge and Ivy Bridge processors • Good for loops with operations that can be performed in parallel ■ Floating-point intensive ■ High ratio of computation to memory bandwidth Intel AVX2 • Supported in “Haswell” processors ■ Extend the AVX instruction set to integers ■ Adds fused multiply-accumulate for increased floating point throughput ■ More extensive set of vector shuffle instructions Using AVX2 with Fallback to AVX / SSE • Check
  • Advanced Wxpython Nuts and Bolts Robin Dunn O'reilly Open

    Advanced Wxpython Nuts and Bolts Robin Dunn O'reilly Open

    Advanced wxPython Nuts and Bolts Robin Dunn Software Craftsman O’Reilly Open Source Convention July 21–25, 2008 Slides available at http://wxPython.org/OSCON2008/ wxPython: Cross Platform GUI Toolkit 1 Presentation Overview • Introduction • Widget Inspection Tool • wx.ListCtrl • Keeping the UI Updated • Virtual wx.ListCtrl • Sizers and more sizers • wx.TreeCtrl • XML based resource system • wx.gizmos.TreeListCtrl • Data transfer • CustomTreeCtrl – data objects • wx.grid.Grid – clipboard • ScrolledPanel – drag and drop • wx.HtmlWindow • Creating custom widgets • Double buffered drawing wxPython: Cross Platform GUI Toolkit 2 Introduction to wxPython • wxPython is a GUI toolkit for Python, built upon the wxWidgets C++ toolkit. (See http://wxWidgets.org/) – Cross platform: Windows, Linux, Unix, OS X. – Uses native widgets/controls, plus many platform independent widgets. • Mature, well established projects. – wxWidgets: 1992 – wxPython: 1996 wxPython: Cross Platform GUI Toolkit 3 Introduction: architecture wxPython Library Proxy classes wxPython Extension Modules wxWidgets Toolkit Platform GUI Operating System wxPython: Cross Platform GUI Toolkit 4 Introduction: partial class hierarchy wx.Object wx.EvtHandler wx.Window wx.TopLevelWindow wx.Panel wx.Control wx.Frame wx.Dialog wx.ScrolledWindow wxPython: Cross Platform GUI Toolkit 5 wx.ListCtrl • Presents a list of items with one of several possible views – List – Report – Icon • Supports various attributes and operations on the list data – Icons, and colors – Sorting – multiple selection •
  • Raritas: a Program for Counting High Diversity Categorical Data with Highly Unequal Abundances

    Raritas: a Program for Counting High Diversity Categorical Data with Highly Unequal Abundances

    Raritas: a program for counting high diversity categorical data with highly unequal abundances David B. Lazarus1, Johan Renaudie1, Dorina Lenz2, Patrick Diver3 and Jens Klump4 1 Museum für Naturkunde, Berlin, Germany 2 Leibniz-Institut für Zoo- und Wildtierforschung, Berlin, Germany 3 Divdat Consulting, Wesley, AR, USA 4 CSIRO, Mineral Resources, Kensington, NSW, Australia ABSTRACT Acquiring data on the occurrences of many types of difficult to identify objects are often still made by human observation, for example, in biodiversity and paleontologic research. Existing computer counting programs used to record such data have various limitations, including inflexibility and cost. We describe a new open-source program for this purpose—Raritas. Raritas is written in Python and can be run as a standalone app for recent versions of either MacOS or Windows, or from the command line as easily customized source code. The program explicitly supports a rare category count mode which makes it easier to collect quantitative data on rare categories, for example, rare species which are important in biodiversity surveys. Lastly, we describe the file format used by Raritas and propose it as a standard for storing geologic biodiversity data. ‘Stratigraphic occurrence data’ file format combines extensive sample metadata and a flexible structure for recording occurrence data of species or other categories in a series of samples. Subjects Biodiversity, Bioinformatics, Ecology, Paleontology Keywords Software, Point-counting, Rarity, Data standards, Micropaleontology, Biostratigraphy, Submitted 5 April 2018 Biodiversity, Ecology, Python, Range chart Accepted 26 July 2018 Published 9 October 2018 Corresponding author INTRODUCTION David B. Lazarus, Human observations as a source of scientific data [email protected] Quantitative data about many aspects of the natural world are collected in modern Academic editor Donald Baird science with the use of instruments, but a substantial amount of observational data is still Additional Information and collected by human observation.