A particle Swarm Optimization-based Framework for Agile Software Effort Estimation



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The Iteratoal Joural Of Egeerg Ad Scece (IJES) olume 3 Issue 6 Pages 30-36 204 ISSN (e): 239 83 ISSN (p): 239 805 A partcle Swarm Optmzato-based Framework for Agle Software Effort Estmato Maga I, & 2 Blamah N Departmet of Computer Scece, Adamawa State Uversty, Mub, Ngera 2 Departmet of Computer Scece, Uversty of Jos, Ngera -------------------------------------------------------ABSTRACT---------------------------------------------------- Software effort ad cost estmato process ay software egeerg project s a very crtcal compoet. The success or falures of projects deped heavly o the accuracy of effort ad schedule estmatos. The paper examed A Partcle Swarm Optmzato-Based Framework for Agle Software Effort Estmato. Tradtoal approaches were used to estmate effort for agle projects, but they mostly result accurate estmates. Ths paper amed at the applcato of some Partcle swarm optmzato framework as a soft computg techque for agle software developmet methodology effort estmato. The paper also detfed project that uses agle developmet methodology, later appled Partcle Swarm Optmzato to mmze project durato ad effort requred to buld software. Fally the PSO model mproves the effort ad tme estmato accuracy by mmzg these parameters ad the estmates values are close to the actual results. Geerally, the acceptable target value for Mea magtude of relatve error (M) s 25%. It dcates that the magtude of relatve error () for each project for the establshed estmato model should be less tha 25% o the average. A software developmet effort estmato method wth a smaller M value tha the oe wth bgger M value gves better estmates tha a model wth a bgger M value. The M obtaed from the paper dcated that the M value for effort s 5.2% less tha the ormal establshed estmato model. KEYWORDS: Optmsato, effort estmato, agle, software --------------------------------------------------------------------------------------------------------------------------------------- Date of Submsso: 0 Jue 204 Date of Publcato: 30 Jue 204 -------------------------------------------------------------------------------------------------------------------------------------- I. INTRODUCTION Software effort ad cost estmato process ay software egeerg project s a very crtcal compoet. The success or falures of projects deped heavly o the accuracy of effort ad schedule estmatos. The troducto of agle methodology the software developmet dustres preseted may opportutes for resarchers ad practtoers.today, software exceeds 25 mllo source code statemets because of the complexty ad sze of the software. Software developmet orgazatos requre more techcal staff or persoel ad the cost of such software may be mllos dollars. Errors cost estmato ca be very serous deed [7]. Ths s because over estmatg the cost of software project leads to too may resources allocated to the project ad uder estmatg the cost of the project leads to lttle resources allocated to the project. Therefore, accurate estmato of the cost before the start-up of a project s essetal for both the developers ad the clets.the most mportat measure of effcecy of ay software egeerg projects s ts ablty to reach completo o tme ad o budget regardless of ay evromet the software may operate wth. Software cost estmato s mportat whe developg a system ad has bee a vtal but dffcult task sce the cepto of computer, [7]. Software costs are maly refers to the effort spet a developmet of a software project, whch s creasgly cocered by the developers ad the users. If we could make a good estmato of the software workload before the developmet, the software developmet maagers may mprove the qualty of software products through cotrollg the developmet tme ad budget durg software developmet process,[4].most of estmato models attempt to geerate a effort estmate, whch ca the be coverted to the project durato ad cost. Although effort ad cost are closely related, they are ot ecessarly related by a smple trasformato Fucto. II. STATEMENT OF THE PROBLEM Ths paper addresses agle effort estmato framework wth software products that address the most frequetly asked questos software developmet whch cludes: [] How much effort s requred to complete each actvty? [2] What s the tme s eeded to complete each actvty? [3] The total cost of each actvty? www.thejes.com The IJES Page 30

Some Partcles Swarm Optmzato-Based... [4] Whe such questos are posted, a lot of optos are avalable as soluto; ths study therefore set out to desg a Partcle swarm Optmzato-Based frame work that would be used to estmate efforts for agle software. III. AIM AND OBJECTIES OF THE STUDY The am of ths paper s to study a software cost estmato frame work for agle processes usg partcle swarm optmzato algorthms. The specfc objectves of the study are to: [] Idetfy projects that use agle processes software developmet, determe the effort ad schedule estmatos that yeld the hghest degree of accuracy ad relablty (Optmzato); ad [2] Provde a framework to determe optmum durato, effort ad schedule estmato requred to buld agle software usg a partcle swarm optmzato model. I. THEORETICAL FRAME WORK Accordg to [0] a software project s a project wth hgh ucertaty, so that software project success s relatvely low. [3]. Notes that software developmet s a hghly complex ad upredctable task sce may specalzed groups are typcally requred to collaborate o oe project.the ablty to accurately ad cosstetly estmate software developmet efforts, especally early stages of the developmet lfe cycle, s requred by the project maagers plag ad coductg software developmet actvtes because the software prce determato, resource allocato, schedule arragemet ad process motorg are depedet upo t. Ths ssue le the fact that the software developmet s a complex process due to the umber of factors volved, cludg the huma factor, the complexty of the product that s developed, the varety of developmet platforms, ad dffculty of maagg large projects, [3].Accordg to [7] project cost estmato ad project schedulg are ormally carred out together. The costs of developmet are prmarly the cost of effort volved, so the effort computato s used both the cost ad schedule estmate. For most projects, the domat cost s the effort cost. Software effort maly refers to the effort spet a developmet of a software project, whch s creasg cocered by the developers ad the users [4].Software cost estmato s ot a stadaloe actvty. The estmates are derved large from the requremets of the project, ad wll be strogly affected by the tools, process, ad ther attrbutes assocated wth the project [7]. Accordg to research coducted by [6] the Iformato System developmet process, regardless of the methodology adopted, requres effectve maagemet ad plag. A large part of ths plag s the creato of estmates at the begg of a project so that resources ca be approprately allocated. Estmatg the cost of a IS developmet project s oe of the most crucal tasks for project maagers [9] but despte ths t cotues to be a weak lk the IS developmet feld [2]. Iformato System (IS) developmet projects have a log hstory of beg delvered over tme, over budget ad falg to satsfy requremets. The ma factors that are typcally estmated at the begg of a IS developmet project are: cost, sze, schedule, people resources, qualty, effort, resources, qualty, effort, resources, mateace costs, ad complexty. Estmates are produced ad used for a varety of purposes ad a study by [] shows the most commo uses. These are: to schedule projects for mplemetato, to quote the charges to users for projects, to staff projects, to audt project success, to cotrol or motor project mplemetato, to evaluate project estmators, ad to evaluate project developers. Accordg to [8] software cost estmato s the process of gaugg the amout of effort requred to buld software project. The effort s usually represeted Perso- Moth (PM) ad t depeds upo both the sze as well as the complexty of the gve software project. The PM ca be coverted to dollar cost. The model was desged such a maer that accommodates the COCOMO model ad mproves ts performace. It also ehaces the predctablty of the software cost estmates. The model was tested usg two datasets COCOMO dataset ad COCOMO NASA 2 dataset. The paper was ttled a adaptve leag approach to software cost estmato. There so may methodologes troduced software developmet. Ideed, 25 years, a large umber of dfferet approaches to software developmet have bee troduced, of whch oly few have survved to use today []. Rght ow, agle methodology s the most popular methodology software developmet. Agle methodology emerged due to evolvg ad chagg software requremets [4]. As ths approach the requremet s ot always feasble there s also a eed for flexble, adaptve ad agle method, whch allow the developers to make late chage the specfcatos [].Accordg to [6], agle software developmet methods lke extreme programmg try to decrease the cost of chage ad therewth reduce the overall developmet costs. Agle methods try to avod the defcts of classc software developmet procedures.mostly, the followg methodologes are cosdered to reach ths am: short release cycles, smple desg, cotuous testg, ad refactorg, collectve owershp, codg stadard ad cotuous tegrato. Other characterstc of agle methodologes accordg to [2] cludes: Effort ad schedules estmates ormally are computed usg www.thejes.com The IJES Page 3

Some Partcles Swarm Optmzato-Based... parametrc models accordg to the sze of the software project, whose sze s measured by les of code (LOC) or fucto pots ad so forth. There are four basc steps software project effort ad schedule estmato. They ca be summarzed ad follows:. METHODOLOGY Models of software cost/effort are approaches that detfy key cotrbutors to cost ad effort geeratg mathematcal formulae that assocate these attrbutes to cost ad effort. [5] Idetfy may quattatve models from dfferet studes by dfferet papers whch are used to estmate effort requred to develop a software system. For the purpose of ths study, the paper cosdered Partcle Swarm Optmzato (PSO) model. User stores from agle velocty ad project durato wll be optmzed ad better framework for agle effort estmato wll be acheved. I. OPTIMIZATION PROBLEM AND MODEL FORMULATION [] Basc compoet of a optmzato problem are: [2] A objectve fucto expresses the ma am of the model whch s mmzed. [3] A set of ukows or varables cotrol the value of objectve Fucto [4] Objectve fucto s the mathematcal fucto that s mmzed. Ths s the selecto of desg varable, objectve fucto ad model of the desg. A desg varable, that takes a umerc value, wll be cotrolled from the pot of vew of the desg. Desg varable are bouded, that s, t wll have a maxmum ad mmum value. A objectve s the umercal value that s mmzed.. FUNCTIONS THAT ARE MINIMIZED I order to estmate durato eeded to complete a project, t s calculated as T ( Days ) 3. I E ( ES ) ( Days ) 3.2 ( ) D The ut of T ths calculato s Days whch ca be the coverted to moths, dvdg by umber of workg days per moth. Thus T ( ES ) D ( ) ( ( W ) Moths Where WD s work days per moth, s the project velocty, E s the effort, ES s the effort of user story, T s the project durato or tme ad D s crtcal ad s called project decelerato. I. PARTICLES SWARM OPTIMIZATION (PSO) Partcle Swarm Optmzato (PSO) s a populato based search algorthm developed, the techque s based o the movemet ad tellgece of swarms. It uses a cocept of socal teracto for problem solvg. The Populato cotas set of partcles each of whch represets a soluto for a gve optmzato problem. These partcles are ormally talzed radomly as most evolutoally computato techques (for example, geetc algorthms). Durg the evolutoary process, each partcle, based o some evaluato crtero, updates ts ow posto wth certa velocty. The velocty s compled based o both the best experece of the partcle tself ad that of the etre populato. Ths update process s repeated for a umber of geeratos. The update process stops ether whe the objectves are reached or whe the maxmum umber of geerato s reached. Summary of geeral cocept of PSO s: [] It cossts of a swarm of partcles. [2] Each partcle resdes at a posto the search space. [3] The ftess of each partcle represets the qualty of ts posto. [4] The partcles fly over the search space wth a certa velocty. [5] Each partcle s treated as a pot a N dmesoal space whch adjusts ts flyg experece of other partcles. [6] The velocty (both drecto ad speed) of each partcle s flueced by ts ow posto foud so far ad the best soluto that was foud so far by ts eghbours. [7] Evetually the swarm wll coverge to optmal posto. www.thejes.com The IJES Page 32

Loop utl partcle exhaust Loop utl maxmum terato Some Partcles Swarm Optmzato-Based... Start Italze partcles wth radom posto ad velocty vectors For each partcle s posto X evaluate ftess Stop: gve Gbest as optmal soluto Fg. 3.0 Partcle Swarm Optmzato (PSO) Flowchart I f ftess (X) better tha ftess (Pbest) the Pbest=X Set best of Pbest as Gbest Update partcles elocty usg equato 3.4 ad posto usg equato 3.5 k k c Pbest X c r Gbest X r 3.4 2 2 k X X 3.5 I a physcal -dmesoal search space, the posto ad velocty of each partcle are represeted as the vectors: X x,..., x ad v,..., v C ad C 2 are accelerato (weghg) factors kow as cogtve ad socal scalg parameters. Determe the magtude of the radom forces the drecto of Pbest ad Gbest. r ad r 2 are radom umbers betwee 0 ad. K s the terato dex The accelerato coeffcet should be set suffcetly hgh. Hgher accelerato coeffcets result less stable systems whch the velocty has a tedecy to explode. max was troduced to cotrol the velocty exposto.the motvato behd troducg the erta weght ( ) was the desre to better cotrol the scope of the search ad reduce the mportace of (or elmate) max. The erta weght ca be used to cotrol the balace betwee explorato ad explotato. Whe s bg, partcle swarm ted to global search whle they ted to local search whe t s small? Hece, sutable selecto of the erta weght ca provde a balace betwee global ad local explorato abltes ad thus requre less terato o average to fd the optmum. Wth the troducto of erta weght, the equato to update partcle velocty becomes: k Pbest X c r Gbest X k c r 3.6 2 2 Whle the equato to update partcle posto remas the same. X k X Performace Idcators o PSO Applcato: I the paper of software cost ad effort estmato, the performace dcators used s usually usg the Mea of Magtude of Relatve Error (M) or Predcto level (Pred) as accuracy referece. Therefore ths study, M was used to determe the effectveess of www.thejes.com The IJES Page 33

Some Partcles Swarm Optmzato-Based... PSO applcato. E s the effort ad the equato used for the computato was based o the Effort Mea Magtude of Relatve Error usg the equato: EM AE EE AE EM s the Effort Mea Magtude of Relatve Error, AE s the Actual Effort, EE s the Estmated Effort, s the umber of projects ad s a umber (No). computed as: AE EE AT www.thejes.com The IJES Page 34 3.7 s the magtude of relatve error ad s T s the Tme ad the Tme Mea Magtude of Relatve Error s determed from the equato: TM AT ET AT TM s Tme Mea Magtude of Relatve Error s, AT s the Actual Tme ad ET s the Estmated Tme. Is the Magtude of Relatve Error whch s computed the equto: AT ET AT II. DISCUSSION The summary of the results obtaed from the mplemetato of the partcle swarm optmzato framework to optmze the project durato (Tme) ad effort s show below. Table 4. shows the data obtaed from te past agle projects, ther respectve veloctes (), the work days per moth the projects, project decelerato (D) ad ther respectve actual effort. Estmated effort (EE) usg PSO framework from the mplemetato of the algorthm C-Sharp ad the computed Magtude of Relatve Error for effort s also preseted appedx. Table 4. appedx shows the project umber, agle project velocty ( ), Project work days, agle sprt sze, ad the actual efforts over te hstorcal completed agle projects, the estmated effort (EE) usg PSO framework ad the effort. Table 4.2 shows the actual tme over te agle past completed projects, the estmated tme usg PSO ad the Tme Magtude of relatve error ().The evaluato cossts comparg the accuracy of the estmated effort wth the actual effort. There are may evaluato crtera for software effort estmato; amog them the paper cosdered the most frequet oe the Magtude of Relatve Error () ad Mea Magtude of Relatve Error (M). The Effort Mea Magtude of Relatve Error (EM) ad Tme Mea Magtude of Relatve Error (TM) are defed as equato3.7 ad equato 3.8 respectvely. The Mea Magtude of Relatve Error (M) computes the average of over N projects. Usg equato 3.7, the computed value for EM was foud to be 0.988 whch s about 9.88% ad TM was 0.230 whch s 23.0%Geerally, the acceptable target value for M s 25%. It dcates that the for each project for the establshed estmato model should be less tha 25% o the average [5]. A software developmet effort estmato method wth a smaller M value tha the oe wth bgger M value gves better estmates tha a model wth a bgger M value. The M obtaed from the paper dcated that the M value for effort s 5.2% less tha the ormal establshed estmato model. Ths works coformty wth [5] that the less s the M value tha the M value of the establshed estmato model the more accurate s the effort III. CONCLUSION The level of complexty of software projects today has draw much atteto to the eed for methods of estmatg how much effort wll be requred, how log t wll take, ad how may people wll be eeded to buld software. Therefore, software costg should be carred out objectvely wth the am of accurately predctg the effort, tme ad staff level to develop software.accurate ad relable software project estmates such as tme, effort the early phase of software developmet s oe of the crucal objectves software project maagemet. IX. RECOMMENDATIONS After careful cosderatos of the results obtaed from the tables, the followg recommedatos are made: [] Developg software products should requre takg to cosderato factors such as evromet, sze of the products, project velocty, users stores ad the model to be used. [2] Because software sze s the key put for most software parametrc estmatg models, t s crtcal that accurate estmatg techques be used by agle software team stead of estmatg program sze based o opos of oe or more experts. 3.8

Some Partcles Swarm Optmzato-Based... [3] Due to heret lmtatos of o-parametrc models adopted by some agle developmet team, ths study recommeds that software developers should adopt the ewest models that wll gve relable effort estmato that s based o curret developmet. REFERENCES [] P. Abraham, O. S., Rokae & J.Warster. (2002). Agle software developmet method. Retreved October,203, from TT Home Page: http://www.vtt.f/f/publcatos/2002/478.pdf [2] R. Agarwal, M. Mumar, G. Yogesh, S. Mallck, R.M. Bharadwaj & D. Aatwar (200). Estmatg software projects. AGM SIGSOFT, Software Egeerg Notes. 26, 60-67. [3] I. Attarzedah & S.H. Ow (200). A ovel soft computg to crease the accuracy of software cost estmato. IEEE. [4] B. Baskeles,, U., Boyazc, B. Turam & A Beer. (2007). Software effort estmato usg mache learg methods. Computer Iformato Sceces ISCIS. IEEE. [5] A. Kaushk, R So. & A.K. So, (202). A Adaptve Learg Approach to Software Cost Estmato. 202 Natoal Coferece o Computg ad Commucato Systems (NCCCS). IEEE. [6] K. Cooboy & A. Ftzgeeral, (2004). Towards a Coceptual Framework for Agle Methods. Proc. AGM Workshop o Iterdscplary Software Egeerg Paper. [7] C. Joes (2007). Why Flawed Software Projects are ot Cacelled Tme. Cutter IT Joual, 6, 2-7. [8] M. Jorgese & M Shepperd. (2007). "A systematc Revew of Software Developmet Cost Estmato Studes". IEEE Trasacto o Software Egeerg,, 20-205. [9] J. Keug, R Jeffery. & B. Ktcheham,. (2004). The challege of troducg a ew software cost estmato techology to a small software orgasato. Proceedgs of the 2004 Australa Software Egeerg Coferece. Sydey, Australa. [0] T.B. Kusumasar,,, I. Supraa, S Suredro. &,H. Sastramhardja (20). Collaborato model of software developmet. 20 Iteratoal Coferece o Electrcal Egeerg ad Iformatcs. Badug, Idoesa. [] A.L. Lederer,& J. Prasad, (995). Perceptual ad formato system cost estmato. AGM SIGCPR Coferece o Supportg Teams, Groups, ad Leag Isde ad Outsde the IS Fucto REINENTING IS. Nashvlle Teessee. [2] G Mller,. (200). The Characterstcs of agle software processes. Proceedgs of the 39th It'l Cof. ad Exhbto o Techology of Object Oreted Laguages ad Systems. [3] K.S. Na, X. L,. J.T. Smso & K.Y.Km. (2004). ucertaty profle ad software project performace:a Cross Natoal Comparso. The Joural of System ad Software,70, 55-63. [4] M. Omar, S.L Syed-Abdullah. & A.Yas,. (2003). The Impact of Agle Approach o Software Cost Estmato. [5] R. Racovc, (2004). Towards a Methodology to Estmate Cost of Object-Oreted Software Developpmet Projects. ComSIS, (2) 73-94. [6] A. Schmetedorf, M Kuz. & R Dumke. (2008). Effort estmato for agle software developmet projects. 5th Software Software Measuremet Europea Forum. Mla. [7] I. Sommervlle. (2008). Software Egeerg. USA: Addso Wesley. [8] S. Zudd, T Kamal. & Z. Shahrukh, (202). A Effort Model for Agle Software Developmet. Advaces Computer Scece ad ts Applcato (ACSA), 2(), 35-324 APPENDIX Table 4. PSO Based Effort Project No Work Sprt D Actual PSO based Effort Effort Days Sze Effort (EE) 4.20 22.00 0.00 0.687 56.00 52.00 0.0256 3.70 2.00 0.00 0.703 202.00 97.00 0.0248 4.00 22.00 0.00 0.8789 73.00 78.00 0.0289 3.80 22.00 0.00 0.8868 33.00 325.00 0.0272 4.90 22.00 0.00 0.9034 24.00 2.00 0.0242 4.0 22.00 0.00 0.9034 339.00 347.00 0.0236 4.20 22.00 0.00 0.860 97.00 94.00 0.0309 3.80 22.00 0.00 0.8332 257.00 254.00 0.07 3.90 22.00 0.00 0.6750 84.00 85.00 0.09 4.60 22.00 0.00 0.7632 2.00 24.00 0.042 Table 4.2 shows the result of the PSO based or estmated tme usg PSO, the actual tme ad Magtude of Relatve Error () for tme over te completed projects. www.thejes.com The IJES Page 35

Table 4.2 Project Durato Some Partcles Swarm Optmzato-Based... Project No Actual Tme (Days) PSO based (Estmated tme) (Days) Tme. 63 62 0.059 2. 92 9 0.009 3. 56 57 0.078 4. 86 84 0.0232 5. 32 3 0.033 6. 9 93 0.0220 7. 35 34 0.0286 8. 93 9 0.025 9. 36 37 0.0278 0. 62 59 0.037 Table 4.3 Computed values of M Parameter M alue M % Effort 0.988 9.88 Tme 0.230 23.0 BIOGRAPHY Maga Ibrahm: Is a lecturer wth Adamawa State Uversty, Mub, Ngera. He s a masters studet the departmet of computer scece at Adamawa State Uversty, Mub, Ngera. He s a member of Ngera Computer socety, Member IEEE. He obtaed hs Bsc computer scece 2007 from Same Uversty Mub, Ngera. Hs areas of research terest are Computatoal Itellgece Software Computer Algorthms. Nachamada achaku Blamah :Is a Seor Lecturer wth the Uversty of Jos, Ngera. He obtaed hs Bachelors of Techology, Master of Scece, ad Doctorate degrees Computer Scece. Dr. Blamah s a member of the IEEE Computatoal Itellgece Socety ad the Computer Professoals (Regstrato Coucl of Ngera), ad hs research terests are maly the areas of computatoal tellgece ad mult aget systems. www.thejes.com The IJES Page 36