Verbalizing Business Rules (Part 4)

Terry   Halpin
Terry Halpin Professor of Computer Science, INTI International University (Malaysia) Read Author Bio || Read All Articles by Terry Halpin

Business rules need to be validated by business domain experts, so should be specified using concepts and languages easily understood by business people.  This is the fourth in a series of articles on expressing business rules formally in a high-level, textual language.

The first article [4] discussed criteria for a business rules language, and verbalization of simple uniqueness and mandatory constraints on binary associations.  The second article [5] discussed hyphen-binding, and verbalization of internal uniqueness constraints that span a whole association, or that apply to n-ary associations.  The third article [6] discussed verbalization of basic external uniqueness constraints.

The current article discusses the relational-style verbalization of external uniqueness constraints involving nesting or long join paths, as well as attribute-style verbalization of uniqueness constraints and simple mandatory constraints.

Verbalization of external uniqueness constraints involving nesting

Consider the output report shown in Table 1.  This table is used to record which countries play which sports, as well as the ranking assigned (if known).  In the sample population, Australia and Great Britain are ranked first and second respectively in cricket, and the United States is ranked first in baseball.  We record the fact that New Zealand plays cricket, but we don't yet know its ranking in that sport ('?' denotes a null value).

Table 1. Sport Rankings of Countries.

Country

Sport

Rank

AU

Cricket

1

GB

Cricket

2

NZ

Cricket

?

US

Baseball

1

This situation may be schematized in ORM as shown in Figure 1.  Here the fact type Country plays Sport is objectified as Play, and this nested object type is then used in the fact type Play achieved Rank.  The exclamation mark in 'Play !' declares the Play object type to be independent (i.e., instances of it may exist without playing other roles -- the achieved role is optional).

Figure 1.  The external uniqueness constraint forbids ties.

The internal uniqueness constraints indicate that the Play association is many:many, and the achieved association is many:1.  The external uniqueness constraint declares a 'no-ties' rule, meaning that for any given sport and (non-null) rank, at most one country that plays that sport achieved that rank.  For example, the rank of 'first' in cricket can't be assigned to both Australia and Great Britain.

In most cases where an external uniqueness constraint involves nesting, the constraint can be verbalized naturally as above.  But this assumes the verb phrase in the outer fact type also makes sense when applied to just the target object type (here Country) in the inner fact type, and that the inner fact type includes a reading from that object type.  A general verbalization technique that makes no such assumptions can be provided by pre-declaring the context in which the constraint is to be interpreted.  For example:

Context: Country plays Sport is objectified as Play.

Play achieved Rank.

Constraint: each Sport, Rank combination is associated with at most one Country.

The UML class diagram shown in Figure 2 models the same situation.  UML has no graphic symbol for an external uniqueness constraint, so this constraint is expressed here as an informal comment in a note attached to the model elements relevant to the constraint.  Alternatively, it could be expressed formally in OCL [9], but the OCL syntax is currently too technical for reliable validation by business people.

Figure 2.  The 'no-ties' constraint expressed informally as a note in UML.

Verbalization of external uniqueness constraints involving long join paths

Figure 3 shows an ORM schema fragment for an application dealing with international direct-dial phone numbers for cities.  The ' <<' indicators reverse the normal downwards/rightwards reading direction of predicates.  In navigating ORM schemas, a conceptual join (or 'object join') occurs when passing through an object type, because the object playing the entry role is the same object playing the exit role.[3]  The two roles (colored yellow) spanned by the right-most external uniqueness constraint are projected from a role path that involves three conceptual joins, on Country, State, and City.  Since all the join roles (shaded green) are mandatory, the joins are all inner joins.

Figure 3.  This model includes an external uniqueness constraint over roles projected from a long join path.

Conceptual joins needn't entail relational joins, since relations may combine multiple fact types.  For instance, the ORM schema maps by default to the relational schema shown in Figure 4.  At this level, the external uniqueness constraint is enforced by naturally joining the tables on countryName and then ensuring that the regionNr, areaCode bag-projection is unique (a constraint easily coded in SQL).  The conceptual joins on State and City come for free at the relational level, since the relevant roles map to the same table.

Figure 4.  Relational schema mapped from the conceptual schema in Figure 3.

Here the region number usually identifies a country (e.g., 61 for Australia) but not always (e.g., the United States and Canada both have the region number 1).  For the purposes of this example, let us simplify reality a little by assuming that within a given country, the area code identifies a city (e.g., regionNr = 61, areaCode = 7 identifies the Australian city 'Brisbane').  As with the previous example, verbalization of an external uniqueness constraint over a long join path is easier if a context has been pre-declared. In this case, the constraint verbalizes as follows.

Context: City has AreaCode

and is in State that is in Country that has RegionNr.

Constraint: each RegionNr, AreaCode combination is associated with

at most one City and at most one State and at most one Country

In this verbalization, the 'at most one' constraints on State and Country could be elided because they are implied by simple uniqueness constraints (e.g., each City is in at most one State), but the verbalization is designed to handle the general case where such additional constraints might not apply.  As neither ER nor UML include the notion of join constraints, examples in those notations will not be given.

Attribute-style Verbalization of Uniqueness and Simple Mandatory Constraints

Figure 5 depicts a simple schema in both ORM and UML notations.  Previously, all constraints have been verbalized in relational-style, using predicate readings.  We now consider how to verbalize uniqueness constraints in attribute-style for binary fact types (possibly represented as attributes).

In UML models, attribute-style rules may make use of both attribute names and association end names.  In ORM, which makes no use of attributes as base constructs, attribute-style rules make use of role names (shown here in square brackets).  Here the role name 'natives' means "persons born in that country."

While the singular or plural nature of the chosen role names or attribute names may help indicate to readers whether certain uniqueness constraints apply, these are merely informal hints, which are potentially unstable (owing to schema changes) and which may be of little use in other natural languages (e.g., Japanese) that often fail to distinguish between singular and plural.

Figure 5.  A simple schema in (a) ORM and (b) UML.

If an object type (e.g., Person) is assigned an attribute (e.g., birthDate), this may be viewed as a property of the object type.  For any binary association of the form A r1 r2 B, where A and B are object types (not necessarily distinct) and r1 and r2 are the roles of the predicate read from A to B, then r2 is a far role of A, and r1 is a far role of B.

For example, in the association Person visited Country, countriesVisited is a far role of Person, and visitors is a far role of Country.  For attribute-style verbalization, the far roles of an object type may also be treated as properties.

There are two basic ways that property names may be used in verbalization.  The first way is to assume an underlying association of the form ObjectType has Property (e.g., Person has birthDate, Person has countriesVisited), and then use relational-style verbalization of the constraints in conjunction with quantifiers (e.g., zero or more, at least one, at most one, exactly one).  As usual, the phrase 'exactly one' is shorthand for 'at least one and at most one'.

Using this technique, the uniqueness and mandatory constraints for Figure 5 may now be verbalized in attribute-style as follows.

Each Person has zero or more countriesVisited.
Each Person has exactly one birthCountry.
Each Person has exactly one birthDate.
Each Country has zero or more visitors.
Each Country has zero or more natives.
Each Date has zero or more personsBornOn.

In UML, Date would normally be considered a data type, on which the attribute birthDate is defined, and an attribute name such as 'personsBornOn' would not be supplied.  However the above 'constraint' stated explicitly for Date is implicit in UML.

The second way to verbalize constraints in attribute-style is to pre-declare the object type as the context (using either 'For each' or 'Context:'), and then constrain each of its properties using predefined unary predicates (e.g., is unique).  Using this second technique, the presence or absence of uniqueness and mandatory constraints for this example may be verbalized as follows.

For each Person

countriesVisited is multi-valued
birthCountry is unique
birthDate is unique
countriesVisited is optional
birthCountry is mandatory
birthDate is mandatory

For each Country

visitors is multi-valued
natives is multi-valued
visitors is optional
natives is optional

If desired, the constraints from the viewpoint of Date may be verbalized in ORM explicitly as:

For each Date

personsBornOn is multi-valued
personsBornOn is optional

Attribute-style verbalization for simple internal constraints is often less natural than relational-style.  However attribute-style notation is useful for providing compact verbalization of some complex constraints, as well as derivation rules that rely on mathematical computation.  (This will be discussed in later articles.)

To illustrate the utility of attribute-style for some constraints, consider Figure 6.  The external uniqueness constraint was verbalized in relational-style in [6] as follows:

Given any Date1 and Date2

there is at most one Period that began on Date1
                and ended on Date2.

In this example, we have added role names in the ORM schema for startDate and endDate.  If desired, these names could be used in place of 'Date1' and 'Date2' in the relational-style verbalization.

The external uniqueness constraint tells us that each combination of startDate and endDate applies to at most one Period.  The attributes corresponding to these roles appear in the extended UML class diagram, where the constraint under consideration is expressed by appending the non-standard notation '{U1}' after the attributes to indicate these are subject to the same uniqueness constraint.

Figure 6 An external uniqueness constraint in (a) ORM and (b) an extended version of UML.

Regardless of which notation is used, the external uniqueness constraint may be verbalized in attribute-style as follows.

At most one Period has the same combination of startDate and endDate.

That completes our basic coverage of verbalization of uniqueness and simple mandatory constraints.  The next article discusses advanced aspects of verbalizing mandatory constraints.  In particular, it considers verbalization of mandatory constraints on roles of n-ary associations, and disjunctive mandatory constraints (also known as inclusive-or constraints) over sets of roles.

References

[1]  R. Barker.  CASE*Method: Tasks and Deliverables.  Addison-Wesley, Wokingham, England, 1990.

[2]  T.A. Halpin.  Information Modeling and Relational Databases.  Morgan Kaufmann, San Francisco, 2001.

[3]  T.A. Halpin.  "Join Constraints," Proc. EMMSAD'02: 7th Int. IFIP WG8.1 Workshop on Evaluation of Modeling Methods in Systems Analysis and Design.  Toronto, (June, 2002).  Available online at http://www.orm.net/pdf/JoinConstraints.pdf  return to article

[4]  T.A. Halpin.  "Verbalizing Business Rules (part 1)," Business Rules Journal, Vol. 4, No. 4 (April 2003).  URL: http://www.BRCommunity.com/a2003/b138.html  return to article

[5]  T.A. Halpin.  "Verbalizing Business Rules (part 2)," Business Rules Journal, Vol. 4, No. 6 (June 2003).  URL: http://www.BRCommunity.com/a2003/b152.html  return to article

[6]  T.A. Halpin.  "Verbalizing Business Rules (part 3)," Business Rules Journal, Vol. 4, No. 8 (August 2003).  URL: http://www.BRCommunity.com/a2003/b163.html  return to article

[7]  T.A. Halpin, K. Evans, P. Hallock, & B. MacLean.  Database Modeling with Microsoft Visio for Enterprise Architects.  Morgan Kaufmann, San Francisco, 2003.

[8]  Object Management Group.  UML 2.0 Infrastructure.  Object Management Group, 2003.  URL:  http://www.omg.org/uml

[9]  Object Management Group.  UML 2.0 Object Constraint Language.  Object Management Group, 2003.  URL:  http://www.omg.org/uml  return to article

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Standard citation for this article:


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Terry Halpin , "Verbalizing Business Rules (Part 4)" Business Rules Journal Vol. 4, No. 10, (Oct. 2003)
URL: http://www.brcommunity.com/a2003/b172.html

About our Contributor:


Terry   Halpin
Terry Halpin Professor of Computer Science, INTI International University (Malaysia)

Dr. Terry Halpin, BSc, DipEd, BA, MLitStud, PhD, is a Professor of Computer Science at INTI International University, Malaysia, and a data modeling consultant. His prior industrial background includes many years of research and development of data modeling technology at Asymetrix Corporation, InfoModelers Inc., Visio Corporation, Microsoft Corporation, and LogicBlox. His previous academic background includes many years teaching computer science at the University of Queensland (Australia) and Neumont University (USA). His current research focuses on conceptual modeling and conceptual query technology. His doctoral thesis formalized Object-Role Modeling (ORM/NIAM), and his publications include over 200 technical papers and seven books, including Information Modeling and Relational Databases, 2nd Edition (2008: Morgan Kaufmann). Dr. Halpin may be reached directly at t.halpin@live.com.

Read All Articles by Terry Halpin

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