Pasifika C++

75 Pages·2017·2.14 MB·English

Pasifika C++
AIDANDELANEY,ALLENB.DOWNEY,NARENDRASISODIYA,
TIRTHAP.CHATTERJEE
PasifikaC++
AidanDelaney,AllenB.Downey,NarendraSisodiya,TirthaP.Chatterjee 2
Contents
1 WhyStudyComputing? 7
1.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.3 WhatisProgramming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.3.1 Formalisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.4 WhatcanComputersDo? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.5 WhatComputersCan’tDo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.6 WhyC++ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.7 Whatwecandonow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2 HelloWorld 17
2.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2 TheConsole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.3 FirstProgram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.3.1 AStylisticNoteonWhitespace. . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.4 Whatwecannowdo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3 intandOtherTypes 23
3.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2 SimpleTypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.3 TypeErrors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.4 StorageBoxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.5 Whatwecannowdo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4 Functions 27
4.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.2 SimpleFunctions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.3 Signaturebeforeuse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4.4 MultipleParameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.5 TestingFunctions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
4.5.1 TestHarness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
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4.6 voidreturn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.7 Whatwecannowdo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5 InputandOutput 33
5.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.2 Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.3 Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.4 TestingInput . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.5 Whatwecannowdo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
6 BranchingComputation 39
6.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
6.2 StaticStructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
6.3 TracingExecution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
6.4 Conditionalexecution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
6.5 Alternativeexecution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
6.6 Whatwecannowdo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
7 Iteration 47
7.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
7.2 Multipleassignment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
7.3 Iteration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
7.3.1 Thewhilestatement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
7.4 forloops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
7.5 Whatwecannowdo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
8 Lists 55
8.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
8.2 Avector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
8.3 Accessingelements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
8.4 BetterIteration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
8.5 Copyingvectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
8.6 Vectorsize. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
8.7 Vectorfunctions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
8.8 Whatwecannowdo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
8.9 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
8.10 Determinsm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
8.11 Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
8.11.1 Vectorofrandomnumbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
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8.11.2 Counting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
8.11.3 Checkingtheothervalues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
8.11.4 Ahistogram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
8.11.5 Asingle-passsolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
8.12 Randomseeds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
8.13 Whatwecandonow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
9 Provenance 69
9.1 Licence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
9.2 GNUGENERALPUBLICLICENSE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
9.2.1 Preamble . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
9.2.2 TERMSANDCONDITIONSFORCOPYING,DISTRIBUTIONANDMODIFICATION . 70
9.2.3 NOWARRANTY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
10 PacifikaC++ 75
10.1 Building . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
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1 Why Study Computing?
1.1 Objective
Inthischapterwemotivatewhywestudycomputerprogramming.
1.2 Background
Therearealotofinterestingthingsoutthereintheworld. Youcouldlearnaboutmagicalrealism
inliteraturefromBorges’writingsthroughtoDelToro’sexcellentmoviePan’sLabyrinth.Ormaybe
you’reinterestedinhowEinstein’stheoriesofrelativityledtoQuantumMechanics. Amidstallof
theseinterestingtopicswhychoosetostudycomputerprogramming?Ihavemultiple,andsometimes
contradictoryviews,onwhyIlikeprogramming.It’sessentiallyreductionist,todoitcorrectlyrequires
greatsocialskillsanditrepresentsabout50%ofmydailyuniverse.I’llexplaineachoftheseclaimsin
turn.
Computerprogrammingisreductionist.Westudyaproblemandreducetheproblemtoit’sbarebones.
Asanexample,wereduceeverythingtonumbers–wecan’trepresentthedepthandbreadthhow
muchyoumightloveapet,butwecanrepresentitonascalefrom0to100!Afterreducingtheproblem,
wethenproduceacomputerprogramthatsolvestheproblemfromverybasiccomponents.Eachtime
youwriteaprogramit’slikewalkingintoaworkshopcontainingabunchofsteelpipesandafurnace
andbeingtoldthatyouhavetobuildamotorbike.Wegenerallylookaproblemsfromthebottom-up;
howcanwesolvetheproblemwiththesmallnumberofcomponentsthatareavailabletous.
Bycontrast,thepeoplewhowantustowriteprograms–employers,family,friendsandwidersociety
– look at things from a top-down perspective. They need to automate some systems in order to
solveareal-worldproblem. Youremployermightwantaprogramtocalculatetheirannualtaxbill,
andthenautomaticallytransferthetaxpaymentdirectlytothetaxauthorities1.Theperspectivesof
suchstakeholdersisalmosttheoppositeofreductionist.Itrequiresthinkingaboutanentiresystem.
Moreoversolvingreal-worldproblemsdevelopsexcellentcommunicationskillsinordertoteaseout
therealissuesthestakeholderwantstosolve.OftenstakeholdersaskforaprogramtodoXwhenthey
1Thisdoesn’tapplyinVanuatuasthereisnoincometaxorcorporationtax,buttheyarebeingintroducedinthenearfuture.
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reallywanttosolveproblemY.Programmershavetheirownlanguagefordescribingsuchthings.We
callittheXYProblem.
Sofarwe’veconsideredareductionistbottom-upreasontostudyprogramming.We’vealsobriefly
discussedhowyoualsohowprogrammingcanhelpyoutodevelopgreatcommunicationskills.My
thirdreasonforstudyingprogrammingisanargumentmadebySimonPeytonJones.Hearguesthat
inthe20thCenturyweintroducedthenaturalsciencesintoschools–thatisphysics,chemistryand
biology–sothatalladultswouldhaveagoodunderstandingofthephysicalworldinwhichwelive.In
the21stCenturywelivemuchofourdayoutsidethephysicalworldandinsidethevirtualworld2.Many
ofourrelationshipsaremediatedbysocialnetworks–IhavegoodfriendswhoI’veneverseen.Other
simplethingsinlifearealsodigital,banktransferscanbeorganisedthroughawebbrowserandavoid
standinginlineinaphysicalbank.Therearegrowingtrendswhereweusesoftwaretosolvetransport
issues,negatingthereasonstocoughup$14konasecond-handToyota.Thevirtualworldhassucha
hugeimpactonourreal-worldthatitisusefultostudyprogrammingsothatwecanunderstandthe
buildingblocksofthevirtualworld.
Sotherearethreereasonstostudyprogramming;thefirstbecauseit’sabigboxoflegofromwhich
youcanbuildreallyinterestingthings,thesecondbecauseitsolvesinteresting(andnotsointeresting)
real-worldproblemsthatrequirealotofcommunicationandthethirdreasonisbecauseitgiveyoua
goodunderstandingofthevirtualuniverseinwhichwespendmuchofourdailylife.
1.3 WhatisProgramming
Ifyou’restillreadingyou’reeitherconvincedbyoneofmythreereasonsforstudyingprogrammingor
youneedthecoursecreditgivenbypassingaprogrammingclass.Hopefullyit’stheformerasintrinsic
motivationismorelikelytodriveyoutosuccessthanextrinsicmotivation.Inbothcasesyouknowwhy
you’restudyingprogramming,thequestionnowbecomes“whatisprogramming?”.
Inoneview,aprogramisanunambiguouslistofinstructions.Eachtimeyoufollowthelistofinstruc-
tions,youwillachievethesameresult.Thecomparisonisoftenmadewithcooking,whererecipesare
oftensharedasalistofinstructions.Takeforexampletheinstructionsformakingachickenlovoor
umu.Inthecaseoflovoyoumightgettheinstructionsto:
1. Digapit,
2. Buildafire,
3. Carefullyplacelavarocksoverthefire,
4. Lightthefireandletitburndowntoembers,
5. Seasonthechicken,
2Ifyoudon’tbelievemeonthis,thenhavealookaroundandseehowmanystudentsthinkIcan’tseethemtextingundera
deskinyournextclass.
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6. Wrapthechickeninbananaleaves,
7. Putthewrappedchickenonthehotstones,
8. Coverthefoodwithearth
9. Wait2hours,removechickenandeat!
Tomostpeople,theaboveinstructionsareenoughtomakeagreatdinner.Howevertheseinstructions
areambiguous. Theydon’tsayhowdeeporwidetobuildthepit. Theydon’tsayhowhighthefire
shouldbewithinthepit.Howlargeshouldthelavarocksbe?Orwhatdoweseasonthechickenwith?
Moreover,ifyou’veevermadealovoorumuyouknowit’salotofeffort.Toomuchefforttocooka
singlechickensomaybeweshouldalsoplacetaroandfishalongsidethechicken.Thereasonthatthe
instructionscanbeambiguousisbecauseyou,dearreader,areintelligentenoughtofillintheblanks.
Computers,ofcourse,arenotintelligent. Theycannotfillinanyblanksinanexplanation. Sowe
needtopresentthemwithalistofinstructionswritteninanunambiguouslanguage.Theprocessof
producingunambiguousexplanationsiscalledproof bymathematicians,butwe’llcallitprogramming.
1.3.1 Formalisation
Inordertoremoveambiguityfromtheinterpretationofsentenceswe’regoingtoabandontheuse
ofnaturallanguage.Wewon’ttrytowriteourinstructionsinEnglish,FrenchorBislama.Theseare
fantasticlanguagesinwhichtoexpressloveorrevolution.However,theveryfactthattheselanguages
allowustoexpressanddiscusspoorlydefinedconceptsistheveryreasonthattheyareunsuitablefor
providingunambiguousinstructionstoamachine.Toprogramacomputerweneedaformallanguage,
oneinwhicheachwordandsentencehasawell-definedmeaning.
Bywritinginstructionsinaformallanguageweremoveambiguityfromtheinstructions. It’salso
importanttonotethatwealsoloosesomethingintranslation.Abunchofinstructionsthatdescribe
makingatraditionallovocanbereadandunderstoodbyanyliterateperson.Lovoinstructionswritten
inanunambiguouslanguagearelikelytobeverydifficulttoread.InordertoillustratethisIneedto
introduceaproblemthatismuchmorestraightforwardthanmakingalovo.Let’sconsiderthekids
gamehangman.
Thegamehangmanisplayedbykidsinschoolsallovertheworld.Onestudentchoosesasecretword
andwritesanumberofdashesonapieceofpaper. Thereisonedashforeachletterofthesecret
word.Thesamepersonalsodrawsagallows3.Afriendthenguesseslettersofthesecretword.Ifthey
correctlyguessaletterofthewordthentheletteriswrittenonadashinanappropriateposition.If
theydonotguesscorrectlythenabitofastickmanisdrawnhungonthegallows.Thefriendwinsthe
gameiftheycorrectlyrevealallthelettersofthewordbeforethefullstickmanisdrawnonthepage.
3Thenamehangmananddrawingagallowsareprettyawful,butthenagainmostkidsareawful!
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Ourpreviousparagraphisareasonableexplanationofthegame.Again,likeourlovoexample,you’re
probablyabletofillinthebitswhereI’veexplaineditpoorly.Whatifwehadtowritetheinstructionsof
thegameinawaythattheycouldn’tbemisinterpreted?Legalpeoplecommonlywritesuchinstructions:
Thegameofhangman,hereinreferredtoasTHEGAME,isagamefortwopartiesreferredto
asTHEPLAYERandTHEJUDGE.
(a) THEJUDGEwilldrawonpaperagallowsandbelowthegallowsaseriesofdasheswhere
thereisonedashforeachletterofasecretword.
• THEJUDGEwillnotprima-faciarevealthesecretwordtoTHEPLAYER
(b) THEPLAYERwillguessaletterofthesecretwordand
• iftheguessedletterisoneormorelettersinthesecretword,thenTHEJUDGEwrites
theguessedlettersontopofadashthatisatthesamepositionintheseriesasthe
guessedletterinthesecretword.
• otherwiseTHEJUDGEwilldrawthenextbodypartofastickmanonthegallows.
(c) thebodypartsofastickmanaredrawninprogression,onperturn,startingwithahead,
abody,aleftleg,arightleg,aleftarmandarightarm.
(d) THEJUDGEwinsthegameifthestickmanisdrawnbeforethesecretwordisrevealed.
Thelegalcodeforhangmanisusefulwhentwoplayersneedtoargueabouttheimplementationofa
rule.Wecanstillargueabouttheinterpretationofsomeoftherules;shouldthejudgedrawthearmas
anupperarmandlowerarm? Cantheplayerguesstwolettersatatime?4 Inourcasewewantour
ruletobeinterpretedbyamachinethatcan’targueabouthowtoimplementarule. Weknowour
machineshavenointelligence.Theycansimplyreplacesymbolswithothersymbols
Hopefullyyounowagreethatournaturallanguages,evenwhenrestrictedtolegallanguage,arenot
preciseenoughtoinstructadumbcomputer.Weneedlanguagesthatareun-natural.Weneedformal
languagesthataresuitedtodescribinghowtomanipulatesymbolsand“move”symbolsaround.Such
alanguageisgoingtobedifficulttoreadbecauseofitslackofexpressiveness. Itdoesn’thavethe
expressivebandwidthofanaturallanguage.
Inamoreformallanguagedesignedforcomputation–aprogramminglanguage–wehavetowritea
lotofinstructionstodescribehangman.Theinstructionsmightlooksomethinglike:
1 start program
2 run instructions to construct gallows
3 run instructions to input secret word
4 repeat run instructions to take a turn until the game is over
5 end program
4Asolicitorcouldwritetheserulesinadifferentway.Theycouldfirstformalisethedefinitionofaturnandthendescribe
theprogressofthegameasaseriesofturns.Inanycasetheformalisationintolegallanguageaddsmorecomplexity
thantheinformalexplanation.
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