Table Of ContentTheComputerJournal,47(3),©TheBritishComputerSociety;allrightsreserved
A System for Measuring Function
Points from an ER–DFD Specification
EvelinaLamma1,PaolaMello2 andFabrizioRiguzzi1
1DipartimentodiIngegneria,UniversitàdiFerrara,viaSaragat,144100Ferrara,Italy
2DEIS—UniversitàdiBologna,VialeRisorgimento,240136Bologna,Italy
Email: {elamma,friguzzi}@ing.unife.it,[email protected]
WepresentatoolformeasuringtheFunctionPoint(FP)softwaremetricfromthespecificationof
asoftwaresystemexpressedintheformofanEntityRelationship(ER)diagramplusaDataFlow
Diagram(DFD).First,theinformalandgeneralFPcountingrulesaretranslatedintorigorousrules
expressing properties of the ER–DFD. Then, the rigorous rules are translated into Prolog. The
measuresgivenbythesystemonanumberofcasestudiesareinaccordancewiththoseofhuman
experts.
Received16January2003;revised15October2003
1. INTRODUCTION Relationship(ER)diagramplusaDataFlowDiagram(DFD).
ThesystemiscalledaFUNctionpointmeasurement(FUN)
Software metrics are emerging as a powerful tool for the
andapreliminaryversionofitappearedin[10].
managementofthesoftwaredevelopmentprocess. Software
In order to develop the system, the informal IFPUG
metrics allow the application of engineering principles to
counting rules are specialized for the case of ER–DFD and
softwaredevelopment,providingaquantitativeandobjective
maderigorous. Toachievethisaim,anumberofassumptions
baseforprocessandtechnologydecisions.
weremade. Theinformalcountingrulesexpressedinnatural
Amongsoftwaremetrics,FunctionPoints(FPs)[1,2]give
languagein[3]havethusbeentranslatedintorigorousrules
a measure of the size of a software system by measuring
expressingpropertiesoftheER–DFDgraph. FUNhasbeen
the functionalities that the system offers the user. This
testedonsevendifferentcasestudieswhichobtainedresults
metricisapplicablebothatthebeginningofthedevelopment
veryclosetothoseofhumancounters.
process, in the requirements or specification phases, and
Thetoolisvaluableforthreereasons. First,itsaveshuman
at the end of the process, after implementation. The
effort. Second, it has been experimentally shown to be in
importance of FP lies in the fact that they can be used to
accordancewithhumancounters. Third,ifconsistentlyused
estimate the cost of a software development project given
inanorganizationoracrossorganizations,itovercomesthe
the requirements or specification because in Albrecht and
problemofdependencefromthecounter.
Gaffney[2]ithasbeenshownthatFParehighlycorrelated
withwork-hours. There exist in the market a number of commercial tools
The rules for counting FP are described in the Function thathelpthesoftwareengineerintheprocessofFPcounting
Point Counting Practices Manual [3], published by the though none of them is fully automatic [4]. To the best of
International Function Point User Group (IFPUG) [4]. our knowledge, the only tool that is capable of automati-
Recently, IFPUG FP counting rules have become the ISO callycountingFPisdescribedin[11]andwasdevelopedin
standardnumber20926[5]. academia. Suchasystemstartsfromaspecificationwritten
Recently,therehasbeenadebateabouttheuseofFP[6,7]. inUML.
The main problem with FP is that they are not completely FUN has been implemented in Sicstus Prolog ver-
independent from the person doing the count. Kemerer [8] sion 3#5 [12] and is available from http://www.ing.unife.it/
reported a 12% difference for the same product used by software/FUN/.
peopleinthesameorganization, whileLowandJeffery[9] The paper is organized as follows. In Section 2, we
reporteda30%variancewithinanorganizationandmorethan describetheFPmeasurementprocess. InSection3,werecall
30%acrossdifferentorganizations. Inordertoovercomethis ERandDFDspecificationsandpresenttheirintegrationinto
problem,Kitchenham[7]suggestedsimplifyingthecounting ER–DFDspecifications. Section4describestheapplication
rules so that FP can be automatically counted from early ofFPrulestoER–DFDandSection5illustratesthesystem
systemrepresentations. implementation in Prolog. Section 6 shows the application
Inthespiritofthesuggestionof[7],thispaperproposesa ofthesystemtoanumberofcasestudies. Relatedworksare
systemfortheautomaticcountingofFPfromaspecification discussedinSection7. Conclusionsanddiscussionoffuture
of the software expressed in the form of an Entity workfollowinSection8.
TheComputerJournal, Vol.47, No.3, 2004
ASystemforMeasuringFunctionPoints 359
2. FUNCTIONPOINTMEASUREMENTPROCESS is performed and that the boundary of the application is
indicated in the ER–DFD diagram. We do not automate
FP measurement rules are defined in the IFPUG Counting
Step(vi)becauseitrequiresmanynotionsontheapplication
Practices Manual [3]. The method is based on identifying
and the environment that are not present in the ER–
andcountingthefunctionsthatthesystemhastoprovide,i.e.
DFD specification and therefore are difficult to formalize.
InternalLogicalFiles(ILFs),ExternalInterfaceFiles(EIFs)
Moreover,manycompaniesprefertoconsideronlytheISO
(data functions), External Inputs (EIs), External Outputs
standardizedUFPcount.
(EOs) and External Inquiries (EQs) (transaction functions).
Eachfunctionidentifiedinthesystemisthenclassifiedinto
three levels of complexity (simple, average and complex), 3. ENTITYRELATIONSHIP—DATAFLOW
and an FP number is assigned to each function according DIAGRAMS
to its type and complexity. The rules for identifying the
Wewillperformthemeasurementonthespecificationofthe
functionsandfordeterminingtheircomplexityareexpressed
applicationexpressedbyanERdiagram[13]integratedwith
innaturallanguageandtheyrefertoanumberofhigh-level
a DFD [14]. We consider an integration of the diagrams
abstractionsdefinedinthemanual[3]. Ruleshavebeenkept
which is similar to Formal DFDs [15]: the data stores of
informalandabstractsothattheycanbeappliedtoanykindof
DFD are replaced by entities and relationships of the ER
descriptionofthesystem,fromarequirementdocumenttoan
diagrams; therefore, we have data flows entering directly
implementationofthesystem. However,asaconsequence,
into entities and relationships, and data flows coming out
they are, to a certain extent, vague and not completely free
from them. Moreover, we distinguish three types of data
fromambiguities.
flows: properdataflowsthatrepresenttheexchangeofdata;
The sum of the FP contributions from all the functions
error flows that represent the exchange of error messages
givestheunadjustedFPcount(UFP):
and control flows that represent the exchange of control
(cid:1) (cid:1)
UFP= w x information. We call such an integrated diagram an ER–
ij ij
DFD.InordertodistinguishbetweenelementsoftheDFD
i(cid:1) Typesj(cid:1) Complexity
and ER diagram, which have a similar graphical symbol,
where Types={ ILF, EIF, EI, EO, EQ} , Complexity= we adopt the following conventions: external agents (the
{ simple, average, complex} , wij is the number of FPs user or other applications) of DFD are represented with a
assigned to a function of type i and of complexity j and dashed line box to distinguish it from entities represented
xij isthenumberoffunctionsoftypeithathavecomplexity as normal boxes. Data flows, error flows and control flows
j. Thevaluesofwij aregivenbytheIFPUGmanualwhile are represented by arrows to distinguish them from the
thevaluesofxij arecomputedbythecounter. connections between entities and relationship represented
The final FP count is then obtained by multiplying the as simple lines. Data flows, error flows and control flows
unadjustedcountbyanadjustmentfactorthatexpressesthe are distinguished on the basis of the line of the arrow:
influenceof14generalcharacteristicsofthesystemonwhich continuousfordataflows,dashedforerrorflowsanddotted
theapplicationwillrun. for control flows. Figure 1 shows a sample diagram. Note
FPcountisthusperformedinsixsteps: that either the symbol ‘1’ or ‘M’ (for many) is associated
to each connection between an entity and a relationship
(i) identifyingthetypeofFPcount: developmentproject,
to represent the functionality of a relationship: e.g. in
enhancementprojectorapplication;
Figure 1, relationship rel1 is one to many from entity2 to
(ii) identifyingtheboundaryoftheapplicationsubjectto
entity1, meaning that an occurrence of entity1 appears in
themeasure;
therelationshipatmostonetimeandoccurrencesofentity2
(iii) identifying the data functions, classified as ILF and
appearintherelationshipatmostMtimes.
EIF,andevaluatingtheircomplexitybycountingthe
A number of fields are associated with each data flow:
number of Data Element Types (DET) and Record
when a field has the same name as the attribute of an
ElementTypes(RET)foreachfunction;
entity, theyrefertothesamedata. Whenthefielddoesnot
(iv) identifying the transaction functions, classified as
correspond to any attribute, it represents data derived from
EIs, EOs and EQs and evaluating their complexity
attributesbycomputation. Errorflowsandcontrolflowsdo
by counting the number of DET and File Types
nothaveanyfieldsassociatedwiththem.
Referenced(FTR)foreachfunction;
Wesupposethatthediagramalsocontainstheindication
(v) determining the number of UFP by summing the
oftheboundariesofthedifferentapplicationsintheformof
contributionsofallfunctions;and
dashedlines.
(vi) computingthefinalnumberofFPbymultiplyingthe
InFigure1,twoprocessesareshown. Ascanbeseen,the
UFPcountbytheadjustmentfactor.
twoprocessescanexchangedatabyusinganelementofthe
Our aim is to automate Steps (iii)–(v) starting from the ERdiagram: inthisexample,thedatathatisreadbyProcess2
specificationofthesystemintermsofanER–DFDdiagram. fromentity1iswrittenbyProcess1.
Steps (iii) and (iv) are the most complex, time-consuming In order to perform the count, a number of assumptions
and prone to error, therefore they are the most interesting on the ER–DFD graph have been made. We assume that
to automate. We assume that a development project count every attribute of an entity or a relationship is unique, user
TheComputerJournal, Vol.47, No.3, 2004
360 E.Lamma,P.MelloandF.Riguzzi
FIGURE1. ExampleofanER–DFDdiagram.
recognizable and non-repeated in the sense of [3]. This within the boundary of the application. The primary
assumptionwillbeclarifiedinSection4.2. intentofanILFistoholddatamaintainedthroughone
Each process in the DFD must be an elementary process or more elementary processes of the application being
inthesenseof[3]: counted[3].
An elementary process is the smallest unit of activity
Let us now introduce the terminology used in IFPUG’s
that is meaningful to the user(s). ...The elementary
manual.
process must be self-contained and leave the business
oftheapplicationbeingcountedinaconsistentstate[3]. ControlInformationisdatathatinfluencesanelementary
process of the application being counted. It specifies
Assuming that every process in the DFD is an elementary
what,when,orhowdataistobeprocessed[3].
processisreasonableifwesupposethattheDFDprocesses
reflectthebasicactivitiestobeperformedbytheapplication. Thetermuseridentifiablereferstodefinedrequirements
Weassumealsothattheprocessinglogicofeveryprocessin for processes and/or groups of data that are agreed
the DFD is unique. This assumption is not very restrictive upon, andunderstood, byboththeuser(s)andsoftware
since it is reasonable for a DFD diagram not to have developer(s)[3].
duplicatedprocesses.
Thetermmaintainedistheabilitytomodifydatathrough
anelementaryprocess[3].
4. RULESFORCOUNTINGFPsFROMER–DFD
TheIFPUGidentificationruleforILFsis: agroupofdataor
In this section, we present the rules for counting FPs from
controlinformationisanILFifitsatisfiesallofthefollowing
the specification of an application expressed in the form of
conditions:
an ER–DFD. For each function, we have translated IFPUG
informal rules into rigorous rules expressing properties of (cid:128) Thegroupofdataorcontrolinformationislogical
theER–DFDgraph. Therulesobtainedarerigorousbecause anduseridentifiable.
alltheambiguitiesandvaguenessofIFPUGruleshavebeen (cid:128) The group of data is maintained through an
removed. Thus, it was easy to translate them into code. elementaryprocesswithintheapplicationboundary
In order to remove ambiguities and vagueness, we have beingcounted[3].
interpretedIFPUGrulesinthewaywethoughtwasmorerea-
sonable. Todoso,wehadtomakeanumberofassumptions When applying the above rule to ER–DFD, groups of
thatarelistedinSection3andarereportedbelow. logically related data are represented by sets of connected
In Sections 4.1 and 4.2, we discuss identification and entities and relationships while elementary processes are
complexity rules for data functions. In Sections 4.3 and represented by processes of the DFD. As discussed in
4.4, we describe identification and complexity rules for Section3,wehaveassumedthateveryprocessintheDFDis
transactionfunctions. anelementaryprocess.
Wealsoneedthefollowingdefinition:
4.1. Identificationrulesfordatafunctions
Definition1. (Maintained)Anentityorarelationshipis
DatafunctionsareILFandEIF. maintained by a process if and only if there is a data flow
fromtheprocesstotheentityorrelationship. Asetofentities
4.1.1. Internallogicalfiles andrelationshipsismaintainedbyaprocessifandonlyifthe
TheIFPUGdefinitionofanILFis: processmaintainsalltheelementsoftheset.
Aninternallogicalfile(ILF)isauseridentifiablegroupof We can present now the ILF identification rule for
logicallyrelateddataorcontrolinformationmaintained ER–DFD.
TheComputerJournal, Vol.47, No.3, 2004
364 E.Lamma,P.MelloandF.Riguzzi
FIGURE8. SimplestcaseofEO.
FIGURE6. SimplestcaseofEIofcontrolinformation.
4.3.3. Externaloutput
An external output (EO) is an elementary process that
sendsdataorcontrolinformationoutsidetheapplication
boundary. The primary intent of an external output is
topresentinformationtoauserthroughprocessinglogic
otherthan,orinadditionto,theretrievalofdataorcontrol
information. Theprocessinglogicmustcontainatleast
FIGURE7. SimplestcaseofanEQ. onemathematicalformulaorcalculation,createderived
data,maintainoneormoreILFsoralterthebehaviorof
The simplest case of EI of data is shown in Figure 2. The thesystem[3].
simplest case of an EI of control information is shown in
Figure8showsthesimplestcaseofanEO.
Figure6.
What distinguishes an EO from an EQ is the fact that
InordertoidentifyEIsintheER–DFDdiagram,wehave
an EQ does not elaborate the retrieved data, while an EO
toconsidertheprocessesinthediagram. Wehaveassumed
outputsderiveddata. Therefore,wehavethefollowingrule
inSection3thattheprocessinglogicofeveryprocessinthe
forER–DFD.
DFDisunique.
Rule7. (EOidentification)AprocessintheER–DFDis
Rule 5. (EI identification) A process of the ER–DFD
anEOif
belongingtotheapplicationisanEIif
(1) thereisatleastonedataflowfromafiletotheprocess;
(1) there is at least one data flow from the outside to the
(2) thereisatleastonedataflowfromtheprocesstothe
process,
outside;
(2) theprocessmaintainsatleastoneelementofanILF
(3) data flows from the process to the outside contain at
or
leastonefieldthatisnotcontainedinanyofthedata
(1) thereisaflowofcontrolinformationfromtheoutside
flowsfromILFstotheprocess.
totheprocess.
4.4. Complexityrulesfortransactionalfunction
4.3.2. Externalinquiry
InordertoassigntherightnumberofFPtoeachidentified
An external inquiry (EQ) is an elementary process that
transactionalfunction,wehavetocounttheDETsandFTRs
sendsdataorcontrolinformationoutsidetheapplication
associatedwiththefunction. ThedefinitionforDETsisthe
boundary. The primary intent of an external inquiry is
same as the one for data functions. The counting rule for
topresentinformationtoauserthroughtheretrievalof
DETsofEIis:
data or control information from an ILF of EIF. The
processing logic contains no mathematical formulas or Rule8. (EI,DETcounting)CountoneDETforeachfield
calculations, and creates no derived data. No ILF is indataflowsfromexternalsourcestotheEI.CountoneDET
maintainedduringtheprocessing,noristhebehaviorof foreacherrorflowfromtheEI.
thesystemaltered[3].
TheIFPUGdefinitionofanFTRis:
Figure7showsthesimplestcaseofEQ.
AFileTypeReferencedis
Rule6. (EQidentification)AprocessoftheER–DFDis
(cid:128) an Internal Logical File read or maintained by a
anEQif
transactionalfunction,
(1) there is at least one data flow from the outside to the (cid:128) an External Interface File read by a transactional
process; function[3].
(2) there is at least one data flow from the process to the
Recallingthedefinitionofasetofentitiesandrelationships
outside;
(and hence of a file) maintained given in Section 4.1.1,
(3) thereisatleastonedataflowfromanelementofafile
andreferencedgiveninSection4.1.2, wecannowgivethe
totheprocess;
countingruleforFTRs:
(4) allthefieldsofdataflowsgoingoutsidetheapplication
boundary are among the fields of data flows to the Rule9. (EI,FTRcounting)CountoneFTRforeachILF
process; maintained or referenced by the process and one FTR for
(5) noelementofanILFismaintainedbytheprocess. eachEIFreferencedbytheprocess.
TheComputerJournal, Vol.47, No.3, 2004
366 E.Lamma,P.MelloandF.Riguzzi
whenentitynamehassub-entitieschild1,...,childn. presentedinSection4.1.1: ilf(Appli,ILF)succeedsif
Argumentstotalandexclusivehavetobereplacedby ILF is a list containing the entities and relationships of an
theBooleanconstants0and1statingwhetherthehierarchy ILFfortheapplication Appli. TheILFidentificationrule
is total and/or exclusive. Each sub-entity must then be is implemented by the following Prolog clause (in Sicstus
representedbythefact Prologsyntax):
subentity(name, [attrib1,...,attribm]). ilf(Appli,ILF):-
application(Appli,EntList,RelList,
stating that sub-entity name has attributes
ProcList),
[attrib1,...,attribm].
% pick a process Proc of Appli
A relationship between entities is mapped into a Prolog
member(Proc,ProcList),
factoftheform:
append(EntList,RelList,ERList),
% find the ent. and rel. that are maintained
relationship(name, ent1, ent2,[attrib1, ...,
by Proc
attribn], card1, card2).
findall(ER,dataflow(Proc,ER,_),ILF1),
where name is a binary relationship between ent1 and delete(ILF1,user,ILF2),
ent2 with attributes attrib1,..., attribn and remove_duplicates(ILF2,ILF),
cardinalitycard1froment1andcard2toent2. card1 % verify that ILF is inside the boundary of
andcard2caneitherassumevalue1orm. Thecardinalityof Appli,
therelationshipisactuallyneverusedbytherulesdescribed subset(ILF,ERList),
above, but we have decided to store this information for % that is not empty,
possibleextensionsofthecurrentsystem. ILF \== [],
A data flow from sour to dest with fields % that is connected
field1,...,fieldnisrepresentedbyaPrologfactof connected(ILF),
theform: % that no partitions are ILF
\+ some_partitions_are_ILFs(Appli,ILF).
dataflow(sour,dest,[field1,...,fieldn]).
We use the Sicstus built-in predicate findall
Acontrolflowfromsourtodestisrepresentedby
(Template,Goal,Bag) that assigns to Bag a list
of instances of Template returned by each proof of
controlflow(sour,dest).
Goal found by Prolog. All variables in Goal are taken
andanerrorflowfromsourtodestisrepresentedby as being existentially quantified. The call findall(ER,
dataflow(Proc, ER,_), ILF) returns in ILF the
errorflow(sour,dest).
list of all the entities and relationships maintained by the
processProc. Thepredicatesubset(Sublist,List)
As an example, the ER–DFD reported in Figure 1 is
verifiesthatallelementsof SublistareinList.
representedas:
application(appli,[entity1,entity2], 6. CASESTUDIES
[relationship1],[process1,process2]).
In this section, we describe the application of FUN to a
application(user,[],[],[user]).
number of software systems. The first is an application
entity(entity1,[a1],[a2]).
forthemanagementofHumanResourcesthatisthesubject
entity(entity2,[b1],[b2]).
of a series of case studies [17, 18, 19] of FP measurement
relationship(relationship1,entity1,entity2,
published by IFPUG. Here we will consider [18] in which
[c1],1,m).
measurementisperformedstartingfromthespecificationof
dataflow(user,process1,[info]).
theapplicationexpressedasanERdiagramandaDFD.
dataflow(process1,relationship1,[c1]).
Theaimoftheapplicationistomanageinformationabout
dataflow(process1,entity1,[a1,a2]).
employeesofafirm. Inparticular,theuserrequiresstoring
dataflow(process1,entity2,[b1,b2]).
information about each employee, including data on the
dataflow(entity1,process2,[a1,a2]).
dependantsoftheemployee,dataonthesalaryorthehourly
dataflow(process2,user,[a1,a2,total]).
rate and data on the work location. The location must be a
controlflow(user,process1).
validlocationintheapplicationFixedAsset. Iftheemployee
errorflow(process1,user).
works abroad, the hourly rate must be converted to US
dollarsbyaccessingtheapplicationCurrencyandretrieving
5.3. Exampleoftranslationofthecountingrules
the conversion rate. Moreover, the application has to store
intoProlog
informationaboutdifferentjobs. Finally,theuserrequiresto
In this section, we show how the rule for identifying ILFs storeinformationabouttheassignmentofjobstoemployees.
has been translated into Prolog. The predicate ilf/2 is Table4showstheattributesofentitiesandrelationshipsand
used to identify ILFs, according to Rule 1 and Definition 1 Figure9theERdiagram.
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ASystemforMeasuringFunctionPoints 367
TABLE4. Attributesofentitiesandrelationships.
Entitiesorrelationships Attributes
Employee Social_Security_Number(key),Name,Nbr_Dependents,Type_Code.
Salaried Supervisory_level
Hourly Standard_Hourly_Rate,US_Hourly_Rate,Collective_Bargaining_Unit_Number
Dependant Dep_SSN(key),Dep_name,Dep_birth_date
Job Name,Job_Number(key),Pay_grade
Description Line_Number,Description_Line
JobAssignment Effective_Date,Salary,Performance_Rating,Status_Inactive,System_Date
Location Location_Name(key),Address,City,State,Zip,Country.
Currency Currency_Location(key),Base_Currency,Conversion_Rate_To_Base_Currency,Date_Of_Rate.
FIGURE9. CompleteERdiagramfortheHumanResourceapplication.1
Theprocessesthattheuserrequiresareadding,changing, Among these processes, we will consider here in more
inquiring and reporting information about employees, detailthefollowing:
jobs and job assignments. In inquiring, the user asks (cid:128) adding an employee, together with data on his
for information regarding an employee, a job or a job
dependantsandthesalaryorhourlywage(seeFigure10
assignment given respectively, a Social_Security_Number,
fortheadditionprocess);
a Job_Number or a Social_Security_Number and a (cid:128) reporting on all employees, printing the list of
Job_Number. In reporting, the application prints a list of
employeestogetherwiththeirtotalnumber(Figure11);
allemployees,jobsorjobassignmenttogetherwiththetotal (cid:128) inquiring on the data of an employee, given his social
numberofshownentities. Moreover,theapplicationshould
securitynumber(Figure12);
alsoallowinquiringonlocationinformation(processInquire (cid:128) adding job information, together with its description
Locations): itshouldprint,foreachemployee,his/hersocial
(Figure13);and
securitynumbertogetherwiththeinformationonthelocation (cid:128) addingajobassignment(Figure14).
wherehe/sheisworking.
After having loaded from the Sicstus interpreter both the
1Thisdiagramdiffersfromtheonein[19]becausetherelationshipEmp. system code and the application description, the count is
Currencyhereisinsidetheapplicationboundary. Webelievethisdiagram startedbycallingthegoal:
ismorecorrectsincetherelationshipEmp.Currencyismaintainedbypro-
cessesinsidetheapplication. | ?- totalFP(hr,FP).
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