EXPERIMENTAL COMPARISONS OF ENTITY-RELATIONSHIP AND OBJECT-ORIENTED DATA MODELS ABSTRACT INTRODUCTION

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1 EXPERIMENTAL COMPARISONS OF ENTITY-RELATIONSHIP AND OBJECT-ORIENTED DATA MODELS Peretz Shoval Iformatio Systems Program, Departmet of Idustrial Egieerig ad Maagemet Be-Gurio Uiversity of the Negev, Beer-Sheva ISRAEL ( fax: ) ABSTRACT The exteded etity-relatioship () model is beig "threateed" by the object-orieted () approach, which peetrates ito the areas of system aalysis ad data modelig. The issue of which of the two data models is better for data modelig is still a ope questio. We address the questio by coductig experimetal comparisos betwee the models. The results of our experimets reveal that: a) schema comprehesio: terary relatioships are sigificatly easier to comprehed i the model tha i the model; b) the model supasses the model for desigig uary ad terary relatioships; c) time: it takes less time to desig schemas; d) prefereces: the model is preferred by desigers. We coclude that eve if the objective is to implemet a database schema, the followig procedure is still recommeded: 1) create a coceptual schema, 2) map it to a schema, ad c) augmet the schema with behavioral costructs that are uique to the approach. INTRODUCTION The object orieted () approach has spread ito various areas of computig that iclude ot oly programmig, but also systems aalysis ad desig, database maagemet, amog others. There is o doubts about the advatages of the 00 approach for programmig, i that it supports software reuse ad iformatio hidig,. However, the superiority of approach i earlier stages of software developmet, i.e., system aalysis ad data modelig, has ot as yet bee prove. I cocetrate o data modelig (or coceptual desig), a activity aimed at creatig a coceptual schema. This schema is usually represeted i a diagrammatic form, as it serves as a commuicatio tool betwee developers ad users. Oce approved by users, it is coverted ito a specific database schema, depedig o the data model ad DBMS used for implemetatio. This coversio is cosidered simple, beig a algorithmic, automatic process. The major problem, however, is to create a good coceptual schema that is sematically correct ad comprehesible. For may years, Etity-Relatioship, with its may extesios, geerally termed, has bee the most widely used model for coceptual desig. Recetly, the model has bee threateig to replace the model. I additio to static (structural) costructs of the model whose represetatio of data structure is somewhat equivalet to represetatio (e.g., object classes cosidered equivalet to etity ad relatioship types) - the approach models system behavior through "methods" that are attached to the object classes, with messages passig amog them. While this extra capability, ulike, provides more tha just a data structure model, it does ot ecessarily mea that should be replaced by, sice may ideed be "better" tha 00 for modelig the data structure. Takig ito cosideratio that a schema ca easily be mapped to a schema (Gogola et al 1993, Koratzky & Shoval 1994, Nachouki et al 1992, Narasimha et al 1993), it may be worthwhile to begi the process of data modelig with the desig of a coceptual schema, the covert it to a schema (if the objective is to implemet a DBMS), ad fially add the behavioral costructs. Such a "idirect" strategy for creatig a schema could be cosidered whe the model is regarded a "better" tha the model. "Better" ca be judged from various perspectives. I address this issue from four perspectives: a) comprehesio: uderstadability of schemas; b) desig quality: correctess of schemas; c) time to complete desig tasks; ad d) desigers' preferece of models. We have coducted two experimetal comparisos which compare the two models o these dimesios. The ext sectio discusses related studies, the followig two sectios overview the uderlyig models, the I describe the experimets ad their results, ad the fial sectio summarizes the results ad coclusios. RELATED STUDIES Various studies o the evaluatio ad compariso of data models have bee coducted. The earlier studies maily compared record-based models (hierarchical, etwork ad relatioal). Later o, became the most frequetly studied model. has bee compared with relatioal ad other recordbased models, as well as with other sematic models (e.g. Batra et al 1990, Juh & Nauma 1985). Some studies compared the data models from a desiger perspective i a attempt to fid out which yields more accurate ad precise schemas. Other studies compared the query laguages of the data models i order to determie the laguages by which the desigers compose queries with greater accuracy ad speed. Yet, other studies took a user perspective, attemptig to determie ease of 74

2 comprehesio. A survey of earlier studies ca be foud i Batra & Sriivasa (1992). Although the results of these studies are ot always clear-cut or cosistet, there is a tedecy to agree that HER is superior to other, record-based ad coceptual models. Oe of their geeral coclusios was that usability of data models should be evaluated by their ability to model relatioships, a poit that is stressed i our experimets Recetly we have begu to fid studies which evaluate the model o the basis of cotrolled experimets. For example, Agrawal ad Siha (1992) examied the ifluece of desigers' experiece i fuctioal aalysis ad task characteristics o quality of 00 schema desig. They foud out that the model does ot always lead to good results; the quality of result depeds o task characteristics. Palvia et al. (1992) compared, ER ad DSD models from a ed-user perspective, to see which schema is more comprehesible. Their subjects were MIS studets, ad their database schemas were trivial i terms of size ad complexity. Each subject received a versio of a database correspodig to oe data model, alog with 30 questios that evaluate comprehesio of the database. The total score o correct aswers was used as a measure of comprehesio. They cocluded that users of the model showed a sigificatly better uderstadig of the data tha users of the other two models. They admit, however, that their coclusio is weak, because comprehesio was measured o overall terms oly, ad suggest that future research be directed to studyig specific aspects of comprehesio, e.g., differet types of relatioships. Bock ad Rya (1993) reported o a compariso of ad models from a desiger perspective. They examied correctess of desig of eight types of costructs, ad measured correctess accordig to a gradig scheme developed by Batra et al. (1990). Their results idicated that is better for represetig attribute idetifiers, uary 1:1 ad biary m: relatioships, while there are o sigificat differeces for other dimesios. Also, they foud o differece i time to complete the tasks. Although these results are iterestig, i our opiio they have limited exteral validity, maily because the model they used (as i Kroeke 1992) represets relatioships oly by referece attributes i such a way that does ot eable to distiguish betwee a object that represets a biary relatioship from a object that represets a terary relatioship. THE UNDERLYING AND MODELS The objective of this sectio is to overview ad exemplify the models we use for experimetatio. Sice each of the models has may variats, we cofie ourselves to two specific types, that are sufficietly geeral to validate the results of the compariso. The model: As is more "stadard" tha, we oly preset a example (Figure 1) usig a diagrammatic otatio as i Elmasri ad Navathe (1994) ad Teorey et al. (1986). The model The model is still evolvig ad as yet o stadard has bee defied. The model that we use is based o O 2 (Deux et al 1991) ad ODE (Agrawal & Gehai 1989). By extedig the model we are able to show all the details of the schema o diagram, as would be expected at the coceptual desig stage. (Sice we focus o modelig data structure ad ot system behavior, methods are ot icluded.) A example of the schema is show i Figure 2, represetig the same reality as the diagram i Figure 1. 75

3 ar Sport Tru Figure 1: Diagram A object has attributes. (For brevity, we omit "class" ad simply say "object".) A attribute may be atomic or multi-valued, i which case the attribute ame is preceded by "set". A idetifier attribute of a object is uderlied. A attribute may refer to aother object, i which case the refereced object ame i writte i [ ] brackets ext to the respective attribute ame. This actually implies a bidirectioal relatioship betwee the objects, which is sigified i two complemetary ways: a) referece-attributes are icluded i each of the ivolved objects; b) a lik coects the two objects, with a idicatio of the relatioship cardiality. I the case of a 1 : relatioship betwee two objects, the object i the "1" side has a set referece attribute to the other object, ad i case of a m: relatioship both objects have set referece attributes. A attribute may be a tuple cosistig of multiple (value or referece) attributes, ad sigified by { } brackets. For example, the set producers {[Producer], umber of plats} of City. A m: relatioship ca also be represeted as a separate object, with referece attributes to the related objects. A terary or higher order relatioships is represeted as a separate object, liked to the other objects ivolved i the relatioship. The referece attributes i all objects are icluded. I the example, we have store facts about agets sellig vehicles to persos. Therefore, we used the objects Perso, Aget ad Vehicle, ad for the relatioship we created the object Sales. Each of the three origial objects has a set referece attribute to Sales, while Sales has a tuple cosistig of three referece attributes to those objects. The use of tuple of referece attributes i a object that represets a relatioship eables to determie the degree of the relatioship represeted by that object (e.g., whether it is biary or terary). Fially, object hierarchies are sigified by liks from the subtypes to the supertypes, similar to the otatio. 76

4 Producer ame address set wtiere_producig {[City], umber of plats) set vehicles_produced [Vehicle] 1 Aget ame address set vehicles_sold [Sales] City ame state set producers ([Producer], umber of plats) set ihabitats [Perso] mayor [Perso] 1 N Vehicle licece o. model set sold_by/to [Sales] produced_by [Producer] Sales sale ([Aget],(Perso], [Vehicle]) price ($) date_ol_sale Perso ss ame birth_date set tetephoe.umbers lives_i [City] mayor_of [City] set vehicles_bought [Sales] Car oilcosumptio (Ipm) Sport max_speed (mph) Truck capacity (tos) Figure 2: Diagram THE USER COMPREHENSION EXPERIMENT AND RESULTS This sectio provides a summary of the user-comprehesio experimet ad its results. For more details (see Shoval & Frumerma 1994). The experimet We examied user comprehesio as follows: two groups of users, each studyig a differet model, were give a diagram of the model they studied, ad a set of idetical questios (statemets) about facts i the schema. The users were studets of behavioral sciece ad maagemet, havig similar backgrouds ad experiece. They all took the same three computer related courses; therefore, they may be cosidered as "sophisticated users", i.e., users who ca iteract with professioal aalysts, express iformatio eeds ad approve their products. The subjects were radomly divided ito two groups, each studyig oe model. The studies emphasized comprehesio of the schema diagrams (rather tha desig of diagrams). The same istructor taught both models (to avoid bias i teachig quality), ad the same amout of time hours - was allocated to teach each model. I order to motivate the studets, they were told that their performace i the experimet would be cosidered as part of the fial course grade. We prepared a questioaire that cosisted of 48 "true" ad "false" statemets about facts i the coceptual schemas. The purpose was to fid out ot oly if there is a differece i overall comprehesio betwee the two schema diagrams, but also if there is a differece i the specific costruct types. Therefore, we classified the statemets accordig to differet costruct types: a) attributes of etities/objects, b) biary-relatioships, c) two biary relatioships, d) teraryrelatioships, ad e) other facts - with o direct relatioships. We prepared two equivalet schema diagrams, oe for each model. The diagrams icluded exactly the same facts. The HER diagram icluded 12 etities, 7 biary-relatioships, 2 terary-relatioships ad various attributes. I the diagram there were 14 objects - some of which represetig biary ad terary relatioships - each with various types of attributes: atomic, multi-valued, referece-attributes ad tuples. Each participat was give a schema diagram, accordig to the model s(he) studied, ad a questioaire. Each user was expected to review the diagram ad to mark each statemet "true" or 77

5 "false". The level of comprehesio was measured by coutig the umber of correct aswers withi each group for each of the categories of statemets, ad for all statemets together. Aalysis of results The results of the experimet are summarized i Table 1. For each category (icludig "All") ad model it shows the mea grade i absolute values ad i percets, ad the stadard deviatio. The last two colums idicate the sigificace of differece betwee mea grades, determied accordig to twotail Z tests at 0=0.05. As it shows, we caot reject the ull hypothesis that overall, there is o differece of comprehesio betwee the two models, although there is a slight differece i favor of the HER model. There is, however, a sigificat differece i favor of HER for "terary-relatioships": a average of 91.1% for vs. oly 67.8% for. O the other had, there is a advatage to for "other facts": 83.5% to vs. 74.1%to. Type of Costruct Attributes Biary Relatioships Two Relatioships Terary Relatioships Other Facts All Table 1; Summary of the Results for Comprehesio of Model STDS Questios Mea Score Mea i % Z-Value which? (a=0.05) The isigificat differeces betwee the models with respect to "attributes", "biary-relatioships" ad "two relatioships" ca be explaied by the similarity i diagrammatic represetatio. As would be expected, i both models statemets ivolvig two biary-relatioships are more difficult to comprehed tha those ivolvig just attributes or sigle relatioships - average scores were oly 74.78% for ad 77.22% for 00. Sice we foud a sigificat differece betwee the models i the case of terary-relatioships, we further examied these results by distiguishig betwee m::l relatioships ad m:: relatioships. I both cases we foud a sigificat differece i favor of the model. For m::l, the average score of was 93.33, compared to a average score of oly for. For m::, the average scores were ad 62.17, respectively. The advatage of o terary relatioships ca be explaied by the lucidity of the diamod symbol which coects the three etities. It seems that this symbol is clearer ad more visible tha the "ormal" object rectagle which is used i for ay type of object. Moreover, i, a terary-object icludes sets of tuple attributes, which seem to be more complicated to comprehed compared to, where the diamod represetig the terary-relatioship has oly its ow attributes. With respect to "other facts", tured out to be superior. This is actually ot a specific category as it icludes differet statemets which deal with etities or objects that exist i the diagram but have o direct relatioships. may be easier to comprehed for this category because here most of the iformatio is ecapsulated withi the objects, as opposed to where it is "spread-out" amog the etities ad relatioships. THE DESIGN QUALITY EXPERIMENT This sectio provides a summary of the desig-quality experimet ad its results. For more details )see Shoval & Shira 1996). The experimet I this experimet we compared the models from a desiger perspective, addressig three dimesios: a) desig quality, i.e., correctess of schemas; b) time to complete desig tasks, ad c) desiger 78

6 prefereces of the models. With respect to desig quality we defied ull hypotheses that there is o differece i correctess of modelig these costructs types: 1) etities/objects, 2) attributes of etities/objects, 3) iheritace relatioships, 4) uary 1:1 relatioships, 5) biary 1:1 relatioships, 6) biary l: relatioships, 7) biary m: relatioships, 8) terary m::l relatioships, ad 9) terary m::p relatioships. With respect to time ad preferece, we hypotheses that: 10) there is o differece i time to complete desig tasks, ad 11) there is o differece i desiger prefereces of the models. We defied two desig tasks, both similar i size ad complexity (ivolvig the same types ad umbers of various costructs). We created a arrative descriptio for each task, o which basis each subject was asked to desig a coceptual schema diagram usig oe of the two models. The subjects icluded 44 studets, all majorig i Iformatio Systems, with a similar backgroud ad course of studies. All subjects were traied to use the two models. The same amout of time (six hours) was devoted to study each model, ad the same istructor taught all the studets. I order to motivate the subjects, they were told that their performace i the experimet would be part of the fial grade. The subjects were radomly divided ito two groups: subjects i oe group desiged the first task with ad the secod task with HER; subjects i the other group switched models ad tasks. The startig ad edig times of each task were recorded. At the ed, each subject was give a short questioaire, usig 7-poit scales, to express a opiio o the ability of each model to desig a coceptual schema, ad to idicate the relative preferece of the models. Correctess of each schema was measured accordig to the evaluatio scheme described i Batra et al. (1990). Each costruct type, i each model, was scored separately by subtractig a certai umber of poits for each error type (distiguishig betwee mior, medium ad major errors). The we averaged the scores of all subjects o each costruct type for each of the two models. Aalysis of results The results are summarized i Table 2 ad discussed herei Table 2: Summary of Results for desig Quality, Time ad Preferece Hypotheses model model Sigificace Average STDV Average STDV T-value P-value Etity/Class Attributes Iheritace Uary 1 : Biary 1: Biary l: Biary m: which? 8 9 Terary m::l Terary m::p [Time (miutes) I <.0001 tfl, lla How good is model (1-7)?* <.0001 lib Relative preferece ** , 4 II * The is based o the Wilcoxo test; 3.45 is Z-value of the test. ** 7 = absolute preferece of ; 1 = absolute preferece of.--.* A. Correctess of desig (hypotheses 1-9): We used the T-test to measure the differece of mea scores for each of the ie types of costructs. The last colums idicate the sigificace of the results. The "which?" colum idicates if the results are sigificat (at o=0.05) ad which model is favored. We foud o sigificat differece for six of the costructs, amely etity types or object classes (1), attributes (2), iheritace, or supertype-subtype hierarchies (3), ad the three types of biary relatioships (5-7). These results are explaied by the similarity of the models whe dealig with these 79

7 costructs. The slight differeces i the symbols that represet etities or objects, as well as iheritace liks, tured out to be isigificat for desig quality. This is evideced by the high scores o those costructs - above or close to 90. Iterestigly, i both models the scores for 1:1 relatioships were higher tha those for l: relatioships, which, i tur were higher tha those for m: relatioships. These cosistet results stregthe their validity. Cotrary to the above, we foud sigificat differeces for uary (4) ad terary (8 ad 9) relatioships; all favored the model, as explaied herei: Uary 1:1 relatioships: Represetatio of uary relatioships may be complicated, especially i the model, because there are differet optios by which to represet them. For example, the 1:1 uary "marriage" relatioship, which appeared i the experimet, ca be represeted i model as a referece attribute i Employee, or as a separate object (Marriage) related to Employee. As it tured out, i both models may errors occurred, but i we foud more errors i cases where the desigers chose to represet the relatioship as a separate object. Terary m::p relatioships: There were oly a few errors i modelig m::p relatioships with the model, but may errors with model. Typical errors i occurred whe istead of a separate object, the relatioship was represeted as (complex) attributes of other objects. For example, to represet a terary relatioship betwee Worker, Project ad Skill, some desigers defied a tuple of referece attributes {[Skill], [Project], work_hours} i the object Worker. Terary m::l relatioships: Here too, the model was, ideed, better. The results idicate that i both models m::l relatioships are more difficult to model tha m::p relatioships, but desigers made more errors. A typical error was represetatio of a terary as two biary relatioships (e.g., a terary relatioship betwee Worker, Project ad City was represeted by some desigers as two biary relatioships: oe betwee Worker ad Project, aother betwee Project ad City). Whe we ote the similarities ad differeces betwee our results ad the results obtaied i (Bock & Rya 1993), we see that the model was ot superior for ay dimesio. I both studies was better tha for uary 1:1 relatioships; but i (Bock & Rya 1993) was better for biary m: relatioships, whereas i our study was better for terary relatioships. B. Time for completig the desig task (hypothesis 10): As see i Table 2, it takes sigificatly less time to desig schemas. Although the time factor i itself is of mior importace, the fact that this result is cosistet with the results o correctess of desig, stregthes the validity of the experimet. C. Preferece of models by desigers (hypothesis 11): For this dimesio as well, tured out to be sigificatly better. This is evideced both by the scores give to each model idepedetly (row 1 la), ad the relative preferece of the two models (row 1 Ib). The average of 2.82 o a 7-poit scale idicated a sigificat preferece of the model. Eve if we agree that preferece is ot importat as performace, the cosistet results further validate the experimet. SUMMARY AND CONCLUSIONS I summary, we foud that the model is superior to the model for the followig reasos: 1. Comprehesio of schemas: terary relatioships are easier to uderstad, whereas for, oly o-specific ("other") facts are easier to uderstad, with o sigificat differece for the other costructs. 2. Desig quality: Complex (uary ad terary) relatioships are desiged more correctly i, whereas there is o sigificat differeces whe desigig other modelig costructs. 3. Time: it takes less time to desig a schema. 4. Prefereces: desigers prefer to use the model. Therefore, we coclude that eve if the objective is to desig ad implemet a schema, the followig strategy is recommeded: a) desig a schema ad validate it by users/ maagemet; b) 80

8 map it to a equivalet 00 schema (usig a appropriate mappig algorithm or tool; ad c) augmet the schema with the behavioral costructs ("methods" ad "messages"). REFERENCES Agrawal, R. ad Gehai, N. (1989) ODE (object database ad eviromet): The laguage ad the data model, ACM SIGMOD Itl. Cof. o Maagemet of Data, pp Agrawal, R. ad Siha, A. (1992) A empirical study of the effects of experiece ad task characteristics o object-orieted modelig, i: WITS'92 Workshop o Iformatio Techology ad Systems, pp Batra, D. (1993) A framework for studyig huma error behavior i coceptual database modelig, Iformatio & Maagemet, Vol. 25,pp Batra, D., Hoffer, J. ad Bostrom, R. (1990) Comparig represetatios with relatioal ad models, Comm. of the ACM, Vol. 33 (2), pp Batra, D. ad Sriivasa, A. (1992) A review ad aalysis of the usability of data maagemet eviromets, It'l J. of Ma-Machie Studies, Vol. 36, pp Bock, D. ad Rya, T. (1993) Accuracy i modelig with exteded etity relatioship ad object orieted data models, J. of Database Maagemet, Vol. 4 (4), pp Deux, O. et al. (1991) The O2 system, Commuicatios of the ACM, 34 (10), pp Elmasri, R. ad Navathe, S. (1994) Fudametals of Database Systems, 2d Ed., Bejami/ Cummigs,. Gogola, M., Herzig, R., Corad, S., Deker, G. ad Vlachatois, N. (1993) Itegratig the ER approach i a eviromet, It'l Coferece o ER Approach, pp Juh, S. ad Nauma, J. (1985) The effectiveess of data represetatio characteristics o user validatio, I: Proceedigs of the Sixth It. Cof. o Iformatio Systems, pp Kerliger, F. (1973) Foudatios of Behavioral Research, Holt, Rihart ad Wisto. Koratzky, Y. ad Shoval, P. (1994) Coceptual desig of object-orieted schemas usig the biaryrelatioship model, Data & Kowledge Egieerig, Vol. 14, pp Kroekc, D. (1992) Database Processig, 4th Ed., Macmilla Publishig. Nachouki, L., Chastag, M. ad Briad, H. (1992) From etity-relatioship diagram to a objectorieted database, It'l. Coferece o Etity-Relatioship Approach, pp Narasimha, B., Navathe, S. ad Jayarama, S. (1993) O mappig ER ad relatioal models oto schemas, It'l Coferece o ER Approach, pp Palvia, P., Lio, C. ad To, P. (1992) The impact of coceptual data models o ed-user performace, J. of Database Maagemet, Vol. 3 (4), pp Shoval, p. ad Frumerma, I (1994) ad coceptual schemas: a compariso of user comprehesio, J. of Database maagemet, Vol. 5 (4), pp Shoval, P. ad Shira, S. (1996) Etity-Relatioship ad Object-Orieted data modelig - a experimetal compariso of desig quality, Data & Kowledge Egieerig, forthcomig. Teorey, T., Yag, D. ad Fry, J. (1986) A logical desig methodology for relatioal database usig exteded etity-relatioship model, ACM Computig Surveys, Vol. 18, pp