IT PROJECT METRICS. Projects and Programs Evaluation. Risks, resources, activities, portfolio and project management. 1. IT projects.

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1 IT PROJECT METRICS Ion IVAN PhD, Unversty Professor, Department of Economc Informatcs Unversty of Economcs, Bucharest, Romana Author of more than 25 books and over 75 journal artcles n the feld of software qualty management, software metrcs and nformatcs audt. Hs work focuses on the analyss of qualty of software applcatons. E-mal: onvan@ase.ro, Web page: Adran VISOIU 2 PhD Canddate, Assstant Lecturer, Economc Informatcs Department, Unversty of Economcs, Bucharest, Romana E-mal: adran.vsou@cse.ase.ro Dragos PALAGHITA 3 4 th year student, Unversty of Economcs, Bucharest, Romana E-mal: dpalaghta@gmal.com Abstract: The objectves of IT projects are presented. The qualty requrements that these projects must fulfll are establshed. Qualty and evaluaton ndcators for runnng IT projects are bult and verfed. Project qualty characterstcs are presented and dscussed. Model refnement for IT project metrcs s treated and a software structure s proposed. For an IT project whch s desgned for software development, qualty evaluaton and project mplementaton mode metrcs are used. Key words: IT metrcs; IT projects; qualty; qualty characterstcs. IT projects They represent an mportant category of projects and ther management mples specfc partculartes because: - Ther unque character; nformatcs systems and software are developed only one tme to brng n new solutons; - The reproducton of the resulted products s defned by costs nearng zero, determned by the possblty to make copes on modern storage devces; - The work force used to develop the IT project s hghly qualfed and represents, n most cases, over 85% of the projects value; - The development cycle of an IT project must nclude wthout queston soluton mprovement stages to brng n the latest technologes n the feld; neglectng these new technologes wll lead to an old soluton whch may be rejected by the benefcares and the nformatcs market; 302

2 - The structure of the development cycle s adapted the pursued objectve, the allocated resources, whch leads to decsons regardng the contnuance or abandonment of the projects, when the revewed effcency crteron suggest one of the two choces; ths explans the fact that of 00 projects, over 50 are abandoned n the development process, only 0 projects get n mantenance and only 2-3 go n to the reengneerng process; - In the context of an evolvng nformaton and knowledge based socety, all IT projects must be orented to be user frendly, n order to grant free access to broader categores of nformaton to every ctzen. IT project mply vast amounts of money. For projects n constructons, the amount of money needed range between thousands and mllons of euros, and the resultng product s tangble, t becomes functonal and s drectly perceved. For IT projects the amount of money needed starts from ten thousands euros and fnally the result can only be seen n computers and networks, whch are no more than 5% of the projects value. The hdden part of 85% must prove ts effcency through functonalty, n tme. Ths s why t s necessary buldng IT project metrcs, to measure: - How are the resources used; - Whch are the products performances; - How effcent wll the products be n explotaton; - Whch are the rsks of not fnshng the project or to compensate devatons from the project. Currently there are numerous metrcs for every software typology, for every qualty characterstc and for cost estmaton. It s mportant these metrcs are analyzed and a practcal approach for usng quanttatve methods s developed such that n the IT feld the grounds of decsons wll change the structure of projects and make the number of projects that get reengneered to ncrease. 2. Qualty characterstcs of IT projects The IT projects qualty characterstcs form a dynamcal, complex and optmal system. The systemc character s gven by the nterdependences between characterstcs. At a gven tme t, a qualty characterstc of a project postvely nfluences the level of another characterstc at tme t+. Also, that characterstc has a negatve nfluence on the level of another qualty characterstc. The dynamc character s lnked to the fact that nterdependence ntensty between characterstcs vares n tme. More, the mportance of qualty characterstcs changes from one IT project to another, from user to user or even nsde the project, the modfcaton occurs from one stage of the project to another. The complex character resdes n the large number of qualty characterstcs, n the number of nterdependences, and mostly n the drectons n whch they manfest. The accumulated experence n elaboratng and mplementng projects shows that the characterstcs system becomes more complex as the objectves are better pursued and the level of performance s hgher. 303

3 The optmalty of the qualty characterstcs system oversees the quanttatve sde of costs that the tendency to plan and complete projects wth a hgher qualty level generates. There s a soluton of the qualty optmzaton model that shows the moment n whch the mprovement of qualty s no longer sustaned through costs, whch are far grater than the costs needed to fx the correspondng defects of a lower qualty level of the IT project. If M s consdered the number of the qualty characterstcs C, C 2,..., C M of the projects, for each characterstc must be stated: - the content ; - the factors of nfluence; - the assocated models - the use of ndcators n takng decsons; - the ndcators aggregaton. Complexty s the characterstc used n dfferentatng projects. A project A s more complex than a project A j f: - the type number of resources used s grater; - the number of stages through whch the project s fnshed s grater; - the number of machnes used s grater; - the number of dfferent operatons done by each machne s grater; - the qualfcaton needed by workers to operate the machnes s hgher; - the number of lnks between stages s grater; - the executon tme s grater; - the organzatonal effort s grater; - the densty of executon procedures s hgher. A graph s assocated to the project A n whch the nodes are ether stages or actvtes, and the arcs are the ones that set the precedence. If: - n the number of nodes of the graph G(A ) for the project A - n 2 the number of arcs whch lnk the nodes of the graph G(A ) the complexty CP of the project A n a Halstead way s gven by: CP(A )=n log 2 n + n log 2 n 2 A project A s more complex than a project A j f and only f: CP(A )>CP(A j ) Meanng ( n ) ( n ) j n j n ( n ) 2 ( n ) j 2 2 n > j 2 n If n tme n an organzaton projects are mplemented of whch a project A k s consdered a model, the relatve complextes of the projects CR(A ), CR(A 2 ),, CR(A M ) are obtaned from: (A) CR(A) = C(Ak) 304

4 The project model has the relatve complexty CR(A k ) =. The K completeness of project K s a qualty characterstc whch refers to two aspects: K o the completeness of the offer regardng the content of the document whch s under evaluaton K the completeness of the mplementaton regardng the stages developng process and the completeness of the process If p s the percentage of the elaboraton stage of the offer and p 2 s the percentage of the developng of the project p +p 2 = and p, p 2 (0,) t results that the level of completeness KP of project A s gven by: KP= p *Ko+p 2 *K. The level of completeness K of any constructon regards: np the number of parts mposed to consder the constructon accepted nr the number of parts effectvely realzed and the relaton s obtaned: mn{ np, nr} K = max{ np, nr} A project contans: - elgblty crteron to whch varables that belong to {0,} are assocated to; f n the project the mposed requrements are respected the value s gven to a crteron Cr ; f a project must fulfll L elgblty crterons the ndcator IL = = s calculated where α s the level of the Cr crteron, α {0,}; - the techncal sde defnton, n whch defntons are gven, processes are descrbed, models are bult; the completeness refers to the degree n whch these descrptons nclude all the components known by specalsts; the descrptons must offer a suggestve pcture n connecton wth what s gong on n the actual choused doman; there must not be a lack of elements whch by ther absence: o prove that the authors do not have a grasp on the doman; o show that the authors of the project do not have knowledge of materals, equpment, processes, operatons, effects and models. L α The specalsts that analyze a new project have a clear mage about the structure that ncludes mandatory parts, mnmum requrements and by comparson see what s mssng or what has been treated shallow. Clarty s a very mportant characterstc not only for the offer made for a project but also to the development process. The offer s a text. The mplemented project s a product, a servce, an acton. The clarty of text T assocated wth project A s analyzed n the followng manner: - the text T s decomposed n parts a, a,..., a r; - each part a j, j =,2,,r, s connected wth resources, actons and equpments; - the logc content of a j wth the logc of the process development; - parts of the text are connected wth resources buldng up pars (a j,r p ) 305

5 If the pars parts of text resources are completely defned then the text T s clear. If parts of text or resources are not pared, the project does not have a good clarty level. The clarty s nfluenced n a negatve way by pars n whch for dfferent parts of text the same resources come up. The necessty of defnng probabltes whch are assocated wth the pars (a j, r p ) also has a negatve nfluence on clarty. Correctness s qualty characterstc of a project, through whch the ones that make the offer ant partcpate n the development of the project ensure: - the concordance between theory and practce - the use of results obtaned by other specalsts, results that were verfed n practce; - the use of concepts as they were defned, mantanng the context unaltered; - respectng the defned procedures for executng operatons; - through all the means used, that the requrements mposed by obtanng a hgh level of qualty for the product or servce n ts fnal form, are respected. The correctness of a project offer s demonstrated, and the correctness of a product or the executon of a servce s ponted out ether by analyss, or by establshng the effects the product or servce wll generate. A product or a servce s correctly or ncorrectly realzed. If t s accepted that the product or servce s partally correct, the correctness measurng ndcator moves from the values 0 or to the nterval [0,]. The problem of correctness n calculatng costs and effcency regards: - the hypothess on the bass of whch the effcency calculatons are made; - establshng the expenses levels for each chapter by pontng out quanttes, untary prce, and nterval lmtaton; - usng the calculaton models as they were defned; - boundng the varables regardng specfc consumes through comparatve analyss wth projects already mplemented; - respectng the control keys; - respectng the nequaltes regardng the expense structure n condtons of the mpossblty of not transmttng from one captal to another of the expenses. For the defnton of IT projects the followng are defned: - the crterons Cr, Cr 2,, Cr h ; - the domans of varaton measured for each crteron [a, b ], [a 2, b 2 ],, [a h, b h ]. If for crteron Cr the level x s measured, then the correctness of the project s gven by: h CG = = h = x h a CG = b. The correctness norm s realzed by defnng the relaton: h h a x CGN = = b = b 306

6 There are numerous cases n whch the relatve correctness of a crteron Cr s obtaned usng a report lke: A CR = h Where: A the number o fulflled sub crterons h the total number of subcrterons In ths case the global correctness s CG= h ( = CR ) h Consstency s a qualty characterstc whch s used to pont out to what extent an IT project s bult respectng precse rules, wthout ncludng components whch have the role of annhlatng what was pror executed. The text of the project ncludes stages, chapters developed n ascendant order wth the next components beng constructed based on the ones before. A project s under defned f the text or the product doesn t contan those elements that nsure ts functonalty. The project s over defned f t ncludes a lot more components than necessary. The numerous detals make t hard to accomplsh, and the functon for whch t s constructed s lost among many other functons, some havng nothng n common wth the ntal objectve. Only a defned project, n whch every component has ts role well establshed, s a consstent project. A project structure, SP, s consdered, havng the complexty C (SP), structure whch corresponds to projects, products or IT servces consdered to be functonal, whch exst and have a degree of satsfacton at user level grater than 0.8, the degree of satsfacton s gven by: GS=NF/NT Where NF the number of users that have successfully fnshed the problem for whch they used the resources of the project; NT the total number of users that accessed the resources belongng to the project. The consstency CO for the project A s gven by: CO = mn{ C( SP), C( A )} max{ C( SP), C( A )} Ablty to complete s another characterstc that all evaluators take n consderaton and t s nfluenced by: - the experence of the team whch proposes a soluton for an IT problem; - the estmaton of resources used for mplementng the soluton; - the estmated duraton of the project; - dentfed resources and procedures used to attenuate the effects. 307

7 The practce of elaboratng an offer and mplementng t presume: - knowledge of technologes; - rgorous knowledge of duraton and mnmal and maxmal consumptons necessary to complete actvtes; - the correct defnng of precedence; - dentfyng the operatons needed to prepare; - buldng a tmelne for actvtes; - regroupng the actvtes such that the equpment and hghly qualfed workforce are effcently used. If n a project are dentfed: NA number of actvtes; D tme to complete actvty ; K number of resources necessary for completng actvty ; x j resource consumpton j for completng actvty ; t s start tme for actvty ; t f end tme for actvty ; The planned and effectve levels are establshed. For the planned levels mark p wll be used; the planned level for actvty xxx wll be xxx p. For the effectve level the mark e wll be used, such that varable xxx wll have the effectve level xxx e. The ndcator IUR regardng the use of resources s bult usng the relaton: where IUR = NA k = j= NA = k α p e, xj = xj α j = 0, for the rest j The ablty to complete s seen also compared to optmstc or pessmstc atttude manfested by those who make an offer or mplement a project. If the planned level for a resource s x jp, the mnmal consumpton for completng operaton x j mn, and the maxmal consumpton for a resource s x j max the level realstc approach s bult as the ndcator IR gven by: Where IR = NA = j= NA k = k β j 308

8 p mn p 0, xj = xj sau xj = x β j =, for the rest max j Relablty s qualty characterstc of IT projects whch states the degree n whch the stages n the lfe cycle of the project are developng successfully The lfe cycle of an IT project ncludes: E- the offer elaboraton stage E2- project mplementaton stage E3- the current use of the product resulted after through the project E4- the mantenance process E5- usng the product post mantenance E6- takng the product out of use Each of these stages has assocated an mportance coeffcent p, ={,2,3,4,5,6}. Each stage E s characterzed by a duraton D(E). The physcal duraton norm of the lfe cycle of the project s gven by: 6 DFN= D(E) = The corrected duraton norm of the project s gven by: 6 DFNC= = p D(E) DFNC<DFN because p (0,) = =,2,3,4,5,6. 6 p= resultng that D(E)>pD(E) for In the background of every stage processes are runnng. If a process θj s stopped because of varous causes, the duraton of the process DP(θj) ncreases wth Δ(θj ) whch ncrease depends on: the complexty of the cause that determned the nterrupton; the ablty of the team to elmnate the cause; the resources that are redrected to elmnate the cause; the place where the cause was spotted; as a cause s spotted later, the resources used and duratons are ncreasng; The physcal runnng cycle norm of the project s dentcal wth the effectve duraton f and only f Δ(θj)=0 j N. In realty, throughout the lfetme there are recorded nterruptons of specfc stages Δ(E), such that the effectve duraton of the cycle: n DFE= ( D( E ) + Δ( E )) = The norm relablty of the project P,f(P) s gven by: DFN f(p)= DFE The corrected relablty fc(p) s gven by the relaton: 309

9 DFNC fc(p)= DFEC n p D E h E where DFEC= [ ( ) + Δ( )] where h =,2,3,4,5,6 are the fractons assocated = to the mportance whch s gven to the duraton of process delayng from the stages E, =,2,..6. Compared to other products or servces n whch relablty s characterzed by qualty n use, at the benefcary, gvng the degree n whch the product or servce accomplshes the set objectve, n case of the IT projects, the relablty of a project s mstaken wth the relablty of the lfe cycle because: n all the stages the workforce plays an mportant role, representng more then 85% of the producton costs; the successful functonng of the fnte product strctly depends on the operatng of each subsystem; the offer lays down the conceptual foundaton and resource allocaton; the elaboraton of the offer s a stage of the lfe cycle of the IT project; the offer elaboraton process relablty s essental to the entre product; the eventual deployng of an reengneerng process s meant to redefne basc elements of the offer, and the multple moblzaton effect of the new structure of an IT project s lmted to all the other stages that follow. It s mportant to dentfy n the exstng projects n the databases those varables wth the help of whch the levels of dfference Δ(E) are calculated to help compute the effectve relabltes of these projects n the norm verson and most of all n the corrected verson. Gven the Project P n the table below, Table. Data for P project Name Norm duraton Effectve Interrupton duraton duraton E E E E E E Total Total The relablty of project P = There are other qualty characterstcs of an IT project lke: - comparablty - reusablty - orthogonalty - reproducton ablty For these characterstcs the research must be contnued such that the results wll be operatonal n daly practce. 30

10 3. IT project model qualty refnement Models are bult startng from a model of hypothess. It s necessary to go on to the stage of refnng the models. The refnement process conssts of: - Reducng the number of varables; - Decreasng as much as possble the degree of ncorporated nonlnearty ; - Guaranteeng mnmal loss of nformaton by usng smplfed models. The refnement of IT projects assumes: - Takng n consderaton only the data that s collected usually for elaboratng the offer and runnng the projects; - Retanng n the ndcator strcture the varables that decsvely nfluence the evoluton of the project from a practcal pont of vew; Refnement s made on two levels: - At the frst level, from the set of ndcators I, I 2,..., I M a subset s retaned formed by the ndcators I, I +,..., I +K, K<<M. - At the second level, the retaned ndcators operate wth the varables X, X +,, X +H, H<<L nstead of usng the varables X, X 2,..., X L. It means that nstead of analyzng M characterstcs, a number of K characterstcs s analyzed. Instead of L varables, the refned ndcators operate wth H varables. The effort must be reduced wthout sgnfcant loss of nformaton obtaned from usng the metrcs. The decsons taken based on the refned metrcs of the IT projects must lead to mantanng the process of mplementaton n the lmts recognzed acceptablty. IT projects metrcs refnement must allow the use of exstent data bases, and the mplementaton of smplfed ndcators must not be affected by the defned data structures, wthout requrng new data structures or data reorganzaton. The IT project metrcs refnement process s carred on lke n fgure. SET OF IT PROJECTS BUILDING METRIC METRICS REFINEMENT RUNNING PROJECTS DECISION MAKING Fgure. Usage of refned models 3

11 The refnement process s customzable by defnng lmts referrng to: - the mnmum lst of varables that defnes the ndcators; - the accepted loss of n formaton level. Under the condtons the ndcators I, I 2,..., I K are consdered n whch the varables X, X 2,..., X L are used, through refnement t s mposed: - the maxmum number of ndcators to be M max ; - the maxmum number of varables to be H max ; - the error level must not be hgher than E. Refnement presumes: P- defnton of the ntal soluton for the refnement process whch ncludes all the K ndcators, all the L varables and the crteron through the measurements are made; P2- takng the data bases that regard IT projects that have frequent defnton classes and best mplementaton, known as successful projects. P3- evaluaton of ndcators I,I 2, I k wth the data taken from the data bases for the L varables P4- calculatng the aggregated error crteron P5- elmnaton of the x varable from the ndcators P6- evaluaton of the ndcators P7- calculaton of the crteron P8- buldng the Er array P9- repeatng the steps P 5 - P 8 to elmnate the varable x + from the lst P0- after buldng the array Er,Er 2, Er L t s sorted n descendng order and the varables for whch the error has the smallest value are elmnated P- the steps P 5 - P 0 are repeated untl the gven error level s obtaned; t s possble ths level s reached n the frst teraton and the refnement process stops; Once the varable lst s refned, the refnement of ndcators starts. P2- the lst I,I 2, I K of ndcators and the lst of refned varables X,X 2, X H are consdered; P3- the ndcators are calculated usng the relaton and are consdered an ntal soluton for the aggregate performance ndcator IP 0 H = p I j j where p j - weght j= and a certan level s obtaned P4- the ndcator I k,k=. s elmnated P5- IP s calculated and a vector α,α, s bult P6- steps P 4 - P 5 are repeated untl the ndcators are elmnated one by one P7- α,α 2, are ordered decreasng P8- the ndcator whch has the smallest error dfference wth IP 0 s elmnated P9- the steps P 4 - P 8 are repeated untl the maxmum admtted number for ndcators s reached 32

12 The refnement actvty s a repeatng process convergent to a stable process. To complete the refnement smulaton methods and genetc algorthms and neuronal networks are bult. 4. Software for mplementng IT metrcs The software product for evaluatng IT projects assumes: buldng a lst wth K qualty characterstcs KAL, KAL 2,, KAL k buldng a lst of ndcators I,I 2, I k buldng a lst wth M varables makng the connecton between the M varables and felds n the data base launchng the refnement process obtanng a sublst of characterstcs wth a sublst of ndcators whch are obtaned wth a sublst of varables valdatng the sublst of ndcators as a metrc of IT projects The software product desgned to mplement IT metrcs s a complex constructon whch: must be accessed off the nternet; has user authentcaton ; accepts defntons of data bases; takes felds from the data base and consttutes the seres that make estmatons; allows the selecton of structures of ntal ndcators I,I2, Ik; offers a lst of performance crteron for selectng ndcators and varables; generate ndcator structures for the refnement process; calculates the level of refned ndcators on request or perodcally to fundament decsons. The software product has the functons: user authentcaton; the management of data sets that correspond to the problems to solve; estmaton of model coeffcents; model refnement; model structure generaton; aggregaton level calculaton to fundament decsons; optons, parameters and solutons are saved f the data sets are vald; addng of nformaton and dentfcaton data. The software structure s gven n fgure 2. 33

13 IT projects datasets Base module User authentcaton IT projects data management Model management Soluton management Model buldng Model generaton Model estmaton Fgure 2. Software structure for IT project metrcs mplementaton The software product s takng numerous elements that consttute a modelbase. The modelbase s a complex constructon n whch lsts are ncluded wth: - dependent varables and ndependent varables; - lnear and nonlnear models structures; - regstered data sets and generated data sets; - mplementaton of the coeffcents estmaton algorthms; - procedures for the hypothess verfcaton; - procedures for the estmated values calculaton; - models herarchzng procedures. These very mportant components are elements wth whch the modelbase s populated. For the modelbase to become operatonal, an admnstraton system has to exst. Frst of all, the admnstraton system has to operate dstnctly wth data sets, wth the procedures and wth the models structures. Second of all, the admnstraton system functons have to effectuate the fast fndng of the data sets, of the models structures and of the procedures n order to secure the processes development n concordance wth the demands of the analyst economst. Thrd of all, the admnstraton system has to be equpped wth functons whch permt the data sets addng, the models addng and the procedures addng. The perspectve has to be changed, through whch the modelbase brngng up to date mpled data / models / procedures deletng or changng of some parts of these wth new sequences. The acceptance of the brngng up to date functon exclusve through addng comes to brng a concordance between the natural way of understandng the evoluton wth the correspondng reflecton of t on nformatcs level. 34

14 The modelbase admnstraton system operates wth non homogenous enttes, mportant aspect n securng the flows consstency. Fourth of all, an open character s secured, the users havng at ther dsposal the possblty of defnng personal algorthms for nterpolaton and extrapolaton, for pseudoaleatory numbers generaton, for the coeffcents estmaton, for mplementng personal models selecton crtera. Ffth of all the, defnng of the specfc concepts regardng the fndng, selecton, extracton, targets the trplets (data, models structures, procedures), whch group complex proceedngs. Sxth of all, a growth of the generalzaton degree for the transacton concept s produced, whch n case of the modelbase mples the traversng of some flows n whch t s operated smultaneously wth data sets, wth data structures and wth procedures. The new conglomerate, more complex than the object structure that ncludes the operands and operators, develops a new projecton on the phlosophy of desgnng an admnstraton system, the admnstraton system of the modelbase, n whch new typologes specfc to the mplemented processes n the feld of artfcal ntellgence are ncluded besdes the already usual proceedngs. Utlzatons of the modelbase mply actvatons of some sequences of procedures from the modelbase. The admnstraton system of the modelbase s a constructon wth a very hgh complexty degree. The users must have the possblty of startng a small dversty of economc analyss projects. For example, the coeffcents estmaton of a model on the bass of a data set conssts of: - the specfcaton of the exogenous varables number and of the endogenous varables number; - the specfcaton of the data seres terms number; - the nserton of the data table; - the delmtaton of the varables lst correspondng to the data seres poston. Also, some results regardng the estmatons qualty are dsplayed. Ths procedure s specfc to the stuaton n whch the user has a clear mage on the phenomenon and ths one s analyss s already a routne actvty. Model generators are software applcatons takng as nput datasets and nformaton regardng model nature, structure and complexty and produce dfferent models from a certan model class. Lnear model generators take as nput a dataset contanng a number of ndependent varables and a dependent varable and produce lnear models combnng nfluence factors. Lnear model generators wth lagged arguments allow the elaboraton of constructons whch permt the modelng of the cases when a varaton n an nfluence factor has a delayed effect on the dependent varable. The generator produces combnatons of both nfluence factors and lags, dentfyng best models. Standard nonlnear model generators use predefned analytcal forms for generatng models. General nonlnear model generators buld automatcally analytcal expressons contanng nfluence factors. All generators order ther results accordng to performance ndcators. 35

15 Model complexty s assessed by measures based on Halstead metrcs, takng nto account the number of operators and operands. Complexty measures help comparng models and buldng performance ndcators. The quanttatve study of phenomena s encouraged by the volume of hstorcally recoded nformaton. Its purpose s to take decsons leadng to contnuous mprovng of performance ndcators for subsequent projects. Modelbases are complex software constructons offerng functons for: defnng, retrevng and updatng models; modelng applcatons management; estmaton and valdaton of coeffcents; automated model generaton from exstng datasets; dataset management. Model generators are modelbase nstruments that buld model structures from a gven class usng varables found n the dataset gven as nput. Model classes group models wth the same structure, e.g. lnear models, lnear models wth lagged varables, nonlnear models. For each class a model generator s developed. Each dataset contans data seres for the recorded varables. The endogenous varable s specfed and the generator bulds analytcal expressons usng nfluence factors. For each model structure, coeffcents are estmated and a performance ndcator s computed. The resultng model lst s ordered by the performance ndcator. The analyst chooses between the best models an approprate form that later wll be used n estmatng the studed characterstc. In the context of model generaton, the refnement process s descrbed as follows. Consder the dataset S and a model generator G. The set of models generated by G to ft the dataset S s L M. The model set L M s characterzed by the followng: the number of models s large; models have a varety of values for the performance crteron rangng from the worst fttng model to the best fttng model; models have a varety of values for the complexty, rangng from the most smple expressons to very complex ones; the best fttng models are not compulsory the most complex ones, and also, the smplest models are not the worst n explanng the studed phenomenon. The refnement process usng model generators s descrbed by the followng dagram shown n fgure 3. 36

16 Dataset D,D2,... Model lst orderng lst of refned models model varables Analytcal expresson generaton lst of model structures lst of models Parameter estmaton Modelbase M,M2,... Fgure 3. The model refnement process The refnement process takes the followng steps: - the dataset s bult; t contans data seres for the dependent varable and ndependent varables; - usng varable names found n the dataset, model structures are generated; the lst of generated model structures s denoted by L G and contans a large number of models, also dependng on the constrans or type of the generaton algorthm; - for each model structure n L G, coeffcents are estmated, along wth statstcal performance ndcators, obtanng the lst of estmated models, L E ; - for each model found n L E, an aggregated performance ndcator s computed; the L E lst s ordered by ths performance ndcator and an arbtrary number of models s chosen, formng L R lst, the refned lst of models; - the refned lst of models s saved nto a modelbase and then used by the human analyst to choose one or more models to be used n estmatng the studed phenomenon. 5. Conclusons Takng nto consderaton the mportance of IT projects the contnuance of the study s mandatory: Qualty characterstcs; Identfyng new ndcators; Makng the data collecton and metrcs calculaton an automatc process; Recordng reacton to the decson qualty to see what are the ndcators whch need perfectng. In current tme there are nstruments used to assst elaboraton processes of IT projects. These nstruments are meant to ensure the completeness of IT projects. If the followng are bult: - actvty lsts; 37

17 - resource lsts; - job lsts. and for each the number of elements s establshed from the lst, as an nstrument s meant to mpose: the complete descrpton of the elements n each lst; the correlaton of elements between lsts; the aggregaton of data from the generated matrces by the combnaton of lsts. If a seres of relatons are mposed regardng: the structure of the offer text; the expense structure; the actvty precedence ; the rates of fnancng. the nstruments are meant to: verfy f the structure s respected; generate the parts of structure; reduce the number of repeats from one component to the other; control the levels of complexty; nclude aggregated levels; elmnate abbrevatons ntroducng the elements clearly; ensures the qualtatve level of the crterons; evaluate the level of allocated resources; use correct words from a specalty vocabulary. For a data base n whch the records regardng the evoluton of a project are saved, the dates must be complete and correct. If data s taken from several projects the followng are calculated: dfferences between the consumpton or normed duraton; The nterval belongng frequences and consumpton varaton; The probablty that a varable wll follow a certan repartton law. The complete mage over an IT project s obtaned only through the mplementaton of a correctly constructed metrc, refned and completely valdated. Bblography Boja, C., Ivan, I. Metode statstce în analza software, Ed. ASE, Bucharest, 2004 Ivan, I., Boja, C. Managementul caltat proectelor TIC, Ed. ASE, Bucharest, 2005 Ivan, I., Nosca, Gh., Popa, M. Managementul caltat aplcatlor nformatce, Ed. ASE, Bucharest, Ivan, I., Popescu, M. Metrc software, INFOREC Publshng House, Bucharest, 999 Ivan, I., Ungureanu, D. Project Complexty, INFOREC Publshng House, Bucharest, 2002 Ivan, I., Vsou, A. Baza de modele economce, Ed. ASE, Bucharest, 2005 Jalote, P. Software Project Management n Practce, Addson Wesley, 2002 Toma, C., Ivan, I., Popa, M., Boja, C. Data Metrcs Propertes, Proceedngs of Internatonal Symposum October 22-23, 2004, Iassy, Romana, pp

18 Vsou, A. Performance Crtera for Software Metrcs Model Refnement, Journal of Appled Quanttatve Methods, Vol. 2, No., March 30, 2007 Vsou, A., Garas, G. Nonlnear model structure generator for software metrcs estmaton, The 37th Internatonal Scentfc Symposum of METRA, Bucharest, May, 26th - 27th, 2006, Mnstry of Natonal Defence, publshed on CD Vsou, A., Ivan, I. Rafnarea metrclor software, Economstul, suplment Econome teoretca s aplcatva, no.947(2973), August 29, 2005 Ion IVAN has graduated the Faculty of Economc Computaton and Economc Cybernetcs n 970, he holds a PhD dploma n Economcs from 978 and he had gone through all ddactc postons snce 970 when he joned the staff of the Bucharest Unversty of Economcs, teachng assstant n 970, senor lecturer n 978, assstant professor n 99 and full professor n 993. Currently he s full Professor of Economc Informatcs wthn the Department of Economc Informatcs at Faculty of Cybernetcs, Statstcs and Economc Informatcs from the Unversty of Economcs. He s the author of more than 25 books and over 75 journal artcles n the feld of software qualty management, software metrcs and nformatcs audt. Hs work focuses on the analyss of qualty of software applcatons. He s currently studyng software qualty management and audt, project management of IT&C projects. He receved numerous dplomas for hs research actvty achevements. For hs entre actvty, the Natonal Unversty Research Councl granted hm n 2005 wth the natonal dploma, Opera Omna. He has receved multple grants for research, documentaton and exchange of experence at numerous unverstes from Greece, Ireland, Germany, France, Italy, Sweden, Norway, Unted States, Holland and Japan. He s dstngushed member of the scentfc board for the magaznes and journals lke: - Economc Informatcs; - Economc Computaton and Economc Cybernetcs Studes and Research; - Romanan Journal of Statstcs He has partcpated n the scentfc commttee of more than 20 Conferences on Informatcs and he has coordnated the appearance of 3 proceedngs volumes for Internatonal Conferences. From 994 he s PhD coordnator n the feld of Economc Informatcs. He has coordnated as a drector more than 5 research projects that have been fnanced from natonal and nternatonal research programs. He was member n a TEMPUS project as local coordnator and also as contractor n an EPROM project. 2 Adran Vsou graduated the Bucharest Unversty of Economcs, the Faculty of Cybernetcs, Statstcs and Economc Informatcs. He has a master degree n Project Management. He s a PhD student at Doctoral School of Bucharest Unversty of Economcs n the feld of Economc Informatcs. He s an assstant lecturer n the Economc Informatcs Department of the Bucharest Unversty of Economcs. He publshed 7 artcles and he s coauthor of Baza de modele economce book. 3 Dragos Palaghta s a 4th year student n the Unversty of Economcs, Bucharest, Cybernetcs Statstcs and Economc Informatcs faculty, Economc Informatcs secton. He s programmng n C++ and C# and hs man areas of nterest are Informatcs Securty and Software Qualty Management. 39

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