[SYLWAN., 158(6)]. ISI

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1 The proposl of Improved Inext Isomorphi Grph Algorithm to Detet Design Ptterns Afnn Slem B-Brhem, M. Rizwn Jmeel Qureshi Fulty of Computing nd Informtion Tehnology, King Adulziz University, Jeddh, SAUDI ARABIA e-mil: Astrt Design ptterns eing pplied more nd more to solve the softwre engineering diffiulties in the ojet oriented softwre design proedures. So, the design pttern detetion is widely used y softwre industries. Currently, mny solutions presented to detet the design pttern in the system design. In this pper, we will propose new one whih first; we will use the grph implementtion to implement oth the system design UML digrm nd the design pttern UML digrm. Seond, we will implement the edges for eh one of the oth two grphs in set of 4-tuple elements. Then, we will pply new inext grph isomorphi lgorithm to detet the design pttern in the system design. Key Word: Design Pttern, 4-tuple, UML, Reltionl view, Inext, Grph isomorphism. 1. Introdution Design ptterns re desriptions of the equivlent Clsses, whih is the pproprite solution to the reurring prolems in the design. One we implement numer of ptterns when designing system, the relted informtion to the design pttern will not e longer ville. Therefore, it is essentil to detet the design pttern instnes in the system design to understnd the system or mintin it [1-3]. The design ptterns regrded s n expert design experienes. The experts' knowledge is represented in the forml 23 ptterns of GoF. Also, design pttern re onsidered s one of the reuse design tehniques. Then, the softwre industry hve een reused these experienes widely. As result of the presene of relile method to detet the design ptterns from system design, then novies will e suess in the softwre reengineering [4-7]. Mny softwre engineering prolems solved y the grph sed methods. Also, Design ptterns hve proved to e effetive in solving the prolems relted to the system design. to detet the design pttern in the system design using the grph sed pproh we must firstly onvert the UML digrm for oth: design pttern nd the system design into diret grph nd then determine whether the pttern grph exist extly in the system grph or not depend on the lssi onept of grph Isomorphi. Sometimes, we do not need to implement the design pttern ompletely in the system design. In some ses we need to know, how mny times design pttern is ompletely or prtilly existed in the system design [1-7]. In this pper, we proposed new solution to detet the different ses of existene of design pttern in system design. First, we will use the grph implementtion to implement oth the system design UML digrm nd the design pttern UML digrm. Seond, we will implement the edges for eh one of the oth two grphs in set of 4-tuple elements. Susequently, we will pply new inext grph isomorphi lgorithm to detet design pttern in system design. The rest of this pper is orgnized s follow: the relted work will reviewed in setion 2. In setion 3, we will present the prolem definition nd the proposed solution. In setion 4, we will vlidte the proposed solution. Finlly, we will present the onlusion from this pper nd the future work in setion Relted Work [SYLWAN., 158(6)]. ISI Indexed 90

2 This setion will disuss the previous work in deteting the design ptterns. To detet the design ptterns in the system design we will deide if the pttern is exist or not. The first method we tlk out ws proposed y Pnde et l. [1]. The first step of this method is pplying the proposed lgorithm to omposite the model grph to produe numer of deomposed grphs nd then try to pplying isomorphism mehnism to find the mthes etween these deomposed grphs nd the design ptterns. The drwk of this method is not overing ll the 23 ptterns of GoF. It is only exmined the ptterns tht mth to the omposed grph of order 2 or 3 nd the omplexity of this deomposition lgorithm is depend on the numer of nodes (it is O (n3) if the grph hs three nodes). So, omplexity will inresed in the systems with lrge model grph. Some pprohes lso deide tht if the design pttern prtilly exists in the system design. To detet the design ptterns, Gupt et l. [2] used the Normlized ross orreltion (NCC). They strted y writing the reltionship mtries of the reltionship grphs tht extrted from the UML digrm of the system design nd the design pttern. Then, they pply the NCC to disover the degree of similrity etween the two grphs (one for the system design nd the other for the design pttern) for the purpose of deteting the Design ptterns. The disdvntge of this method is, it is time onsuming to lulte eh reltionship mtrix distintly. Gupt et l [3] proposed grph mthing lgorithm sed on the A* lgorithm. The proposed lgorithm divided the mthing proess, 1) etween the design pttern grph (DPG) nd the model grph (MG), 2) etween the design pttern grph (DPG) nd the system grph (SG), into K phses. The vlue of K is depending on the minimum numer of nodes (M) in the two grphs used in mthing. It is seleted from the vlues etween 1 to M. The Prolem with this method, it is effetive only in the se of smll mounts of K vlues. Pnde et l[4] proposed new mthing lgorithm whih extrts the reltionship direted grphs from the UML digrms of system model nd design ptterns. Then they ttempt to disover the existent of design ptterns in the model grph using Depth-Node-Input Tle (DNIT). DNIT rrnges the vrious model grph reltionships nd the design pttern y depth. This method is time onsuming in the proess of reting the DNIT entities for the model grph nd for ll design ptterns grphs. Another pproh used the onept of the Boolen funtion to detet the ptterns. Gupt et l. [5] Offering new method tht detet the design pttern depend on the Boolen funtion. They trnsform the UML digrms of the model grph nd the design pttern into Boolen funtion with SOP form. Then, they detet the existene of the design ptterns y ompring the two Boolen funtions. The drwks of using this method re tht it not onsiders the deteting of design ptterns tht hve reltionship from node to itself suh s the singleton design pttern. Some pprohes identify the numer of design pttern instnes in the system. Pnde et l. [7] ttempted to detet the design ptterns nd its instnes y firstly, onstrut the deision tree using rowolumn elements for ll possile sugrphs djeny mtries of the system design grph. After tht, find the row-olumn elements of the design pttern djeny mtrix. Then, hek the isomorphi y trverse the deision tree to detet the row-olumn elements of tht design pttern. The limittion of this method ppers in the se of onstruting deision tree for lrge system design grph; it used huge numer of permuttions sugrphs nd will produe omplex tree tht onsuming lot of time in the trversl proess. M. Gupt et l. [8], they detet the design pttern y pplying grph mthing lgorithm where the mthing proess desries the stte spe illustrtion. The grph mthing lgorithm identifies the omplete su isomorphism for eh reltionship etween two grphs distintly. Then, they omine these distint outputs to detet the existene of the design ptterns or its lterntives. The mpping proess of this method is time onsuming. Gupt nd Pnde [9] propose new lgorithm to detet the design pttern in the soure ode depend on the sugrph isomorphism reltionl view. They ttempt to find the omplete su isomorphism etween the input grph (system under study) nd the design pttern grph to detet the existene of the design ptterns or its lterntives in the grph of system under study. It is time onsuming when find the mthes for eh reltion individully. Yu et l [10] detet the design ptterns y grph isomorphism etween system design nd the design pttern grph. They strt y identifying ll the ndidte nodes from system grph tht orrespond to the design pttern nodes nd then, selet some of them to rete su-grphs of system grph. Finlly, they find the isomorphi etween the design pttern nd them. This method disovers how muh instne of the design pttern in the system grph. This [SYLWAN., 158(6)]. ISI Indexed 91

3 method represents the reltionship etween lsses in the UML digrm of system model y ssigning weight to edges in the grph representtion, this weight desrie ll the reltionship etween tow verties. So, in lrge systems, it will e time onsuming to identify the reltionship for eh edge nd then lulte its weight. All the prolems of the previous work re summrized in Tle Prolem Sttement nd the proposed Solution Following is the prolem tken up in this pper sed on review of the literture [1-7]. How to detet the existene of the design pttern ompletely or prtilly or non-exist in the system design nd how mny times it exists in the system design? This proposed solution will illustrte the implementtion of the system design nd the design pttern UML digrms into two grphs nd the pplying the proposed lgorithm to detet the ompletely or prtilly existene of the design pttern nd how mny opy of tht pttern in the system digrm UML. 3.1 The implementtion of the system design nd the design pttern UML digrms First, we implement the system design nd the design pttern UML digrms s two direted grphs. System grph (SG) is orresponded to the system design UML digrm nd the design pttern grph (DPG) is orresponded to the design pttern UML digrm. Figures 1 to 5 show the exmple of system design nd design ptterns UML with the orresponding SG nd DPG respetively. Eh one of these two grphs hs set of edges tht represent the reltionships etween tow verties nd the self-loop for vertex. The SE is the set of edges tht implements the SG nd the DPE is the set of edges tht implements the DPG where eh element in the SE nd DPE is 4-tuples (A, B, X, Y).The first 2 elements of the 4-tuples A nd B indite the two verties of the edge. The third element X indites the type of reltionship etween A nd B where, vlue1 indites the Diret Assoition, vlue 2 indites the dependeny nd vlue 3 indites the generliztion reltionship. The forth element of the 4-tuples is Y whih indites y 1 if the self-loop existene (if A equl B) otherwise, it will e 0. The dvntge of dding the self-loop element is to detet the Singleton Design Pttern where this element indites if one vertex elongs to itself to mke reltion. We n simply understnd the SE nd the DPE sets y implementing these edges y tle of 4 olumns to implement A, B, X nd Y nd N row where N indites the numer of edges in the grph. 3.2 The New Algorithm to detet the design pttern in the system design The proposed lgorithm will detet the design pttern depend on find ll the possiility of design pttern existene or prt of it in the system design y ompring the 4-tuples of SE nd DPE to stisfy the vlue of X nd Y. the resulted possiilities must form onneted omponent of the SG. SE nd DPE sets re the Input to the lgorithm. The output is the sttements tht indite if the pttern exists ompletely or prtilly with the numer of how muh opies of it in the system design. The tle Poss ws used to sve ll the possiilities of edges from SE in DPE. The numer of olumns of Poss indites the numer of edges of the DPE where it will e s the DPE if the pttern exists ompletely or less thn DPE if the pttern exists prtilly. The numers of rows of Poss indite the numer of opies tht the design pttern exists ompletely or prtilly. Figure 6 shows the steps of the new lgorithm. The output of the proposed lgorithm is tegorized into one of 3 ses s following susetions: 3.3.1The Design pttern exists in the SG with the numer of times it exists This se will our if the numer of olumns of Poss equl to the numer of edges of the DPE (i.e. it will e equl DPE ). The numer of how muh the pttern ompletely exists in the SG will indite y the numer of rows of Poss. If we implement the new lgorithm on the System design of Figure 1 to detet the Fçde design pttern with presented with Figure 2 then: SE= {(,,1,0),(,,1,0), (,,1,0),(d,,3,0),(e,,3,0),(d,,2,0)} [SYLWAN., 158(6)]. ISI Indexed 92

4 DPE= {(P, Q, 1, 0)} After pplying the lgorithm on the SE nd DPE, the Poss will ontin: (,,1,0) (,,1,0) (,,1,0) Then the output will e: The design pttern ompletely exists in the System design with 3 times. Also, if we implement the new lgorithm on the System design of Figure 1 to detet the Prototype design pttern with presented with Figure 4 then: SE= {(,,1,0),(,,1,0), (,,1,0),(e,,3,0),(d,,2,0)} DPE= {(,,1,0),(,,3,0)} After pplying the lgorithm on the SE nd DPE, the Poss will ontin: (,,1,0) (d,,3,0) (,,1,0) (e,,3,0) (,,1,0) (d,,3,0) Then the output will e: The design pttern ompletely exists in the System design with 3 times. We exlude the 3 rows of Poss: (,,1,0) (e,,3,0) (,,1,0) (d,,3,0) (,,1,0) (e,,3,0) euse the first two rows re not onneted, lso the three rows not stisfy the equlity ondition with the elements of DPE whih is the DPE 4-tuple elements hs the sme node in element 2 () The Design pttern prtilly exists in the SG with the numer of times it exists. This se will our if the numer of olumns of Poss less thn the numer of edges of the DPE (i.e. it will e less thn DPE ) ut not equl zero. The numer of how muh the pttern prtilly exists in the SG will indite y the numer of rows of Poss. If we implement the new lgorithm on the System design of Figure 1 to detet the Composite design pttern with presented with Figure 5 then: SE= {(,,1,0),(,,1,0), (,,1,0),(d,,3,0),(e,,3,0),(d,,2,0)} DPE={(,,1,0),(,,3,0),(,,3,0)} Firstly, with n=3 edge the Poss will empty euse ll the possiility not mthing the equlity ondition with the elements of DPE whih is the DPE 4-tuple elements hs the sme node in element 2 (). Also, the first two possiilities re not onneted. (e,,3,0) (d,,3,0) (,,1,0) (e,,3,0) (d,,3,0) (,,1,0) (e,,3,0) (d,,3,0) (,,1,0) After tht, if we derese n y 1, we will find 7 possiilities: (e,,3,0) (d,,3,0) (d,,3,0) (,,1,0) (d,,3,0) (,,1,0) (d,,3,0) (,,1,0) (e,,3,0) (,,1,0) (e,,3,0) (,,1,0) (e,,3,0) (,,1,0) Then Poss will ontin the 3 rows: (d,,3,0) (,,1,0) (d,,3,0) (,,1,0) (e,,3,0) (,,1,0) The output will e: The design pttern prtilly exists in the System design with 3 times. The rest 4 rows not mthing the equlity ondition with the elements of DPE whih is the DPE 4-tuple elements hs the sme node in element 2 (). [SYLWAN., 158(6)]. ISI Indexed 93

5 3.3.3 The Design pttern dose not exists in the SG. This se will our if Poss is empty (No rows or olumns). Then, the pttern dose not exists in SG. If we implement the new lgorithm on the System design of Figure 1 to detet the Singleton design pttern with presented with Figure 3 then: SE= {(,,1,0),(,,1,0),(,,1,0),(d,,3,0),(e,,3,0),(d,,2,0)} DPE= {(A, A, 1, 1)} After pplying the lgorithm on the SE nd DPE, the Poss will e empty nd then the output will e: the design pttern does not exist in the system design. 4. Vlidtion Of The Proposed Solution To vlidte the new Isomorphi lgorithm we using n online questionnire divided into 4 prts for the gols: 1. The effiieny of the proposed solution: This gol vlidte tht the new Isomorphi grph lgorithm is effiient in deteting the design pttern. 2. The usility of the proposed solution: This gol vlidte tht the new Isomorphi grph lgorithm is esy to use. 3. The understndility of the proposed solution: This gol vlidte tht the new Isomorphi grph lgorithm is esy to understnd. 4. The reliility of the proposed solution: This gol vlidte tht the new Isomorphi grph lgorithm is overing ll the ses out the existene of the design pttern in the system design or not.also, to vlidte tht this new Isomorphi grph lgorithm is le to lulte the numer of times the design pttern existene ompletely or prtilly in the system design. Eh prt onsists of 5 -five level sling questions interrelted to eh other to prove the vlidity of one gol. Liker sle is rnging from 1 to 5 s following: very low effet inditing 1; low effet inditing 2; nominl/verge effet inditing 3; high effet inditing 4; very high effet inditing 5. The dt is nlyzed sttistilly to vlidte the proposed solution. 4.1 Findings This setion will present the findings fter nlyzing the responses to the questions of eh gol individully. Cumultive Sttistil Anlysis of Gol 1 (Effiieny) It is essentil to prove tht the new Isomorphi grph lgorithm is effiient in deteting the design pttern. In order to prove the effiieny of the proposed solution, we must firstly prove the effiieny of su-issues strongly relted nd ffeted the effiieny of the new solution. These issues re: the type of lgorithm whih is n Isomorphi grph Algorithm, the UML digrm implementtion for oth system design nd design pttern s diret grph to represent the reltionl view s pre-step for the new solution, implementtion of edges s set of 4-tuples elements for oth the system grph nd design pttern grph, dding the self-loop to filitte detet the Singleton Design Pttern nd the reltionship indition elements in implementing edges of oth the system grph nd design pttern grph. The responses umultive nlysis results for the gol 1 re summrized in Tle 2 nd Figure 7 whih present the nlysis results for the five questions of gol 1. As we shown from figure 7 nd Tle 2 out the umultive desriptive nlysis of gol 1, it is lerly tht 38.67% of the responses find tht the new Isomorphi lgorithm is high effiient nd 36.67% of them find tht our proposed solution is very high effiient in deteting the design pttern in the system design. But, 0.67% of them find this solution low effiient. Where, 24% find the effiient of this solution is norml. [SYLWAN., 158(6)]. ISI Indexed 94

6 Cumultive Sttistil Anlysis of Gol 2 (Usility) It is essentil to prove tht the new Isomorphi grph lgorithm is usle in deteting the design pttern. In order to prove the usility of the proposed solution, we must firstly prove the usility of suissues strongly relted nd ffeted the usility of the new solution. These issues re the sme with suissues of gol1 tht mentioned previously. The responses umultive nlysis results for the gol 2 re summrized in Tle 3 nd Figure 8 whih present the nlysis results for the five questions of gol 2. As we shown from figure 8 nd Tle 3 out the umultive desriptive nlysis of gol 2, it is lerly tht 44.67% of the responses find tht the new Isomorphi lgorithm is high usle nd 36% of them find tht our proposed solution is very high usle in deteting the design pttern in the system design. Where, 19.33% of them find this solution norml usle. Cumultive Sttistil Anlysis of Gol 3 (Understndility) It is essentil to prove tht the new Isomorphi grph lgorithm is understndle to deteting the design pttern. In order to prove the understndility of the proposed solution, we must firstly prove the understndility of su-issues strongly relted nd ffeted the understndility of the new solution. These issues re the sme with su-issues of oth, gol 1 nd 2 tht mentioned previously. The responses umultive nlysis results for the gol 3 re summrized in Tle 4 nd Figure 9 whih present the nlysis results for the five questions of gol 3. As we shown from figure 9 nd Tle 4 out the umultive desriptive nlysis of gol 3, it is lerly tht 41.33% of the responses find tht the new Isomorphi lgorithm is very high understndle nd 40% of them find tht our proposed solution is high understndle in deteting the design pttern in the system design. Where, 18.67% of them find this solution norml understndle. Cumultive Sttistil Anlysis of Gol 4 (Reliility) It is essentil to prove tht the new Isomorphi grph lgorithm is relile in deteting the design pttern. In order to prove the reliility of the proposed solution, we must firstly prove the reliility of su-issues strongly relted nd ffeted the reliility of the new solution. These issues re differing from su-issues of gol 1, 2 nd 3 tht mentioned previously. These su issues re: the ility of the proposed solution to detet the ompletely nd prtilly existene ses, the non-existene of the design pttern in the system design, nd its ility to lulte the numer of times the design pttern ompletely or prtilly existene in system design. The responses umultive nlysis results for the gol 4 re summrized in Tle 5 nd Figure 10 whih present the nlysis results for the five questions of gol 4. As we shown from Figure 10 nd Tle 5 out the umultive desriptive nlysis of gol 4, it is lerly tht 46% of the responses find tht the new Isomorphi lgorithm is very high relile nd 44.67% of them find tht our proposed solution is high relile in deteting the design pttern in the system design. Where, 9.33% of them find this solution reliility is norml. Cumultive nlysis for ll the gols of the new solution The responses umultive nlysis results for the 4 gols of the proposed solution re summrized in Tle 6 nd figure 11. As we shown from Figure 11 nd Tle 6 out the umultive desriptive nlysis of ll the gols, it is lerly tht 42% of the responses rnk the new Isomorphi lgorithm s high nd 40% of them rnk it s very high sle in deteting the design pttern in the system design.but, 0.17% of them rnk it s low sle while, 9.33% of them rnk this solution s norml sle. 5. Conlusion nd Future Work The uthors of this pper proposed new solution to detet ll the possile ses of exist the design pttern or not in the system design. The grph implementtion ws used to implement oth the system design UML digrm nd the design pttern UML digrm. Then, the edges for eh one of the oth two [SYLWAN., 158(6)]. ISI Indexed 95

7 grphs re implemented s set of 4-tuple elements. Lstly, the new inext grph isomorphi lgorithm ws pplied on the two sets to detet the design pttern in the system design. This solution solved the prolems of the relted work nd detets the exist or non-exist of ll the 23 ptterns of GoF nd lulte how mny times the design pttern exist prtilly or ompletely In the future, the uthors pln to implement the proposed solution progrmmtilly s n open soure tool to detet the design pttern. Referenes [1] A. Pnde, M. Gupt nd A.K. Tripthi, A New Approh for Deteting Design Ptterns y Grph Deomposition nd Grph Isomorphism, in Pro. 3rd Interntionl Conferene IC3, Indi, 2010, pp [2] M. Gupt, A. Pnde, R. Singh Ro, nd A.K Tripthi, "Design Pttern Detetion y normlized ross orreltion," in Pro. IEEE Interntionl Conferene on Methods nd Models in Computer Siene (ICM2CS), Indi, 2010, pp [3] M. Gupt, R. Singh Ro nd A.K. Tripthi, "Design Pttern Detetion using inext grph mthing," in Pro. IEEE Interntionl Conferene on Communition nd Computtionl Intelligene (INCOCCI), Indi, 2010, pp [4] A. Pnde, M. Gupt nd A.K. Tripthi, "DNIT A new pproh for design pttern detetion," in Pro. IEEE Interntionl Conferene on Computer nd Communition Tehnology (ICCCT), Indi, 2010, pp [5] A. Pnde, M. Gupt nd A.K. Tripthi,"Design pttern mining for GIS pplition using grph mthing tehniques," in Pro. 3rd IEEE Interntionl Conferene on Computer Siene nd Informtion Tehnology (ICCSIT), Indi, 2010, pp [6] M. Gupt, A. Pnde nd A.K. Tripthi, Design ptterns detetion using SOP expressions for grphs, ACM SIGSOFT Softwre Engineering Notes, vol. 36, pp. 1-5, Jn [7] A. Pnde, M. Gupt nd A.K. Tripthi, " A Deision Tree Approh for Design Ptterns Detetion y Sugrph Isomorphism, in Pro. Interntionl Conferene ICT 2010, Indi, 2010, pp [8] M. Gupt, R. Singh Ro, A. Pnde nd A.K. Tripthi, Design Pttern Mining Using Stte Spe Representtion of Grph Mthing, in Pro. 1 st Interntionl Conferene on Computer Siene nd Informtion Tehnology CCSIT, Indi, 2011, pp [9] M. Gupt nd A. Pnde, Design Ptterns Mining using Sugrph Isomorphism: Reltionl View, Interntionl Journl of Softwre Engineering nd Its Applitions, vol. 5, pp , Apr [10] Y. Dongjin; J. Ge; W. Wu, "Detetion of design pttern instnes sed on grph isomorphism," in Pro. 4th IEEE Interntionl Conferene on Softwre Engineering nd Servie Siene (ICSESS), Chin, 2013, pp d e d e d e d e Diret Assoition Generliztion Dependeny System Grph UML digrm of the system SE= {(,,1,0),(,,1,0),(,,1,0),(d,,3,0),(e,,3,0),(d,,2,0)} design Figure 1 UML digrm of the system design nd its SG nd SE [SYLWAN., 158(6)]. ISI Indexed 96

8 Fde P Susystem Clsses Design Pttern UML of Fçde Design Grph Pttern DPE= {(P,Q,1,0) } Figure 2 UML digrm of the Fçde design pttern nd its DPG nd DPE Q Diret Assoition A Diret Assoition UML of Singleton Design Pttern Design Pttern Grph DPE={(A,A,1,1)} Figure 3 UML digrm of the Singleton design pttern nd its DPG nd DPE Diret Assoition Generliztion Design Pttern Grph UML of Prototype Design DPE={(,,1,0),(,,3,0)} Pttern Figure 4 UML digrm of the Prototype design pttern nd its DPG nd DPE Diret Assoition Generliztion Design Pttern Grph UML of Composite Design DPE={(,,1,0),(,,3,0),(,,3,0)} Pttern Figure 5 UML digrm of the Composite design pttern nd its DPG nd DPE [SYLWAN., 158(6)]. ISI Indexed 97

9 Input: SE, DPE Output: The existene of Design pttern ompletely or prtilly with the numer of how muh opies of it in the SG or not Steps: n= PGE //n is the numer of DPE elements Poss =0 // the Poss Initil s empty tle WHILE (n 0) DO: Fined ll the possiilities of onneted omponent from SE with n Edges where these edges must stisfy the equlity ondition with the 4 element of eh 4-tuples in DPE If Poss >0 Then EXIT WHILE //the design pttern exist ompletely or prtilly Else n=n-1 // derese the numer of edge of DPE y 1 to find prtilly exists of Design Pttern END WHILE Poss_ olumns _Count= numer of olumns of Poss Poss_ rows _Count= numer of rows of Poss //output If (Poss_ olumns _Count = DPE ) //se1 Then: (Print The design pttern ompletely exists in the System design with + Poss_ rows _Count+ times ) Else If (Poss_ olumns _Count < DPE ) //se2 Then: (Print The design pttern prtilly exists in the System design with + Poss_ rows _Count+ times ) Else If (Poss_ olumns _Count =0 && Poss_ rows _Count=0) //se3 Then: (Print The design pttern does not exist in the System design ) Figure 6 the new lgorithm to detet the design pttern in the system design. Figure 7 Perentge Distriutions for Gol 1 [SYLWAN., 158(6)]. ISI Indexed 98

10 Figure 8 Perentge Distriution for Gol 2 Figure 9 Perentge Distriution for Gol 3 Figure 10 Perentge Distriution for Gol 4 [SYLWAN., 158(6)]. ISI Indexed 99

11 Figure 11 Perentge Distriution for ll Gols Pper Title Tle 1 Summrized relted work prolems Prolems A New Approh for Deteting Design Ptterns y Grph Deomposition nd Grph Isomorphism [1] Design Pttern Detetion y Normlized Cross Correltion [2] Design Pttern Detetion Using Inext Grph Mthing [3] DNIT A New Approh for Design Pttern Detetion [4] Design Pttern Mining for GIS Applition Using Grph Mthing Tehniques [5] Design ptterns detetion using SOP expressions for grphs [6] A Deision Tree Approh for Design Ptterns Detetion y Sugrph Isomorphism [7] Design Pttern Mining Using Stte Spe Representtion of Grph Mthing [8] Design Pttern Mining Using Stte Spe Representtion of Grph Mthing [8] Design Ptterns Mining using Sugrph Isomorphism: Reltionl View [9] Detetion of Design Pttern Instnes Bsed on Grph Isomorphism [10] Not over ll the 23 ptterns of GoF Complex for grph with lrge numer of nodes. time onsuming to lulte eh reltionship mtrix distintly Not effiient when using lrge vlues of K. Time onsuming in onstruting DNIT Cn t use in the sitution tht the system design doesn t hve the pttern. not identify ptterns with self-reltionship for lrge system design grphs: Produe omplex tree Time onsuming The mpping proess is time onsuming Time onsuming when find the mthes for eh reltion individully. Time onsuming to identify the reltionship for eh edge nd then lulte its weight. Not over ll the 23 ptterns of GoF Complex for grph with lrge numer of nodes. Tle 2 the umultive nlysis results for gol 1. Q# Very low Low Nominl/Averge High Very high Totl Q1 0.00% 3.33% 23.33% 36.67% 36.67% % Q2 0.00% 0.00% 16.67% 60.00% 23.33% % Q3 0.00% 0.00% 20.00% 33.33% 46.67% % [SYLWAN., 158(6)]. ISI Indexed 100

12 Q4 0.00% 0.00% 30.00% 30.00% 40.00% % Q5 0.00% 0.00% 30.00% 33.33% 36.67% % Totl Avg. 0.00% 0.67% 24.00% 38.67% 36.67% % Tle 3 the umultive nlysis results for gol 2. Q # Very low Low Nominl/Averge High Very high Totl Q6 0.00% 0.00% 20.00% 53.33% 26.67% % Q7 0.00% 0.00% 16.67% 43.33% 40.00% % Q8 0.00% 0.00% 16.67% 50.00% 33.33% % Q9 0.00% 0.00% 23.33% 23.33% 53.33% % Q % 0.00% 20.00% 53.33% 26.67% % Totl Avg. 0.00% 0.00% 19.33% 44.67% 36.00% % Tle 4 the umultive nlysis results for gol 3. Q # Very low Low Nominl/Averge High Very high Totl Q % 0.00% 16.67% 43.33% 40.00% % Q % 0.00% 13.33% 53.33% 33.33% % Q % 0.00% 16.67% 40.00% 43.33% % Q % 0.00% 20.00% 26.67% 53.33% % Q % 0.00% 26.67% 36.67% 36.67% % Totl Avg. 0.00% 0.00% 18.67% 40.00% 41.33% % Tle 5 the umultive nlysis results for gol 4. Q # Very low Low Nominl/Averge High Very high Totl Q % 0.00% 16.67% 40.00% 43.33% % Q % 0.00% 16.67% 30.00% 53.33% % Q % 0.00% 6.67% 50.00% 43.33% % Q % 0.00% 3.33% 46.67% 50.00% % Q % 0.00% 3.33% 56.67% 40.00% % Totl Avg. 0.00% 0.00% 9.33% 44.67% 46.00% % Tle 6 the umultive nlysis results for ll gols. Q # Very low Low Nominl/Averge High Very high Totl Gol % 3.33% % % % % Gol % 0.00% 96.67% % % % Gol % 0.00% 93.33% % % % Gol % 0.00% 46.67% % % % Totl Avg. 0.00% 0.17% 17.83% 42.00% 40.00% % Authors profiles [SYLWAN., 158(6)]. ISI Indexed 101

13 M. Rizwn Jmeel Qureshi- Assistnt Professor t Fulty of Computing & Informtion Tehnology, King Adulziz University, mjor in CBD nd gile Afnn Slem Brhem- Mster student in IT Deprtment t King Adulziz University, interested in Tehnology Mngement, Computer Networks nd Glol Softwre Engineering. [SYLWAN., 158(6)]. ISI Indexed 102