A Radical Revision of UML s Role Concept *

Size: px
Start display at page:

Download "A Radical Revision of UML s Role Concept *"

Transcription

1 A Radical Revision of UML s Role oncept Fiedich Steimann nstitut fü Technische nfomatik Rechnegestützte Wissensveabeitung Univesität Hannove, Appelstaße 4, D Hannove steimann@acm.og Abstact. UML s cuent definition of the ole concept comes with many poblems, not the least being that it is difficult to undestand and communicate. This pape poposes a evised UML metamodel building on a much simple ole definition. Moeove, it eplaces the athe unusual notions of association ole and association end ole as well as the aely used association genealization with the moe popula concept of oveloading, theeby leading to a consideable eduction in the numbe of modelling concepts. Despite the athe adical natue of the poposed alteations, no changes in UML notation become necessay. Howeve, a notable change in modelling style including in paticula a cleae sepaation of stuctue and inteaction diagams ae among the likely effects of the poposed evision. 1 ntoduction UML s cuent vesion [OMG 1999] has thee diffeent definitions of the ole concept: oles as names of association ends, oles as slots in collaboations, and oles as dynamic classes. The fist two ae heitage fom the entity-elationship diagam and object-oiented methods such as OORAM [Reenskaug et al. 1996], espectively, and, as will be seen, ae mostly independent of each othe. The thid is only mentioned in passing [ , p. 3-46] and is pesumably a tibute to a view of oles commonly found in the liteatue [Steimann 1999]. Of couse thee ae vaious othe uses of the tem spead ove the UML specification, fo instance the oles of an acto in diffeent use case diagams o the oles in a state chat, but these uses ae eithe instances of one of the thee definitions listed above o meely a way of speaking. Afte all, ole is one of the most elementay tems not only in modelling (cf. sect. 5), and it is difficult, if not impossible, to get along without it. The ationale of the fist definition of the ole concept is simple: to uniquely identify it, evey end of an association (like evey place of a elationship in the entityelationship diagam) can be assigned a olename, and this end is then efeed to as a ole [ ]. The second definition, the definition of oles as slots of a collaboation, involves moe: in: E Evans, S Kent, B Selic UML 2000: Poceedings of the 3d ntenational onfeence (Spinge, 2000)

2 F. Steiman: A adical evision of UML s ole concept... while a classifie is a complete desciption of instances, a classifie ole is a desciption of the featues equied in a paticula collaboation, i.e. a classifie ole is a pojection of, o a view of, a classifie. The classifie so epesented is efeed to as the base classifie of that paticula classifie ole. [ , p ] and Each association ole epesents the usage of an association in the collaboation, and it is defined between the classifie oles that epesent the associated classifies. The epesented association is called the base association of the association ole. As the association oles specify a paticula usage of an association in a specific collaboation, all constaints expessed by the association ends ae not necessaily equied to be fulfilled in the specified usage. The multiplicity of the association end may be educed in the collaboation, i.e. the uppe and the lowe bounds of the association end oles may be lowe than those of the coesponding base association end, as it might be that only a subset of the associated instances paticipate in the collaboation instance. [ibid.] These definitions become moe tanspaent when looking at the coesponding except of UML s metamodel, as compiled fom figues 2-5, 2-6, and 2-17 of the oiginal specification (shown in figue 1). Fo the sake of conciseness, classifies othe than lass and nteface have been omitted; the complete list can be found in [Rumbaugh et al. 1999]. t must be noted, howeve, that much of UML s complexity is due to this genealization and the esultant geneicity, and that the coectness of the following and all othe agumentation citically depends on what is compised unde the classifie tem. Also notice that Associationlass, a common subclass of Association and lass, has been omitted; although a handy modelling concept, it entails cetain consistency poblems that ae not dealt with hee. 1 child genealization GenealizableElement Genealization 1 paent specialization 1.. base lassifie 1 type specification AssociationEnd name 2.. Association 0..1 base 0..1 base lass nteface 1 type lassifierole AssociationEndRole 2.. AssociationRole Figue 1: An except of the abstact syntax that foms the stuctual pat of the UML metamodel. Moe than one base fo one classifie ole may only be specified if classification is multiple. 195

3 F. Steiman: A adical evision of UML s ole concept lose inspection of the oiginal specification eveals that thee ae many poblems in association with oles. Some of them ae obvious and easily avoided. Fo instance, a classifie ole must not specify a classifie ole as its base, and association ends and association end oles must not be mixed in one association. 1 Othe things ae subtle and become appaent only when woking though the textual specification. Some of these will be discussed next. 2 Poblems 2.1 Base vs. Pojection The use of the tem base in connection with collaboation oles (as eflected in the metamodel of figue 1) suggests that the oles of a collaboation ae deived fom thei bases. And indeed, one well-fomedness ule fo association end oles states that the base classifie of the classifie ole connected to the association end ole must be the same as o a specialization 2 of the classifie connected to the association end ole s base [ , p ]: self.type.base = self.base.type o self.type.base.allpaents->includes (self.base.type) But this obsevation is supeficial. The ule only equies that the base itself, if not the same classifie, is a specialization, not that the classifie ole is a specialization of its base. Quite the contay: a ole epeats only pats of the featues of its base (the availablefeatues [ , p ]) and in case of the classifie ole, lets instances of any classifie engage in the association as long as it confoms to whateve is equied by this ole. Theefoe, the extent of the ole is bigge than that of its base, 3 and use of the tem base (eminiscent of base type/deived type) is misleading. 4 But if the classifie ole is moe geneal than its base, why is this base allowed to be a specialization of the oiginal type? Why should one fist estict the extent of a classifie ole (by selecting a specialization as its base) and then widen it (by educing the numbe of available featues)? And doesn t widening the extent conflict with the view that only a subset of the associated instances paticipate in the collaboation instance? Admittedly, it does make sense to let instances of abitay type paticipate in a collaboation as long as they do what is equied by the ole they play, but then this libety should not be limited to collaboations, since a geneal association specification may be equally pemissive. 5 1 Poblems of this kind can easily be (and some actually ae) fixed though wellfomedness ules. 2 Thoughout this text, specialization is defined as the invese of genealization. 3 Note that the semantics of the base elation diffes depending on what is being elated, because the same does not hold fo association and association end oles: thei extents ae samlle. 4 The oles ae actually also efeed to as pojections o views of thei bases (although patial specifications would seem moe adequate). 5 n fact, seveal extensions of the entity-elationship model allow ad hoc disjunctions (which ae not genealizations!) of entity types to occu in the places of elationship types [Steimann 1999]. ntefaces may seve as such ad hoc disjunctions [Steimann 2001], but this is not discussed in the UML specification. 196

4 F. Steiman: A adical evision of UML s ole concept 2.2 nteface Specifies vs. lassifie Roles n UML, each association end can specify one o moe classifies as inteface specifies (mapped to the specification pseudo-attibute, see figue 1) which ae to estict the access to the instances of the classifie acoss the association. n a way, these inteface specifies paallel the specification of base classifies with a classifie ole, but despite the symmetic stuctue of the metamodel this paallelism is unappaent. nstead, the UML specification offes vaious nebulous explanations, fo instance A ole may be static (e.g., an association end) o dynamic (e.g., a collaboation ole) in the glossay o The use of a olename and inteface specifie ae equivalent to ceating a small collaboation that includes just an association and two oles, whose stuctue is defined by the olename and attached classifie on the oiginal association. Theefoe, the oiginal association and classifies ae a use of the collaboation. The oiginal classifie must be compatible with the inteface specifie (which can be an inteface o a type, among othe kinds of classifies) in the notation guide [ , p. 3-66]. Undoubtedly, both inteface specifies of an association end and base classifies of a collaboation ole seve to specify what is equied fom the instances engaging in an association (o collaboation). Howeve, AssociationEnd genealizes AssociationEndRole, not lassifierole, and it lets the fome inheit the olename attibute. But what happened to the specification pseudo-attibute that should also be inheited fom AssociationEnd? Has it been dopped? f an association end ole in a collaboation specifies an association end as its base and this base lists inteface specifies, must the classifie ole of such an association end ole confom to these inteface specifies? And while the inteface specifies only seve to estict access, not to constain the type of the instances (this is the task of the connected type classifie), the classifie ole does both: it povides a patial specification of the classifies whose instances can play the ole, and it esticts access to the featues of this patial specification. Last but not least, while the base classifie of a classifie ole must connect to the base association of its association ole, no such constaint is imposed on the inteface specifies. Thus, the alleged symmety is eally an asymmety (and a vey confusing one at that). 2.3 Static Stuctue Diagams vs. ollaboation Diagams The duality of concepts just citicized is paalleled by a second one: that of static stuctue and collaboations. Fo an example of this, look at the diagam of figue 2a. Accoding to the UML specification it is a pefect collaboation diagam, albeit one without inteaction infomation. But whee is the collaboation? s the stuctual infomation given in figue 2a less geneally elevant than that of figue 2b, which is a class diagam? O is the existence of (classifie) oles the tue (and only) eason to declae one as a collaboation diagam and not the othe? ndeed, one might pefe to model Teache and Student as subclasses (athe than oles) of Peson 6 would this 6 admittedly a poo pefeence: oles ae no subtypes [Fiesmith & Hendeson-Selles 1998; Steimann 1999] 197

5 F. Steiman: A adical evision of UML s ole concept simple modification tun the collaboation diagam into an odinay class diagam? Hadly. Note well, the poblem hee is not that collaboation diagams expess stuctue, but that oles (othe than the olenames of association ends) ae excluded fom class diagams. Many kinds of constaints on associations (including multiplicities, exclusive os etc.) have been devised, but it is impossible to expess in a class diagam that of all pesons only teaches can be membes of a staff and give couses, even though this may vey well be a fundamental stuctual popety of a modelling poblem. n such cases, the intoduction of an exta collaboation diagam to expess stuctue (but lacking an actual inteaction) must appea atificial, as is the case fo figue 2. (a) faculty membe tuto student /Teache:Peson 1 1 lectue /Student:Peson paticipant 1 faculty :Faculty given couse :ouse taken couse (b) tuto 0..1 student Faculty faculty 0..1 faculty membe lectue 1 Peson paticipant given couse taken couse ouse Figue 2: (a) ollaboation diagam without inteaction infomation (fom [OMG 1999]) (b) coesponding class diagam (adapted fom [Övegaad 1999]) 2.4 Specification vs. nstance Level n UML, inteaction diagams ae offeed at two levels: the specification (o classifie) and the instance level [ , p ]. Howeve, inteactions (and collaboations) always take place between actual objects, not thei oles o classes, and it seems that the specification level is needed only insofa as inteactions equie o impose additional stuctue, stuctue that, because of its geneality, should indeed be expessed on the classifie level. The specification of inteaction itself howeve must be able to distinguish diffeent objects even if they play the same ole and, moe impotantly, must be able to expess that the same object plays diffeent oles in one inteaction. Such is not possible on the classifie level, and it would appea that the instance level is the natual domain fo inteaction specification. The definition of 198

6 F. Steiman: A adical evision of UML s ole concept collaboations with geneic inteaction pattens on the classifie level tends to blu this distinction, and is athe difficult to communicate. 2.5 Association Roles vs. Association Genealization As quoted above, association oles specify a paticula usage of an association in a specific collaboation in which the constaints expessed by the association ends ae not necessaily equied to be fulfilled in the specified usage [OMG 1999, , p ]. Fo instance: The multiplicity of the association end may be educed in the collaboation, i.e. the uppe and the lowe bounds of the association end oles may be lowe than those of the coesponding base association end, as it might be that only a subset of the associated instances paticipate in the collaboation instance. n othe wods: the extent of an association ole is a subset of the extent of its base association. And the UML specification continues: Similaly, an association may be tavesed in some, but pehaps not all, of the allowed diections in the specific collaboation, i.e. the isnavigable popety of an association end ole may be false even if that popety of the base association end is tue. [...] The changeability and odeing of an association end may be stengthened in an association-end ole, i.e. in a paticula usage the end is used in a moe esticted way than is defined by the association. [ , p ] But association oles ae not the only way to estict the use of an association in a UML model: as indicated by the metamodel in figue 1, associations can also be genealized. Wheeas the cuent OMG specification is vey bief about association genealization ( Genealization may be applied to associations as well as classes, although the notation may be messy because of the multiple lines. An association can be shown as an association class fo the pupose of attaching genealization aows. [OMG 1999, , p. 3-80] is the only textual mention found), othe souces go into moe detail: As with any genealization elationship, the child element [of an association genealization] must add to the intent (defining ules) of the paent and must subset the extent (set of instances) of the paent. Adding to the intent means adding additional constaints. A child association is moe constained than its paent. [Rumbaugh et al. 1999, p. 163]. But isn t disallowing navigation moe constained than leaving navigability open (that is, allowing it), and isn t being soted moe constained than not being soted (it is implied by an additional condition, that of the elements being odeed)? All in all, it seems that the semantics of association oles is lagely coveed by the specialization of thei base associations, but this duality of concepts (yet anothe one!) is neve mentioned. 2.6 ntefaces vs. lasses Fo some unappaent eason, UML doesn t make much use of intefaces. n fact, even though thee appeas to be a basic awaeness of the geneal impotance of inte- 199

7 F. Steiman: A adical evision of UML s ole concept faces, the metamodel has no dedicated use fo it (as it has, e.g., fo collaboation oles). nstead, the moe geneal lassifie (compising classes and intefaces) is consistently (ab)used to specify intefaces whee the use of the nteface concept wee in place. Fo instance, the inteface specifies of an association end may be classes, and classifie oles ae geneal classifies although thei pupose is clealy that of a patial specification and hence that of an inteface 7. 3 Revision t should be clea fom the above that UML s cuent ole concept is poblematic. The alleged symmety of association end and collaboation ole is only seeming, and paticulaly the intoduction of association oles and association end oles which shae only supeficial popeties with classifie oles (such as having bases and being slots in a collaboation) appeas to be a peculiaity of UML that is difficult to tanspot. As a matte of fact, the desciption of the connection between associations and association oles emains athe sketchy, and it may be speculated that any attempt to pin it down pecisely would lead to moe poblems. Fotunately, thee is a simple solution to all this. Roles ae no specialty of collaboations and the inteactions they enable, they ae a coe stuctual element (although not necessaily a static one). Roles ae bidges between instantiable classifies and thei associations, be it in the scope of a collaboation o outside the context of any inteaction. But oles ae no association ends (o the names theeof) a ole (moe pecisely, a ole type) is a classifie like a class, only that it does not have instances of its own. nstead, a ole ecuits its instances fom those classifies that ae declaed compatible with the ole, that is, that comply with the patial specification that makes the ole. As fo the emaining UML oles, namely the association oles and association end oles: they too ae not limited to the scope of collaboations. But unlike classifie oles, they ae ivaled by an equally suitable (an much bette undestood) concept: association oveloading. Oveloading, expessing that the same association (opeation, elation, o function) has diffeent popeties depending on the classifies (types) being associated, is ubiquitous in object-oiented pogamming as well as in the theoy of type stuctues [Bläsius et al. 1989], and it gacefully accounts fo the fact that an association in a collaboation (with only a subset of the instances involved) may have diffeent popeties than the same association outside the scope of the collaboation. At the same time, oveloading accounts fo most of the semantics of association specialization as a puely stuctual modelling element the only obvious diffeence is that a specialized association can have a diffeent name than its genealization. Note well, the suggested evision is not a plea against collaboations. ollaboations emain as an impotant means of zooming into paticula stuctual aspects of a model and as a basis fo expessing the inteactions that build upon them. The point hee is that the stuctual aspects of a collaboation can be expessed with the same modelling concepts as any classifie stuctue, be it in o outside the scope of collaboation. 7 pehaps not an inteface in the definition of UML, but that is anothe issue 200

8 F. Steiman: A adical evision of UML s ole concept Moe specifically, the evision of UML s ole concept is compised by the following fou commitments. 1. The metaclasses nteface and lassifierole ae meged into a new metaclass Role. The estictions egading intefaces in UML (that they cannot have attibutes o occu in othe places than the taget ends of diected associations) ae dopped. lass and Role ae stictly sepaated: while classes can be instantiated (unless of couse they ae abstact), oles cannot. 2. The association between classifie oles and thei base classifies is eplaced by a new elationship, named populates 8, which elates classes with the oles thei instances can play. (t is convenient to speak of a class as populating a ole and of an instance as playing a ole. t is impotant that these ae distinguished: populating oughly coesponds to the subclass elationship among classes, and playing to the instance-of elationship of an instance to its class. The diction in this egad is often ambiguous in the liteatue.) 3. Association ends ae equied to connect to oles exclusively. Because oles ae intefaces and suboles can combine seveal intefaces, both pseudo-attibutes type and specification ae eplaced by one new elationship specifies associating each association end with one ole. The classes whose instances actually paticipate in an association ae specified only indiectly via the populates elationship between classes and oles. Association ends need not be given a olename; if they ae, this name must equal the connected ole s. Evey ole must be unique within an association, i.e., no two association ends of one association must specify the same ole. 4. The metaclasses AssociationEndRole, AssociationRole, and the genealization of associations ae eplaced by association oveloading. Fo this pupose, a new metaclass, Signatue, is intoduced whose instances stand between an association and its (oveloaded) association ends. Thus, athe than giving ise to an association ole, an association esticted in the context of a collaboation specifies a new instance of Signatue, compising new association ends, each connected to a ole defined by the collaboation. The metamodel the suggested changes esult in is pesented in figue 3. Fist and foemost, it does not distinguish between coe and collaboation modelling elements: association ends ae always connected to oles, which ae always populated by classes (epesentative of all othe classifies), although a paticula diagam may choose not to show this. Second, UML s indiffeence with egad to a classifie s being a class o an inteface is lifted: intefaces, now temed oles, exclusively occu at associations ends, and classes exclusively as populating them. Last but not least, it accounts fo the fact that the same association can occu multiply in one model, each occuence disambiguated by a diffeent signatue, always involving diffeent association ends and usually also connecting to a diffeent set of oles. 8 Altenative tems fo populates would be implements o ealizes, but these ae athe technical. 201

9 F. Steiman: A adical evision of UML s ole concept genealizes lass Role populates genealizes fills AssociationEnd 2.. Signatue 1.. Association Figue 3: The evised metamodel fo UML A final note on the epesentation of genealization in figue 3. UML intoduces Genealization as an instantiable metaclass (see figue 1). n ode to avoid inconsistencies, it must be declaed fo all genealizable elements what is inheited down each genealization elationship (instance of the Genealization metaclass). The changed metamodel takes a simple appoach: it epesents genealization as an oveloaded elationship of the metamodel. Note that genealizes is of the same ode as populates 9, while all instances of Association ae of a lowe ode. This way, no pecautions avoiding inconsistencies and paadoxes need to be taken. 4 hanges fo the Modelle The good news fist: thee ae no changes of notation necessay. The definition of the new ole concept as a mege of collaboation oles and intefaces and the emphasis on the inteface aspect suggests that oles ae dawn like intefaces, i.e., as steeotyped classifies o, pefeably, as cicles. The oveloading of associations coveing both association genealization and association oles is implicitly expessed by diffeent associations with the same name (and, unde cetain conditions, may be explicated by genealization aows). All othe changes have no impact on the notation itself, only on the style diagams ae composed. 4.1 A New Style fo Stuctue Diagams The most obvious consequence of the new metamodel on diagam style is that all associations must end at oles. Thus, oles (fomely intefaces) should be seen moe fequently in class diagams, whee they function as inteface specifies esticting access to instances acoss the association, but also as patial specifications of the classes whose instances link. n fact, placing oles, not classes, at association ends means lifting the pogam to an inteface maxim (that is consideed good pactice in object-oiented pogamming [Gamma et al. 1995; D Souza & Wills 1998; Steimann 2001]) to the modelling level; it entails that instances of vaious classes can intechangeably engage in the same association as long as thei classes populate the ole specified. n a collaboation diagam at specification level, all associations aleady end at oles (fomely, classifie oles). Howeve, the classes that (by default) populate the oles, the fome base classes (if povided), ae no longe implicit pats of the ole symbols, but have to be shown explicitly. Note that oles in a collaboation diagam seve no 9 UML specifies a simila elationship of types and implementation classes: [...] types may only specialize othe types and implementation classes may only specialize othe implementation classes. Types and implementation classes can be elated only be ealization [3.27.1, p. 3-46]. But the distinction of types and implementation classes is not that of oles and classes. 202

10 F. Steiman: A adical evision of UML s ole concept diffeent pupose than oles in a (new style) class diagam: they specify the inteface (including attibutes!) that ae equied fom the collaboatos, but they do not commit the collaboation to the classes whose instances can play the ole. Figue 4 shows a collaboation diagam and a class diagam in the new style, showing stuctue, but no behaviou. Because with the new style class diagams and the stuctual aspects of collaboation diagams ely on the same modelling concepts, thee is no syntactical diffeence between the two diagam types: both show associations connecting oles and classes populating them. onsequently, the diffeence between the two can be based only on intention: dawing a sepaate collaboation diagam is useful if and only if (a) inteaction infomation is to be povided o (b) associations that ae elevant only within the scope of an actual collaboation (fomely: association oles) ae to be shown. (a) tuto student faculty membe Teache Peson Student faculty given couse taken couse lectue paticipant Faculty ouse (b) tuto student faculty paticipant taken couse faculty membe Peson ouse Faculty lectue given couse Figue 4: New style collaboation diagam (a) and class diagam (b) coesponding to the diagams of figue 2. Note that collaboation diagam diffes fom the class diagam only by the intoduction of the suboles Teache and Student. Finally, a collaboation diagam at instance level specifies behaviou by showing pototypical objects as they inteact. Although not eseved fo the instance level, it is hee that UML s lollipop notation unfolds its intuitive expessiveness: in an inteaction, objects should be accessed exclusively via the oles they play, and these oles (which ae themselves no instances) ae connected to thei playes by unlabeled lines 203

11 F. Steiman: A adical evision of UML s ole concept to expess that they ae the plugpoints between (substitutable) objects and the specified inteaction. Figue 5 gives an example of this. 1:teaches() student 1.1[i:=1..n]: lectue() paticipant taken couse 1.i.1:name() lectue given couse Figue 5: New style collaboation diagam on the instance level. All objects can, but need not, emain anonymous and lack class infomation. The lollipop notation of an object and its oles is eminiscent of the pieces of a jigsaw puzzle, which is intentional. Mapping. Mapping of the new style diagams to instances of the evised metamodel is staightfowad. Evey class maps to an instance of lass, evey ole to one of Role. Realization aows map to instances of the populates association, and genealization aows to instances of the espective genealization associations. Evey occuence of an association with the same name maps to the same instance of Association, but to a diffeent instance of Signatue with coespondingly diffeent instances of AssociationEnd. Figue 6 shows the mapping fo a simple diagam. D s a a t E :lass D:lass E:lass :Role s:role t:role :AssociationEnd :AssociationEnd :AssociationEnd :AssociationEnd :Signatue :Signatue a:association Figue 6: Mapping of a new style stuctue diagam to an instance of the evised metamodel. Association labels of the object diagam ae omitted, but can easily be econstucted fom the class diagam of figue

12 F. Steiman: A adical evision of UML s ole concept 4.2 Retaining Old Style Diagams Evey diagam of the new style is a valid UML diagam, mapping to the old as well as the evised metamodel. But thee ae even bette news: all diagams of the old style that map to instances of the old metamodel also map to the evised one. Howeve, as one may imagine, the mapping is not staightfowad, and it is moe instuctive to look at a systematic tansfomation of conventional diagams into diagams of the new style, fo which mapping is one-to-one. The outline of the mapping pocedue is as follows: Fist, it is ensued that evey association end connects to a suitable ole. Then, the classifie fomely occupying the association end is elated to that ole, eithe as populating, as specializing, o as being identical to it. Finally, in case the association is a specialization o an association ole, the necessay oveloading is declaed. Duing this pocedue it may become necessay to intoduce a (default) ole fo a class that is defined as the class s complete inteface. n these cases, the ole is given the same name as the class (only that the name is set in italics), and it is undestood that the two ae diffeent types even though they cay the same names. 10 Mapping. n class diagams of the old style classifies (mostly classes) diectly connect to association ends. Howeve, these association ends usually come with olenames. Even though these olenames ae no oles, but mee labels, they could be, and the fist step in mapping is to intoduce a ole fo evey association end with the olename as its name, and to let the classifie fomely connected to the association end populate that ole. f no olename is povided, the ole is given the class s name (the default ole), and if the classifie is an inteface, it is consideed a diect subole of the ole intoduced by the olename (if povided), o eveything is left as is (if no exta olename is povided). Figue 7 a shows the mapping fo all fou cases. Next come the inteface specifies. The inteface specifies at association ends always come with olenames, but the association ends may connect to classes o intefaces. The mapping to the new dawing style in eithe case is as above, only that each inteface specifie is made an immediate supeole of the ole connected to the association end. f an inteface specifie is a class, its default ole is assumed. Figue 7 b shows the details. Note that the inteface specifies ae independent of the association end, since it is not equied that they paticipate in the same association. Finally the collaboation oles. Hee, we estict ouselves to single classification, which is still pedominating in the object-oiented wold. Thus, only one base classifie is listed with each classifie ole. f this base classifie is a class the classifie ole is mapped to an inteface with the base classifie populating that inteface (figue 7 c). Whethe o not the ole is the default ole of the class depends on whethe the classifie ole is a patial specification of the base class, i.e., whethe it esticts the available featues. By default, we must assume that this is the case so that a new ole is intoduced caying the classifie ole name if specified o a new name othewise; if not, the default ole can be used. Finally, if the base classifie is an inteface, it eplaces the new ole and the class populating it (figue 7 d). Note in paticula that the mapping of inteface specifies and classifie oles have not much in common. 10 The names may be thought of as being qualified by a lass o a Role suffix, espectively, but this suffix is left implicit fo the sake of eadability. 205

13 F. Steiman: A adical evision of UML s ole concept (a) (b) :D,...,S :D,...,S D... S D... S D D (c) : : /R: /R: /R /R s R R s R R (d) : : /R: /R: /R /R R R R R Figue 5: Mapping of old style notation to the new style (a) fo association ends, (b) fo association ends with inteface specifies, (c) fo collaboation oles with classes as bases, and (d) fo collaboation oles with intefaces as bases. A collaboation diagam does not only intoduce classifie oles, but also association oles and association end oles. These oles ae implicitly given if (a) the association is unique to collaboation diagams o (b) the use of the association is esticted in the context of the collaboation (so that the association has a base association). The latte may esult fom a estiction in multiplicity, navigability, etc. and esults in an 206

14 F. Steiman: A adical evision of UML s ole concept oveloading of associations (and thei ends). Thus, to povide complete mapping ules it would be necessay to conside all othe uses of the association. n figue 5, oveloading is shown only in the context of classifie oles connecting to association ends with olenames, because it is assumed that the olename is heitage fom a class diagam with the same association 11 and that this association is being esticted within the scope of the collaboation. Given these mapping ules the diagams of figue 2 ae easily tansfomed to the new style diagams of figue 4 (with multiplicities and oveloaded associations omitted). Howeve, a couple of things deseve mention. Fist, if an association end (of a class diagam) is to be filled with instances of the specified classifie only, the coesponding ole must not be populated by othe classes. Second, if the same olename occus in diffeent associations, it must be checked whethe the coesponding oles ae actually the same o diffeent. hances ae good that they ae the same if they compise the same set of instances (the ole playes) and if they come with the same set of featues. n case they ae diffeent, olenames can be qualified by thei association names. 5 The Big Pictue The definition of oles as pesented hee is not just anothe fomalization of the same old concept the elation of oles and classes o natual types (as opposed to ole types) of individuals as eflected by the metamodel in figue 3 is easily fomalized using ode soted pedicate logic (including a theoy of oveloading), and is at the same time deeply founded in disciplines as divese as sociology, linguistics, and ontology [Steimann 2000]. Paticulaly the latte two have an obvious influence on modelling, and both leave no doubt that oles and elations ae mutually dependent concepts. n this dependency, classes meely seve as the povides of instances (which oles don t have) and as takes of the esponsibility fo the ealization of whateve the oles of a model pomise. The biggest advantage of this sepaation is that stuctue and inteaction ae specified lagely independently of the classes that delive instances and implementation. As a esult, classes ae kept exchangeable even on the model level. n fact, it seems that modelling with oles delives on the long equested decoupling of classes in a natual and intuitive way. This has been ecognized not only by seveal objectoiented modelling methods such as OORAM [Reenskaug et al. 1996], OPEN [Fiesmith & Hendeson-Selles 1998] and ATALYSS [D Souza & Wills 1998], but also in diffeent application aeas of object-oiented modelling, fo instance by the patten community [Buschmann 1998] and in famewok design [Riehle 2000]. With oles defined as above at hand, instantiating the omposite patten in a model simply amounts to the involved classes populating (o ealizing) the omponent, omposite, and Leaf oles. A majo advantage of the intoduction of oles as patial specifications of classes is that polymophism and substitutability in modelling ae no longe bound to the genealization hieachy of classes (which mainly seves as an abstaction mechanism 11 intoducing olenames fo association ends in collaboation diagams is edundant, since classifie oles can have olenames 207

15 F. Steiman: A adical evision of UML s ole concept and, not only in UML, to specify the paths of inheitance), but apply equally to oles and thei implementos. The advantage hee is that substitutability, if bound to oles, is less demanding than equiing the full substitutability of (the instances of) one class fo anothe 12, because a ole pomises only limited functionality and behaviou. n fact, the liteal meaning of the tem polymophism is that objects (not functions) have diffeent foms, and an object playing diffeent oles may indeed be consideed polymophic in this liteal sense [Steimann 1999]. Last but not least, oles give intefaces a pominent conceptual abstaction that would othewise be missing in object-oiented modelling. Pehaps this lack explains why UML teats intefaces so negligently, but be that as it may, with oles as a natual and intuitive modelling concept (compising the puposes of intefaces and classifie oles), intefaces should finally get thei ightful place in object-oiented modelling. 6 onclusion The distinction between class diagams as static stuctue diagams (with classifies as types and as inteface specifies of association ends) on one side and collaboation diagams as behaviou diagams (with classifie oles and thei base classifies) on the othe is notoiously difficult to undestand (and even moe difficult to wite about). This unfotunate situation is wosened by the fact that UML s offeed divesity of modelling concepts opens the doo wide up fo intoducing inconsistencies into models that ae not easily caught unless an automated tool with full mastey of the UML specification is used. n fact, it may be conjectued that the building of such a tool (mapping all diagams into a single instance of the metamodel) would unveil many moe flaws in the UML specification. Keeping this specification is likely to esult in pactitiones ignoing lage pats of it, if only to be on the safe side. What is equally disappointing is that the UML specification does not pomote the use of the inteface concept, which is today a poven design and implementation constuct. nstead, the metamodel allows it that intefaces and othe classifies ae intechangeably used whee eithe one o the othe is equied. Fo instance, in UML neithe the inteface specifies of association ends no the base classifies of classifie oles need be intefaces, although thei pupose is clealy that of specifying an inteface. nstead, it seems that UML has adopted JAVA s notion of intefaces and follows it athe slavishly to the point that intefaces can only occu at the taget ends of diected associations an undue limitation that is unacceptable fo the ole concept. ORBA and DL, othe OMG standads, ae much moe flexible in this egad. Refeences [Bläsius et al. 1989] KH Bläsius, U Hedtstück, R Rollinge (eds) Sots and Types in Atificial ntelligence Lectue Notes in Atificial ntelligence 418 (Spinge 1989). 12 which is neve eally given because othewise thee would be no need to have diffeent classes 208

16 F. Steiman: A adical evision of UML s ole concept [Buschmann 1998] F Buschmann Falsche Annahmen (Teil 2) OBJEKTspektum 4 (1998) [D Souza & Wills 1998] DF D Souza, A Wills Objects, omponents and Famewoks with UML: The ATALYSS Appoach (Addison-Wesley, Reading 1998). [Fiesmith & Hendeson-Selles 1998] DG Fiesmith, B Hendeson-Selles Upgading OML to vesion 1.1 pat 2: additional concepts and notations Jounal of Object-Oiented Pogamming 11:5 (1998) [Gamma et al. 1995] E Gamma, R Helm, R Johnson, J Vlissides Design Pattens: Elements of Reusable Object-Oiented Softwae (Addison-Wesley 1995). [OMG 1999] OMG Unified Modeling Language Specification Vesion 1.3 ( June 1999). [Övegaad 1999] G Övegaad A fomal appoach to collaboations in the Unified Modeling Language in: UML '99 LNS 1723 (Spinge, 1999). [Reenskaug et al. 1996] T Reenskaug, P Wold, OA Lehne Woking with Objects The OORAM Softwae Engineeing Method (Manning, Geenwich 1996). [Riehle 2000] D Riehle Famewok Design: a Role Modeling Appoach doctoal dissetation (ETH Züich, 2000). [Rumbaugh et al. 1999] J Rumbaugh, Jacobsen, G Booch The Unified Modeling Language Refeence Manual (Addison-Wesley, Reading 1999). [Steimann 1999] F Steimann On the epesentation of oles in object-oiented and conceptual modelling Data & Knowledge Engineeing to appea. [Steimann 2000] F Steimann Fomale Modellieung mit Rollen thesis (Univesität Hannove, 2000). [Steimann 2001] F Steimann Role = nteface: a mege of concepts Jounal of Object-Oiented Pogamming (2001) to appea

DEADLOCK AVOIDANCE IN BATCH PROCESSES. M. Tittus K. Åkesson

DEADLOCK AVOIDANCE IN BATCH PROCESSES. M. Tittus K. Åkesson DEADLOCK AVOIDANCE IN BATCH PROCESSES M. Tittus K. Åkesson Univesity College Boås, Sweden, e-mail: Michael.Tittus@hb.se Chalmes Univesity of Technology, Gothenbug, Sweden, e-mail: ka@s2.chalmes.se Abstact:

More information

(a, b) x y r. For this problem, is a point in the - coordinate plane and is a positive number.

(a, b) x y r. For this problem, is a point in the - coordinate plane and is a positive number. Illustative G-C Simila cicles Alignments to Content Standads: G-C.A. Task (a, b) x y Fo this poblem, is a point in the - coodinate plane and is a positive numbe. a. Using a tanslation and a dilation, show

More information

Detection and Recognition of Alert Traffic Signs

Detection and Recognition of Alert Traffic Signs Detection and Recognition of Alet Taffic Signs Chia-Hsiung Chen, Macus Chen, and Tianshi Gao 1 Stanfod Univesity Stanfod, CA 9305 {echchen, macuscc, tianshig}@stanfod.edu Abstact Taffic signs povide dives

More information

A New and Efficient 2D Collision Detection Method Based on Contact Theory Xiaolong CHENG, Jun XIAO a, Ying WANG, Qinghai MIAO, Jian XUE

A New and Efficient 2D Collision Detection Method Based on Contact Theory Xiaolong CHENG, Jun XIAO a, Ying WANG, Qinghai MIAO, Jian XUE 5th Intenational Confeence on Advanced Mateials and Compute Science (ICAMCS 2016) A New and Efficient 2D Collision Detection Method Based on Contact Theoy Xiaolong CHENG, Jun XIAO a, Ying WANG, Qinghai

More information

Lecture 27: Voronoi Diagrams

Lecture 27: Voronoi Diagrams We say that two points u, v Y ae in the same connected component of Y if thee is a path in R N fom u to v such that all the points along the path ae in the set Y. (Thee ae two connected components in the

More information

SYSTEM LEVEL REUSE METRICS FOR OBJECT ORIENTED SOFTWARE : AN ALTERNATIVE APPROACH

SYSTEM LEVEL REUSE METRICS FOR OBJECT ORIENTED SOFTWARE : AN ALTERNATIVE APPROACH I J C A 7(), 202 pp. 49-53 SYSTEM LEVEL REUSE METRICS FOR OBJECT ORIENTED SOFTWARE : AN ALTERNATIVE APPROACH Sushil Goel and 2 Rajesh Vema Associate Pofesso, Depatment of Compute Science, Dyal Singh College,

More information

Point-Biserial Correlation Analysis of Fuzzy Attributes

Point-Biserial Correlation Analysis of Fuzzy Attributes Appl Math Inf Sci 6 No S pp 439S-444S (0 Applied Mathematics & Infomation Sciences An Intenational Jounal @ 0 NSP Natual Sciences Publishing o Point-iseial oelation Analysis of Fuzzy Attibutes Hao-En hueh

More information

FACE VECTORS OF FLAG COMPLEXES

FACE VECTORS OF FLAG COMPLEXES FACE VECTORS OF FLAG COMPLEXES ANDY FROHMADER Abstact. A conjectue of Kalai and Eckhoff that the face vecto of an abitay flag complex is also the face vecto of some paticula balanced complex is veified.

More information

Illumination methods for optical wear detection

Illumination methods for optical wear detection Illumination methods fo optical wea detection 1 J. Zhang, 2 P.P.L.Regtien 1 VIMEC Applied Vision Technology, Coy 43, 5653 LC Eindhoven, The Nethelands Email: jianbo.zhang@gmail.com 2 Faculty Electical

More information

Controlled Information Maximization for SOM Knowledge Induced Learning

Controlled Information Maximization for SOM Knowledge Induced Learning 3 Int'l Conf. Atificial Intelligence ICAI'5 Contolled Infomation Maximization fo SOM Knowledge Induced Leaning Ryotao Kamimua IT Education Cente and Gaduate School of Science and Technology, Tokai Univeisity

More information

a Not yet implemented in current version SPARK: Research Kit Pointer Analysis Parameters Soot Pointer analysis. Objectives

a Not yet implemented in current version SPARK: Research Kit Pointer Analysis Parameters Soot Pointer analysis. Objectives SPARK: Soot Reseach Kit Ondřej Lhoták Objectives Spak is a modula toolkit fo flow-insensitive may points-to analyses fo Java, which enables expeimentation with: vaious paametes of pointe analyses which

More information

Communication vs Distributed Computation: an alternative trade-off curve

Communication vs Distributed Computation: an alternative trade-off curve Communication vs Distibuted Computation: an altenative tade-off cuve Yahya H. Ezzeldin, Mohammed amoose, Chistina Fagouli Univesity of Califonia, Los Angeles, CA 90095, USA, Email: {yahya.ezzeldin, mkamoose,

More information

Journal of World s Electrical Engineering and Technology J. World. Elect. Eng. Tech. 1(1): 12-16, 2012

Journal of World s Electrical Engineering and Technology J. World. Elect. Eng. Tech. 1(1): 12-16, 2012 2011, Scienceline Publication www.science-line.com Jounal of Wold s Electical Engineeing and Technology J. Wold. Elect. Eng. Tech. 1(1): 12-16, 2012 JWEET An Efficient Algoithm fo Lip Segmentation in Colo

More information

Towards Adaptive Information Merging Using Selected XML Fragments

Towards Adaptive Information Merging Using Selected XML Fragments Towads Adaptive Infomation Meging Using Selected XML Fagments Ho-Lam Lau and Wilfed Ng Depatment of Compute Science and Engineeing, The Hong Kong Univesity of Science and Technology, Hong Kong {lauhl,

More information

The Internet Ecosystem and Evolution

The Internet Ecosystem and Evolution The Intenet Ecosystem and Evolution Contents Netwok outing: basics distibuted/centalized, static/dynamic, linkstate/path-vecto inta-domain/inte-domain outing Mapping the sevice model to AS-AS paths valley-fee

More information

An Unsupervised Segmentation Framework For Texture Image Queries

An Unsupervised Segmentation Framework For Texture Image Queries An Unsupevised Segmentation Famewok Fo Textue Image Queies Shu-Ching Chen Distibuted Multimedia Infomation System Laboatoy School of Compute Science Floida Intenational Univesity Miami, FL 33199, USA chens@cs.fiu.edu

More information

Also available at ISSN (printed edn.), ISSN (electronic edn.) ARS MATHEMATICA CONTEMPORANEA 3 (2010)

Also available at  ISSN (printed edn.), ISSN (electronic edn.) ARS MATHEMATICA CONTEMPORANEA 3 (2010) Also available at http://amc.imfm.si ISSN 1855-3966 (pinted edn.), ISSN 1855-3974 (electonic edn.) ARS MATHEMATICA CONTEMPORANEA 3 (2010) 109 120 Fulleene patches I Jack E. Gave Syacuse Univesity, Depatment

More information

Spiral Recognition Methodology and Its Application for Recognition of Chinese Bank Checks

Spiral Recognition Methodology and Its Application for Recognition of Chinese Bank Checks Spial Recognition Methodology and Its Application fo Recognition of Chinese Bank Checks Hanshen Tang 1, Emmanuel Augustin 2, Ching Y. Suen 1, Olivie Baet 2, Mohamed Cheiet 3 1 Cente fo Patten Recognition

More information

Using Data Flow Diagrams for Supporting Task Models

Using Data Flow Diagrams for Supporting Task Models in Companion Poc. of 5 th Euogaphics Wokshop on Design, Specification, Veification of Inteactive Systems DSV-IS 98 (Abingdon, 3-5 June 1998), P. Makopoulos & P. Johnson (Eds.), Spinge-Velag, Belin, 1998.

More information

User Specified non-bonded potentials in gromacs

User Specified non-bonded potentials in gromacs Use Specified non-bonded potentials in gomacs Apil 8, 2010 1 Intoduction On fist appeaances gomacs, unlike MD codes like LAMMPS o DL POLY, appeas to have vey little flexibility with egads to the fom of

More information

Frequency Domain Approach for Face Recognition Using Optical Vanderlugt Filters

Frequency Domain Approach for Face Recognition Using Optical Vanderlugt Filters Optics and Photonics Jounal, 016, 6, 94-100 Published Online August 016 in SciRes. http://www.scip.og/jounal/opj http://dx.doi.og/10.436/opj.016.68b016 Fequency Domain Appoach fo Face Recognition Using

More information

ART GALLERIES WITH INTERIOR WALLS. March 1998

ART GALLERIES WITH INTERIOR WALLS. March 1998 ART GALLERIES WITH INTERIOR WALLS Andé Kündgen Mach 1998 Abstact. Conside an at galley fomed by a polygon on n vetices with m pais of vetices joined by inteio diagonals, the inteio walls. Each inteio wall

More information

Multi-azimuth Prestack Time Migration for General Anisotropic, Weakly Heterogeneous Media - Field Data Examples

Multi-azimuth Prestack Time Migration for General Anisotropic, Weakly Heterogeneous Media - Field Data Examples Multi-azimuth Pestack Time Migation fo Geneal Anisotopic, Weakly Heteogeneous Media - Field Data Examples S. Beaumont* (EOST/PGS) & W. Söllne (PGS) SUMMARY Multi-azimuth data acquisition has shown benefits

More information

Generalized Grey Target Decision Method Based on Decision Makers Indifference Attribute Value Preferences

Generalized Grey Target Decision Method Based on Decision Makers Indifference Attribute Value Preferences Ameican Jounal of ata ining and Knowledge iscovey 27; 2(4): 2-8 http://www.sciencepublishinggoup.com//admkd doi:.648/.admkd.2724.2 Genealized Gey Taget ecision ethod Based on ecision akes Indiffeence Attibute

More information

Segmentation of Casting Defects in X-Ray Images Based on Fractal Dimension

Segmentation of Casting Defects in X-Ray Images Based on Fractal Dimension 17th Wold Confeence on Nondestuctive Testing, 25-28 Oct 2008, Shanghai, China Segmentation of Casting Defects in X-Ray Images Based on Factal Dimension Jue WANG 1, Xiaoqin HOU 2, Yufang CAI 3 ICT Reseach

More information

Positioning of a robot based on binocular vision for hand / foot fusion Long Han

Positioning of a robot based on binocular vision for hand / foot fusion Long Han 2nd Intenational Confeence on Advances in Mechanical Engineeing and Industial Infomatics (AMEII 26) Positioning of a obot based on binocula vision fo hand / foot fusion Long Han Compute Science and Technology,

More information

Assessment of Track Sequence Optimization based on Recorded Field Operations

Assessment of Track Sequence Optimization based on Recorded Field Operations Assessment of Tack Sequence Optimization based on Recoded Field Opeations Matin A. F. Jensen 1,2,*, Claus G. Søensen 1, Dionysis Bochtis 1 1 Aahus Univesity, Faculty of Science and Technology, Depatment

More information

Module 6 STILL IMAGE COMPRESSION STANDARDS

Module 6 STILL IMAGE COMPRESSION STANDARDS Module 6 STILL IMAE COMPRESSION STANDARDS Lesson 17 JPE-2000 Achitectue and Featues Instuctional Objectives At the end of this lesson, the students should be able to: 1. State the shotcomings of JPE standad.

More information

Automatically Testing Interacting Software Components

Automatically Testing Interacting Software Components Automatically Testing Inteacting Softwae Components Leonad Gallaghe Infomation Technology Laboatoy National Institute of Standads and Technology Gaithesbug, MD 20899, USA lgallaghe@nist.gov Jeff Offutt

More information

Prof. Feng Liu. Fall /17/2016

Prof. Feng Liu. Fall /17/2016 Pof. Feng Liu Fall 26 http://www.cs.pdx.edu/~fliu/couses/cs447/ /7/26 Last time Compositing NPR 3D Gaphics Toolkits Tansfomations 2 Today 3D Tansfomations The Viewing Pipeline Mid-tem: in class, Nov. 2

More information

Title. Author(s)NOMURA, K.; MOROOKA, S. Issue Date Doc URL. Type. Note. File Information

Title. Author(s)NOMURA, K.; MOROOKA, S. Issue Date Doc URL. Type. Note. File Information Title CALCULATION FORMULA FOR A MAXIMUM BENDING MOMENT AND THE TRIANGULAR SLAB WITH CONSIDERING EFFECT OF SUPPO UNIFORM LOAD Autho(s)NOMURA, K.; MOROOKA, S. Issue Date 2013-09-11 Doc URL http://hdl.handle.net/2115/54220

More information

Optical Flow for Large Motion Using Gradient Technique

Optical Flow for Large Motion Using Gradient Technique SERBIAN JOURNAL OF ELECTRICAL ENGINEERING Vol. 3, No. 1, June 2006, 103-113 Optical Flow fo Lage Motion Using Gadient Technique Md. Moshaof Hossain Sake 1, Kamal Bechkoum 2, K.K. Islam 1 Abstact: In this

More information

The EigenRumor Algorithm for Ranking Blogs

The EigenRumor Algorithm for Ranking Blogs he EigenRumo Algoithm fo Ranking Blogs Ko Fujimua N Cybe Solutions Laboatoies N Copoation akafumi Inoue N Cybe Solutions Laboatoies N Copoation Masayuki Sugisaki N Resonant Inc. ABSRAC he advent of easy

More information

A modal estimation based multitype sensor placement method

A modal estimation based multitype sensor placement method A modal estimation based multitype senso placement method *Xue-Yang Pei 1), Ting-Hua Yi 2) and Hong-Nan Li 3) 1),)2),3) School of Civil Engineeing, Dalian Univesity of Technology, Dalian 116023, China;

More information

RANDOM IRREGULAR BLOCK-HIERARCHICAL NETWORKS: ALGORITHMS FOR COMPUTATION OF MAIN PROPERTIES

RANDOM IRREGULAR BLOCK-HIERARCHICAL NETWORKS: ALGORITHMS FOR COMPUTATION OF MAIN PROPERTIES RANDOM IRREGULAR BLOCK-HIERARCHICAL NETWORKS: ALGORITHMS FOR COMPUTATION OF MAIN PROPERTIES Svetlana Avetisyan Mikayel Samvelyan* Matun Kaapetyan Yeevan State Univesity Abstact In this pape, the class

More information

A Shape-preserving Affine Takagi-Sugeno Model Based on a Piecewise Constant Nonuniform Fuzzification Transform

A Shape-preserving Affine Takagi-Sugeno Model Based on a Piecewise Constant Nonuniform Fuzzification Transform A Shape-peseving Affine Takagi-Sugeno Model Based on a Piecewise Constant Nonunifom Fuzzification Tansfom Felipe Fenández, Julio Gutiéez, Juan Calos Cespo and Gacián Tiviño Dep. Tecnología Fotónica, Facultad

More information

User Group testing report

User Group testing report Use Goup testing epot Deliveable No: D6.10 Contact No: Integated Poject No. 506723: SafetyNet Aconym: SafetyNet Title: Building the Euopean Road Safety Obsevatoy Integated Poject, Thematic Pioity 6.2 Sustainable

More information

Reader & ReaderT Monad (11A) Young Won Lim 8/20/18

Reader & ReaderT Monad (11A) Young Won Lim 8/20/18 Copyight (c) 2016-2018 Young W. Lim. Pemission is ganted to copy, distibute and/o modify this document unde the tems of the GNU Fee Documentation License, Vesion 1.2 o any late vesion published by the

More information

INDEXATION OF WEB PAGES BASED ON THEIR VISUAL RENDERING

INDEXATION OF WEB PAGES BASED ON THEIR VISUAL RENDERING INDEXATION OF WEB PAGES BASED ON THEIR VISUAL RENDERING Emmanuel Buno Univesité du Sud Toulon-Va / LSIS CNRS BP 20132, F-83957 La Gade buno@univ-tln.f Nicolas Faessel LSIS CNRS Domaine Univesitaie de Saint-Jéôme

More information

Experimental and numerical simulation of the flow over a spillway

Experimental and numerical simulation of the flow over a spillway Euopean Wate 57: 253-260, 2017. 2017 E.W. Publications Expeimental and numeical simulation of the flow ove a spillway A. Seafeim *, L. Avgeis, V. Hissanthou and K. Bellos Depatment of Civil Engineeing,

More information

IP Network Design by Modified Branch Exchange Method

IP Network Design by Modified Branch Exchange Method Received: June 7, 207 98 IP Netwok Design by Modified Banch Method Kaiat Jaoenat Natchamol Sichumoenattana 2* Faculty of Engineeing at Kamphaeng Saen, Kasetsat Univesity, Thailand 2 Faculty of Management

More information

XFVHDL: A Tool for the Synthesis of Fuzzy Logic Controllers

XFVHDL: A Tool for the Synthesis of Fuzzy Logic Controllers XFVHDL: A Tool fo the Synthesis of Fuzzy Logic Contolles E. Lago, C. J. Jiménez, D. R. López, S. Sánchez-Solano and A. Baiga Instituto de Micoelectónica de Sevilla. Cento Nacional de Micoelectónica, Edificio

More information

Lecture # 04. Image Enhancement in Spatial Domain

Lecture # 04. Image Enhancement in Spatial Domain Digital Image Pocessing CP-7008 Lectue # 04 Image Enhancement in Spatial Domain Fall 2011 2 domains Spatial Domain : (image plane) Techniques ae based on diect manipulation of pixels in an image Fequency

More information

Obstacle Avoidance of Autonomous Mobile Robot using Stereo Vision Sensor

Obstacle Avoidance of Autonomous Mobile Robot using Stereo Vision Sensor Obstacle Avoidance of Autonomous Mobile Robot using Steeo Vision Senso Masako Kumano Akihisa Ohya Shin ichi Yuta Intelligent Robot Laboatoy Univesity of Tsukuba, Ibaaki, 35-8573 Japan E-mail: {masako,

More information

MIS to Prepress ICS. Version Date: File: ICS-MIS-Prepress-1.01.doc,.pdf. Origination & Prepress WG

MIS to Prepress ICS. Version Date: File: ICS-MIS-Prepress-1.01.doc,.pdf. Origination & Prepress WG MIS to Pepess ICS Vesion 1.01 Date: 2006-01-02 File: ICS-MIS-Pepess-1.01.doc,.pdf Oigination & Pepess WG Abstact This ICS defines the Inteface between the MIS and Pepess. It specifies the Pocesses fo a

More information

A VECTOR PERTURBATION APPROACH TO THE GENERALIZED AIRCRAFT SPARE PARTS GROUPING PROBLEM

A VECTOR PERTURBATION APPROACH TO THE GENERALIZED AIRCRAFT SPARE PARTS GROUPING PROBLEM Accepted fo publication Intenational Jounal of Flexible Automation and Integated Manufactuing. A VECTOR PERTURBATION APPROACH TO THE GENERALIZED AIRCRAFT SPARE PARTS GROUPING PROBLEM Nagiza F. Samatova,

More information

Information Retrieval. CS630 Representing and Accessing Digital Information. IR Basics. User Task. Basic IR Processes

Information Retrieval. CS630 Representing and Accessing Digital Information. IR Basics. User Task. Basic IR Processes CS630 Repesenting and Accessing Digital Infomation Infomation Retieval: Basics Thosten Joachims Conell Univesity Infomation Retieval Basics Retieval Models Indexing and Pepocessing Data Stuctues ~ 4 lectues

More information

Configuring RSVP-ATM QoS Interworking

Configuring RSVP-ATM QoS Interworking Configuing RSVP-ATM QoS Intewoking Last Updated: Januay 15, 2013 This chapte descibes the tasks fo configuing the RSVP-ATM QoS Intewoking featue, which povides suppot fo Contolled Load Sevice using RSVP

More information

IP Multicast Simulation in OPNET

IP Multicast Simulation in OPNET IP Multicast Simulation in OPNET Xin Wang, Chien-Ming Yu, Henning Schulzinne Paul A. Stipe Columbia Univesity Reutes Depatment of Compute Science 88 Pakway Dive South New Yok, New Yok Hauppuage, New Yok

More information

Functional Dependencies in OWL ABoxes

Functional Dependencies in OWL ABoxes Functional Dependencies in OWL ABoxes Jean-Paul Calbimonte, Fabio Poto, C. Maia Keet 3 École Polytechnique Fédéale de Lausanne (EPFL) Database Laboatoy - Switzeland jean-paul.calbimonte@epfl.ch National

More information

Conservation Law of Centrifugal Force and Mechanism of Energy Transfer Caused in Turbomachinery

Conservation Law of Centrifugal Force and Mechanism of Energy Transfer Caused in Turbomachinery Poceedings of the 4th WSEAS Intenational Confeence on luid Mechanics and Aeodynamics, Elounda, Geece, August 1-3, 006 (pp337-34) Consevation Law of Centifugal oce and Mechanism of Enegy Tansfe Caused in

More information

A Novel Automatic White Balance Method For Digital Still Cameras

A Novel Automatic White Balance Method For Digital Still Cameras A Novel Automatic White Balance Method Fo Digital Still Cameas Ching-Chih Weng 1, Home Chen 1,2, and Chiou-Shann Fuh 3 Depatment of Electical Engineeing, 2 3 Gaduate Institute of Communication Engineeing

More information

Approaches to Automatic Programming

Approaches to Automatic Programming MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.mel.com Appoaches to Automatic Pogamming Chales Rich, Richad C. Wates TR92-04 July 1992 Abstact This pape is an oveview of cuent appoaches to automatic

More information

Parallel processing model for XML parsing

Parallel processing model for XML parsing Recent Reseaches in Communications, Signals and nfomation Technology Paallel pocessing model fo XML pasing ADRANA GEORGEVA Fac. Applied Mathematics and nfomatics Technical Univesity of Sofia, TU-Sofia

More information

Input Layer f = 2 f = 0 f = f = 3 1,16 1,1 1,2 1,3 2, ,2 3,3 3,16. f = 1. f = Output Layer

Input Layer f = 2 f = 0 f = f = 3 1,16 1,1 1,2 1,3 2, ,2 3,3 3,16. f = 1. f = Output Layer Using the Gow-And-Pune Netwok to Solve Poblems of Lage Dimensionality B.J. Biedis and T.D. Gedeon School of Compute Science & Engineeing The Univesity of New South Wales Sydney NSW 2052 AUSTRALIA bbiedis@cse.unsw.edu.au

More information

Shortest Paths for a Two-Robot Rendez-Vous

Shortest Paths for a Two-Robot Rendez-Vous Shotest Paths fo a Two-Robot Rendez-Vous Eik L Wyntes Joseph S B Mitchell y Abstact In this pape, we conside an optimal motion planning poblem fo a pai of point obots in a plana envionment with polygonal

More information

2. PROPELLER GEOMETRY

2. PROPELLER GEOMETRY a) Fames of Refeence 2. PROPELLER GEOMETRY 10 th Intenational Towing Tank Committee (ITTC) initiated the pepaation of a dictionay and nomenclatue of ship hydodynamic tems and this wok was completed in

More information

Comparisons of Transient Analytical Methods for Determining Hydraulic Conductivity Using Disc Permeameters

Comparisons of Transient Analytical Methods for Determining Hydraulic Conductivity Using Disc Permeameters Compaisons of Tansient Analytical Methods fo Detemining Hydaulic Conductivity Using Disc Pemeametes 1,,3 Cook, F.J. 1 CSRO Land and Wate, ndoooopilly, Queensland The Univesity of Queensland, St Lucia,

More information

Lecture 8 Introduction to Pipelines Adapated from slides by David Patterson

Lecture 8 Introduction to Pipelines Adapated from slides by David Patterson Lectue 8 Intoduction to Pipelines Adapated fom slides by David Patteson http://www-inst.eecs.bekeley.edu/~cs61c/ * 1 Review (1/3) Datapath is the hadwae that pefoms opeations necessay to execute pogams.

More information

Pipes, connections, channels and multiplexors

Pipes, connections, channels and multiplexors Pipes, connections, channels and multiplexos Fancisco J. Ballesteos ABSTRACT Channels in the style of CSP ae a poeful abstaction. The ae close to pipes and connections used to inteconnect system and netok

More information

A Novel Image-Based Rendering System With A Longitudinally Aligned Camera Array

A Novel Image-Based Rendering System With A Longitudinally Aligned Camera Array EUOGAPHICS 2 / A. de Sousa, J.C. Toes Shot Pesentations A Novel Image-Based endeing System With A Longitudinally Aligned Camea Aay Jiang Li, Kun Zhou, Yong Wang and Heung-Yeung Shum Micosoft eseach, China

More information

Prioritized Traffic Recovery over GMPLS Networks

Prioritized Traffic Recovery over GMPLS Networks Pioitized Taffic Recovey ove GMPLS Netwoks 2005 IEEE. Pesonal use of this mateial is pemitted. Pemission fom IEEE mu be obtained fo all othe uses in any cuent o futue media including epinting/epublishing

More information

A Minutiae-based Fingerprint Matching Algorithm Using Phase Correlation

A Minutiae-based Fingerprint Matching Algorithm Using Phase Correlation A Minutiae-based Fingepint Matching Algoithm Using Phase Coelation Autho Chen, Weiping, Gao, Yongsheng Published 2007 Confeence Title Digital Image Computing: Techniques and Applications DOI https://doi.og/10.1109/dicta.2007.4426801

More information

ANALYTIC PERFORMANCE MODELS FOR SINGLE CLASS AND MULTIPLE CLASS MULTITHREADED SOFTWARE SERVERS

ANALYTIC PERFORMANCE MODELS FOR SINGLE CLASS AND MULTIPLE CLASS MULTITHREADED SOFTWARE SERVERS ANALYTIC PERFORMANCE MODELS FOR SINGLE CLASS AND MULTIPLE CLASS MULTITHREADED SOFTWARE SERVERS Daniel A Menascé Mohamed N Bennani Dept of Compute Science Oacle, Inc Geoge Mason Univesity 1211 SW Fifth

More information

Embeddings into Crossed Cubes

Embeddings into Crossed Cubes Embeddings into Cossed Cubes Emad Abuelub *, Membe, IAENG Abstact- The hypecube paallel achitectue is one of the most popula inteconnection netwoks due to many of its attactive popeties and its suitability

More information

4.2. Co-terminal and Related Angles. Investigate

4.2. Co-terminal and Related Angles. Investigate .2 Co-teminal and Related Angles Tigonometic atios can be used to model quantities such as

More information

A General Characterization of Representing and Determining Fuzzy Spatial Relations

A General Characterization of Representing and Determining Fuzzy Spatial Relations 7 The Intenational Aab Jounal of Infomation Technolog A Geneal Chaacteization of Repesenting and Detemining Fuzz Spatial Relations Lui Bai and Li Yan 2 College of Infomation Science and Engineeing, Notheasten

More information

Efficient protection of many-to-one. communications

Efficient protection of many-to-one. communications Efficient potection of many-to-one communications Miklós Molná, Alexande Guitton, Benad Cousin, and Raymond Maie Iisa, Campus de Beaulieu, 35 042 Rennes Cedex, Fance Abstact. The dependability of a netwok

More information

Reachable State Spaces of Distributed Deadlock Avoidance Protocols

Reachable State Spaces of Distributed Deadlock Avoidance Protocols Reachable State Spaces of Distibuted Deadlock Avoidance Potocols CÉSAR SÁNCHEZ and HENNY B. SIPMA Stanfod Univesity We pesent a family of efficient distibuted deadlock avoidance algoithms with applications

More information

n If S is in convex position, then thee ae exactly k convex k-gons detemined by subsets of S. In geneal, howeve, S may detemine fa fewe convex k-gons.

n If S is in convex position, then thee ae exactly k convex k-gons detemined by subsets of S. In geneal, howeve, S may detemine fa fewe convex k-gons. Counting Convex Polygons in Plana Point Sets Joseph S. B. Mitchell a;1, Günte Rote b, Gopalakishnan Sundaam c, and Gehad Woeginge b a Applied Mathematics and Statistics, SUNY Stony Book, NY 11794-3600.

More information

The International Conference in Knowledge Management (CIKM'94), Gaithersburg, MD, November 1994.

The International Conference in Knowledge Management (CIKM'94), Gaithersburg, MD, November 1994. The Intenational Confeence in Knowledge Management (CIKM'94), Gaithesbug, MD, Novembe 994. Hashing by Poximity to Pocess Duplicates in Spatial Databases Walid G. Aef Matsushita Infomation Technology Laboatoy

More information

arxiv: v1 [cs.lo] 3 Dec 2018

arxiv: v1 [cs.lo] 3 Dec 2018 A high-level opeational semantics fo hadwae weak memoy models axiv:1812.00996v1 [cs.lo] 3 Dec 2018 Abstact Robet J. Colvin School of Electical Engineeing and Infomation Technology The Univesity of Queensland

More information

Properties of Tilings by Convex Pentagons

Properties of Tilings by Convex Pentagons eview Foma, 1, 113 18, 006 Popeties of Tilings by Convex Pentagons Teuhisa SUGIMOTO 1 * and Tohu OGAWA,3 1 The Institute of Statistical Mathematics, 4-6-7 Minami-Azabu, Minato-ku, Tokyo 106-8569, Japan

More information

Improvement of First-order Takagi-Sugeno Models Using Local Uniform B-splines 1

Improvement of First-order Takagi-Sugeno Models Using Local Uniform B-splines 1 Impovement of Fist-ode Takagi-Sugeno Models Using Local Unifom B-splines Felipe Fenández, Julio Gutiéez, Gacián Tiviño and Juan Calos Cespo Dep. Tecnología Fotónica, Facultad de Infomática Univesidad Politécnica

More information

Conversion Functions for Symmetric Key Ciphers

Conversion Functions for Symmetric Key Ciphers Jounal of Infomation Assuance and Secuity 2 (2006) 41 50 Convesion Functions fo Symmetic Key Ciphes Deba L. Cook and Angelos D. Keomytis Depatment of Compute Science Columbia Univesity, mail code 0401

More information

An Optimised Density Based Clustering Algorithm

An Optimised Density Based Clustering Algorithm Intenational Jounal of Compute Applications (0975 8887) Volume 6 No.9, Septembe 010 An Optimised Density Based Clusteing Algoithm J. Hencil Pete Depatment of Compute Science St. Xavie s College, Palayamkottai,

More information

3D Periodic Human Motion Reconstruction from 2D Motion Sequences

3D Periodic Human Motion Reconstruction from 2D Motion Sequences 3D Peiodic Human Motion Reconstuction fom D Motion Sequences Zonghua Zhang and Nikolaus F. Toje BioMotionLab, Depatment of Psychology Queen s Univesity, Canada zhang, toje@psyc.queensu.ca Abstact In this

More information

Efficient Execution Path Exploration for Detecting Races in Concurrent Programs

Efficient Execution Path Exploration for Detecting Races in Concurrent Programs IAENG Intenational Jounal of Compute Science, 403, IJCS_40_3_02 Efficient Execution Path Exploation fo Detecting Races in Concuent Pogams Theodous E. Setiadi, Akihiko Ohsuga, and Mamou Maekaa Abstact Concuent

More information

Any modern computer system will incorporate (at least) two levels of storage:

Any modern computer system will incorporate (at least) two levels of storage: 1 Any moden compute system will incopoate (at least) two levels of stoage: pimay stoage: andom access memoy (RAM) typical capacity 32MB to 1GB cost pe MB $3. typical access time 5ns to 6ns bust tansfe

More information

Evaluation of Partial Path Queries on XML data

Evaluation of Partial Path Queries on XML data Evaluation of Patial Path Queies on XML data Stefanos Souldatos Dept of EE & CE, NTUA stef@dblab.ntua.g Theodoe Dalamagas Dept of EE & CE, NTUA dalamag@dblab.ntua.g Xiaoying Wu Dept. of CS, NJIT xw43@njit.edu

More information

What is a System:- Characteristics of a system:-

What is a System:- Characteristics of a system:- Unit 1 st :- What is a System:- A system is an odely gouping of intedependent components linked togethe accoding to a plan to achieve a specific objective. The study of system concepts has thee basic implications:

More information

An Improved Resource Reservation Protocol

An Improved Resource Reservation Protocol Jounal of Compute Science 3 (8: 658-665, 2007 SSN 549-3636 2007 Science Publications An mpoved Resouce Resevation Potocol Desie Oulai, Steven Chambeland and Samuel Piee Depatment of Compute Engineeing

More information

Evaluation of Partial Path Queries on XML Data

Evaluation of Partial Path Queries on XML Data Evaluation of Patial Path Queies on XML Data Stefanos Souldatos Dept of EE & CE NTUA, Geece stef@dblab.ntua.g Theodoe Dalamagas Dept of EE & CE NTUA, Geece dalamag@dblab.ntua.g Xiaoying Wu Dept. of CS

More information

Query Language #1/3: Relational Algebra Pure, Procedural, and Set-oriented

Query Language #1/3: Relational Algebra Pure, Procedural, and Set-oriented Quey Language #1/3: Relational Algeba Pue, Pocedual, and Set-oiented To expess a quey, we use a set of opeations. Each opeation takes one o moe elations as input paamete (set-oiented). Since each opeation

More information

arxiv: v2 [physics.soc-ph] 30 Nov 2016

arxiv: v2 [physics.soc-ph] 30 Nov 2016 Tanspotation dynamics on coupled netwoks with limited bandwidth Ming Li 1,*, Mao-Bin Hu 1, and Bing-Hong Wang 2, axiv:1607.05382v2 [physics.soc-ph] 30 Nov 2016 1 School of Engineeing Science, Univesity

More information

On Error Estimation in Runge-Kutta Methods

On Error Estimation in Runge-Kutta Methods Leonado Jounal of Sciences ISSN 1583-0233 Issue 18, Januay-June 2011 p. 1-10 On Eo Estimation in Runge-Kutta Methods Ochoche ABRAHAM 1,*, Gbolahan BOLARIN 2 1 Depatment of Infomation Technology, 2 Depatment

More information

Scaling Location-based Services with Dynamically Composed Location Index

Scaling Location-based Services with Dynamically Composed Location Index Scaling Location-based Sevices with Dynamically Composed Location Index Bhuvan Bamba, Sangeetha Seshadi and Ling Liu Distibuted Data Intensive Systems Laboatoy (DiSL) College of Computing, Geogia Institute

More information

Clustering Interval-valued Data Using an Overlapped Interval Divergence

Clustering Interval-valued Data Using an Overlapped Interval Divergence Poc. of the 8th Austalasian Data Mining Confeence (AusDM'9) Clusteing Inteval-valued Data Using an Ovelapped Inteval Divegence Yongli Ren Yu-Hsn Liu Jia Rong Robet Dew School of Infomation Engineeing,

More information

GCC-AVR Inline Assembler Cookbook Version 1.2

GCC-AVR Inline Assembler Cookbook Version 1.2 GCC-AVR Inline Assemble Cookbook Vesion 1.2 About this Document The GNU C compile fo Atmel AVR isk pocessos offes, to embed assembly language code into C pogams. This cool featue may be used fo manually

More information

Administrative Scope and Role Hierarchy Operations

Administrative Scope and Role Hierarchy Operations Administative Scope and Role Hieachy Opeations Jason Campton and Geoge Loizou School of Compute Science and Infomation Systems Bikbeck College, Univesity of London ABSTRACT The ARBAC97 model makes an impotant

More information

Modelling, simulation, and performance analysis of a CAN FD system with SAE benchmark based message set

Modelling, simulation, and performance analysis of a CAN FD system with SAE benchmark based message set Modelling, simulation, and pefomance analysis of a CAN FD system with SAE benchmak based message set Mahmut Tenuh, Panagiotis Oikonomidis, Peiklis Chachalakis, Elias Stipidis Mugla S. K. Univesity, TR;

More information

NODAL AND LOOP ANALYSIS TECHNIQUES

NODAL AND LOOP ANALYSIS TECHNIQUES NODAL AND LOOP ANALYSIS TECHNIQUES LEANING GOALS NODAL ANALYSIS LOOP ANALYSIS Deelop systematic techniques to determine all the oltages and currents in a circuit NODE ANALYSIS One of the systematic ways

More information

The Java Virtual Machine. Compiler construction The structure of a frame. JVM stacks. Lecture 2

The Java Virtual Machine. Compiler construction The structure of a frame. JVM stacks. Lecture 2 Compile constuction 2009 Lectue 2 Code geneation 1: Geneating code The Java Vitual Machine Data types Pimitive types, including intege and floating-point types of vaious sizes and the boolean type. The

More information

Machine Learning for Automatic Classification of Web Service Interface Descriptions

Machine Learning for Automatic Classification of Web Service Interface Descriptions Machine Leaning fo Automatic Classification of Web Sevice Inteface Desciptions Amel Bennaceu 1, Valéie Issany 1, Richad Johansson 4, Alessando Moschitti 3, Romina Spalazzese 2, and Daniel Sykes 1 1 Inia,

More information

HISTOGRAMS are an important statistic reflecting the

HISTOGRAMS are an important statistic reflecting the JOURNAL OF L A T E X CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 1 D 2 HistoSketch: Disciminative and Dynamic Similaity-Peseving Sketching of Steaming Histogams Dingqi Yang, Bin Li, Laua Rettig, and Philippe

More information

ASSIGN 01: Due Monday Feb 04 PART 1 Get a Sketchbook: 8.5 x 11 (Minimum size 5 x7 ) fo keeping a design jounal and a place to keep poject eseach & ideas. Make sue you have you Dopbox account and/o Flash

More information

Multidimensional Fuzzy Association Rules for Developing Decision Support System at Petra Christian University

Multidimensional Fuzzy Association Rules for Developing Decision Support System at Petra Christian University Multidimensional Fuzzy ssociation Rules fo eveloping ecision Suppot System at Peta histian Univesity Yulia 1, Siget Wibisono 2, Rolly Intan 1 1,2 Peta histian Univesity, Suabaya, Indonesia 1 {yulia, intan}@peta.ac.id,

More information

Multidimensional Testing

Multidimensional Testing Multidimensional Testing QA appoach fo Stoage netwoking Yohay Lasi Visuality Systems 1 Intoduction Who I am Yohay Lasi, QA Manage at Visuality Systems Visuality Systems the leading commecial povide of

More information

BUPT at TREC 2006: Spam Track

BUPT at TREC 2006: Spam Track BUPT at TREC 2006: Spam Tac Zhen Yang, Wei Xu, Bo Chen, Weian Xu, and Jun Guo PRIS Lab, School of Infomation Engineeing, Beijing Univesity of Posts and Telecommunications, 100876, Beijing, China yangzhen@pis.edu.cn

More information

A Memory Efficient Array Architecture for Real-Time Motion Estimation

A Memory Efficient Array Architecture for Real-Time Motion Estimation A Memoy Efficient Aay Achitectue fo Real-Time Motion Estimation Vasily G. Moshnyaga and Keikichi Tamau Depatment of Electonics & Communication, Kyoto Univesity Sakyo-ku, Yoshida-Honmachi, Kyoto 66-1, JAPAN

More information