algorithms, computer systems, and programming...

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Algorithms, Computer Systems,andProgramming Languages

CSC121,IntroductiontoComputerProgramming

overview

• whatisacomputational process?• whatisanalgorithm?• whatisacomputer?• briefoverviewofcomputer organization• computer processingasadiscrete statemachine• assemblylanguageprogramming• high-level languageprogramming• thelandscapeofcomputational problems

ComputationalProcesses

• acomputational process denotes acollectionofrules, orasequence ofoperations ortransformations whereby some resultinginformation isderived from asetofinitial orgiven information and conditions.

Algorithm

• analgorithm isaplanfordirecting acomputational process.

• algorithms shouldsatisfytheseconditions– eachofthestepsmustbeclearly andpreciselydefined.

– eachstepmustbeeffective (fortheagentexecuting theprocess)

– thestepsmustbeorderedproperly– theprocessmustterminate atsomepoint

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Devising anAlgorithm

• Creating analgorithm isaprocess that involvesthese considerations:a) what istheresult?(specifications forthetask,

process, answer,orproduct)b) what doIknow?(information thatisgivenor

input intothecomputational process)c) howdoIderive(a)from(b)?(modifications,

transformations, stepsrequired toproduce(a))

ComputerSystems (1)

• electronic• digital• programmable• automated

Today’s generationofcomputersystemsareautomated, programmable, electronicdigitalprocessingmachines.

ComputerSystems (2)

• data—symbolic representation ofinformation• process—asequence ofstatesduringwhichthedataaremodified inprescribed ways

• program—a setofinstructionsthatdirect theprocess

Acomputersystemisanelectronicdigital dataprocessingmachine.

ComputerSystems (3)

• software—programs– program—a setofinstructionsthatdirectaprocess

• hardware—devices thatmakeupthephysicalsystemofthecomputer

Acomputersystemiscomprisedbysoftware thatdirects theprocessingperformed byhardware.

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Hardware

• Hardware denotes the devices that comprisethe computer system

Hardware

• processor– CPU– mainmemory

• secondary memory and I/Osubsystem– auxiliary memory– input/outputdevices

ProcessorSystem

main memorystoresbothdataandinstructionsusedforprocessing

centralprocessingunit:manages theinstruction-executioncycle

bus providesinterconnections

Instruction-ExecutionCycle

• fetching thenextinstruction

• decoding (orinterpreting) thatinstruction

• executingwhat theinstructionprescribes

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Memory

• information (data) isstored inuniform-sizedunits

• each unit hasaunique address that identifies it• reading frommemory– copy data fromamemory location– non-destructive

• writing tomemory– moving and replacing data inamemory location– destructive

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Secondary Memoryand I/O

• Secondary memory– nonvolatile storage– cheaper, mass storage

• Input/Output devices– input--translateshuman-readable formsofinformation tomachine-readable data

– output-- translates machine-readable data tohuman-readable forms

DiscreteStateMachine

Digitalcomputers...maybeclassifiedamongstthe'discretestatemachines.’Thesearethemachineswhichmovebysuddenjumpsorclicks fromonequitedefinitestatetoanother.Thesestatesaresufficientlydifferentforthepossibilityofconfusion betweenthemtobeignored.

Turing, “ComputingMachineryandIntelligence”(1951)

CapturingaDiscreteState

• thecurrentvaluesofanydata objectsspecified fortheprocess

• thestatus oftheprocessor– temporary valuesandflags storedthere

• thestatusofinputandoutputoperations• theaddressofthenextexecutableinstruction intheprogram

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Software

• computer programsarecommonlycalledsoftware

• eachmachine instruction inaprogramtypicallycorresponds toatypeofoperation thatthecomputer’s processor canperform

• thesetofpossibleprocessor ormachineinstructions iscalledtheprocessor ormachinelanguage

AssemblyLanguage Programming

• assemblylanguageprogramscontainsymbolicinstructionsrepresentingelementsofsomemachinelanguageinstruction

• eachinstructiontypicallyhas– amnemonicfortheoperationcode

– literalsorlabelsfortheoperands


• Someoperandsare literals– e.g.,

ADD3[ACCß ACC+3]whereACCdenotestheAccumulator

• Someoperandsare labels signifying indirection(indirectcodes)– e.g.,

ADDLOC1024[ACCß ACC+value(LOC1024)]


• constants. literalsorvalues thatmaychangefromtime totime, butare fixedorstaticforthecurrentexecutionoftheprogram

• variables. thesedenote values thatare dynamic,that is,maychange inthecourseofprocessing

• pointers (handles). thesedenotevalues thataretheaddressofother locationscontainingvalues

Labelsmayfunctionas…

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Assignments

• Putting adata valueinto memory iscalled(algorithmica lly) anassignment

• InPython (and most programming languages),it iswritten inthis form

ACCß 3

name =valuewhere name isasymboliclabel andvalue expressessomedatavalue

ConditionalProcessing

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isthecapability oftheprocessortochoosebetweenalternative actionsbasedonevaluating currentdata


• unconditional branch (jump)—change theaddressofthenext instructiontotheoneindicated inthebranchinstruction

• conditional branch (jump)—if someconditionistrue, thenchange theaddressofthenextinstructiontotheone indicated inthebranchinstruction

…ismadepossible atthe processorlevelbybranchinstructions


…ismadepossibleattheprocessor levelbybranchinstructions

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Subroutines

library program unitsthatcanbelinkedwiththemain program


AssemblyProcess Review: Assembly Language Programming

• instructions havealow-level ofabstractionbecausetheymodeltheactualoperationsofthenativeprocessor

• instructions represent(nearly)a1–1relationwiththoseofthecorresponding machinelanguage

• assemblylanguageprogramsarenot portable• assemblylanguagesareconsidered low-levelprogramminglanguages

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High-Level Programming Languages

• High-LevelLanguage(HLL)instructions aremoreabstract– HLL instructionsexpresshigher-orderoperations

• singleHLLinstructions substituteforasequenceoflow-levelmachinelanguageinstructions. Inshort, thereisa1–manyrelation betweenHLLinstructions andmachinelanguageinstructions

• HLLprogramsareportable tootherprocessors– providedasuitablemeans oftranslation

Advantages ofHigh-LevelProgramming Languages

• programmerisrelievedofmanyimplementation details inperformingtasks

• HLLsaredesignedtobemorecompatiblewith thewaywethink andsolveproblems

• HLLprogramscanbeadaptedmoreeasilyforavarietyofcomputersystemsandmodifiedmoreeasily fordifferentfunctions

• HLLprogramsaremoreconcise

Translating HLLPrograms

• interpreters—decodeandexecuteprogramsoneinstruction atatime– translationonthe fly– emulates theway theprocessorfunctions

• compilers—analyzeandtranslate theentire HLLsourceprogramtoproduce anexecutablemachinelanguageversion– likeaprepared text translation

ComputationalProblems: TheLandscape

• Somecomputational problemshavesolutions,butthesesolutionscannotbecomputedeffectivelybecausewe lackthepracticalmeans todoso– someproblemsmaybesolvablewhenwehavefasterprocessorsorgreatermemorycapacities

– forothers,wewillneverhavetheresourcestoeffectivelycompute themwithcurrentsolutionsoralgorithms

• Example: thetraveling salespersonproblem

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• Thebrute-forcesolutionforthe traveling salespersonproblem(TSP)hasafactorialgrowth rate

• Computer scientistsoftendescribe thebehaviorofalgorithmsusinganotationcalled“BigO”– thisdenotestheupperboundfor theworst-caseperformance ofanalgorithm

– TSP=O(N!),forN cities(ornodes)


• Supposethatwehadhardware thatwascapableofanalyzingonemillion individualpathsortripspersecond.– N =10 solution<4seconds– N =100 solution=approximately1049 centuries

• Problemswithalgorithms like forTSParesaidtobeintractable


• there isanotherclassofproblems thatare notsolvable

• example:The HaltingProblem– Supposethatwecreatedaprogram thatcouldanalyzeanyotherprogram.

– Specifically,analyzeaninputprogramwithaspecificsetofinputdata

– Ourprogrammustbeabletodeterminewhethertheinputprogramwillhalt—i.e.,completeitstask

– Aneffectivesolutionhastwopossibilities:“Yes”,theinputprogram terminates or“No”, theinputprogram neverterminatesorhalts


• AlanTuringdemonstratedthattheHaltingProblemwasunsolvablein1936

• headedthegroupatBletchleyParkthatcrackedtheEnigmaMachine inWWII

• developedtheACE computerin1946

• introducedwhatisnowcalledthe“TuringTest”todeterminewhetheramachinecouldbeconsidered intelligent

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Computational Problems: TheLandscape

• undecidable problems: problems forwhichthere canbenoeffectivealgorithm

• intractable problems: theseare decidablebuthavenopracticalalgorithmic solutions

• tractable problems: thesearebothdecidable andhavealgorithms thatare orwouldbepractical toimplement

review

• whatisacomputational process?• whatisanalgorithm?• whatisacomputer?• briefoverviewofcomputer organization• computer processingasadiscrete statemachine• assemblylanguageprogramming• high-level languageprogramming• thelandscapeofcomputational problems

algorithms, computer systems, and programming...

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