SEMANTIC DESIGN PATTERNS FOR BUSINESS PROCESSES

Lobna Makni, Nahla Zaaboub Haddar and Hanene Ben-Abdallah

Faculty of Economics and Management Sciences, Mir@cl Laboratory, Sfax University, Sfax, Tunisia

Keywords: Semantic Business Process Patterns, Business process models, Conflicts, Construction rules.

Abstract: Both the academic and industrial communities are increasingly interested in developing methods and tools

for automating the design of business process models. In this context, several approaches were proposed to

make modeling easier and to enhance the quality of the resulting artifacts. To achieve these objectives, these

approaches are based on pattern reuse. Despite the agreed uppon advantages of patterns in accelerating the

design process and improving the produced model quality, a few researchers showed how to construct

business process patterns. In this paper, we describe an approach to construct Semantic Business Process

Patterns (SB2P) from a set of process models. A SB2P is a pattern synthesized from a set of process models

belonging to the same business domain. It is composed of process fragments that are semantically close but

may have structural and/or behavioral differences.

1 INTRODUCTION

Process modeling is considered a labor intensive

task, whose outcome depends on personal domain

expertise. Designers with low modeling competence

or domain expertise may introduce errors or

inconsistencies in the designed model which may

lead to bad performance and high process costs

(Müller et al., 2007). Thus, modeling tools must

incorporate techniques to help inexperienced

designers to work in an efficient manner. In fact,

there is a wide agreement that reuse can accelerate

the design process and produce high quality

solutions by adopting best practices (Buschmann et

al., 2007), (Tran et al., 2007), (Montero et al., 2010).

The various modeling approaches based on reuse can

be calssified into two main classes: reference

modeling and pattern reuse.

Reference modeling aims to increase productivity

by using configurable process models. A

configurable process model is a modeling artifact

that captures a family of process models and allows

analysts to understand what these process models

share, what their differences are, and why and how

these differences occur (Rosa et al., 2010).

Configured models are created for a specific domain

and are meant to be customized in different

application projects. They are constructed by

merging models after detecting similarities and

differences between them (Li et al., 2009) (Dijkman,

2007). On the other hand, a variety of patterns for

business processes have been proposed in the

literature like workflow patterns (der Aalst et al.,

2003), workflow activity patterns (Thom et al., 2009)

and action patterns (Smirnov et al., 2009). Workflow

patterns focus on specific aspects like control flow,

data flow and resource assignments. Workflow

activity patterns refer to the description of a recurrent

business function as it can be frequently found in

business processes (Thom et al., 2009); the authors

in (Thom et al., 2009) propose seven activity patterns

through an extensive literature study of business

process types (e.g., Approval, Question-answer,

Decision Making, …). In contrast to workflow

patterns, action patterns are closely related to the

semantic content of a process model. In addition,

unlike reference models, action patterns are abstract

enough to be applicable in various domains

(Smirnov et al., 2009).

In this paper, we propose a pattern concept that

combines the advantages of both reference models

and action patterns: focusing on structural concepts

specific to business processes, accounting for the

semantic aspects, and ensuring a high level of

abstraction to provide for a wide reuse range. More

specifically, we define the concept of Semantic

Business Process Pattern (SB2P). A SB2P is a

pattern synthesized from a set of “good-quality”

process models belonging to the same business

domain. It is composed of process fragments that are

Makni L., Zaaboub Haddar N. and Ben-abdallah H..

SEMANTIC DESIGN PATTERNS FOR BUSINESS PROCESSES.

DOI: 10.5220/0003653500830087

In Proceedings of the 6th International Conference on Software and Database Technologies (ICSOFT-2011), pages 83-87

ISBN: 978-989-8425-76-8

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

common to the source models but it may contain

fragments with different structural and/or behavioral

representations in the source models. It represents a

factorization of constructs common to process

fragments in the source models. The factorization

detects and resolves the semantic, structural and

behavioral conflicts between them.

In the remainder of this paper, we first present

our SB2P construction approach. Secondly, we

highlight conflicts susceptible to exist among process

fragments when trying to factorize them and we

present our factorization/synthesis rules. Finally, we

place the presented work in the context of already

proposed approaches.

2 SB2P CONSTRUCTION

APPROACH

To construct a SB2P, we start from a repository of

BPM of good quality, which are classified into

different business domains. Given a business domain,

our approach proceeds according to the three

following steps:

1. Extraction of process fragments that are

semantically close and frequently present in the

analyzed process models (possibly with

different structures and/or behaviors): The

detection of these fragments relies on label

similarities (see section 3.1) using an ontology

for the analyzed business process domain.

2. Difference/conflict detection: For the extracted

process fragments, this step uses a set of

comparison rules to identify three types of

conflicts: semantic, structural and behavioral

(see section 3.2).

3. SB2P construction: Once the conflicts are

resolved among the semantically-close process

fragments, a set of factorization rules are

applied to construct the SB2P (see section 3.2).

3 CONFLICT DETECTION AND

SEMANTICALLY-CLOSE BP

FRAGMENT IDENTIFICATION

Comparing business processes requires a common

specification notation. For the purposes of this paper,

we abstract away from any specific notation and we

represent BPM as directed graphs with labeled nodes.

Each node has a type that represents the commonly

found types in all process modeling languages:

‘activity’, ‘event’ and ‘connector’. In addition, similar

to most modeling languages, our graph uses three

kinds of connectors: AND, XOR and OR.

3.1 Conflict Detection

When comparing processes, we need to distinguish

between semantic, structural and behavioral

conflicts to carry out the comparison. A semantic

conflict appears when activities use different labels

between which there is a semantic relation

(subsumption, part of…). A structural conflict

emerges when various representations describe

similar behavior. While a behavioral conflict appears

when process fragments are semantically close but

have different behavioral profiles. Table 1 presents

our classification of conflicts inspired from

(Dijkman, 2007).

Table 1: Conflicts between business process fragments.

Semantic

conflicts

Subsumed activity: An activity named a

subsumes an activity a

, if it represents the same unit of work

as the other activity, but includes another unit of work as well.

Partly corresponding activity: An activity named a

partly corresponds to an activity a

, if these

activities partly represent equivalent units of work, but both also represent different units of work.

Structural conflicts

Skipped activity: is an activity which exists in one process, but there is neither an equivalent, nor a

subsumed, nor a partly corresponding activity in the other process.

Refined activity: exists if an activity a1 exists in one process, but an equivalent unit of work is only

represented by a collection of activities in the other process. The collection of activities refines the

single activity, because it represents the same unit of work at a different level of granularity.

Additional dependencies: correspond to the case in which one set of activities includes the other. The

set that includes the other has additional dependencies.

Behavioral

conflict

Iterative vs. once-off occurrence: is the case in which an activity is part of a loop in one process while

it is not in the other process. This means that in one process the activity must be performed correctly

in one go, while in the other process it can be performed repeatedly until the result is satisfactory.

Different conditions for occurrence: In case the dependencies for two equivalent activities have

different conditions for their occurrence.

ICSOFT 2011 - 6th International Conference on Software and Data Technologies

3.2 Extraction of Similar Business

Process Fragments

To compare elements of a process model with

another one, we use a mapping function

map

inspired from (Rosa et al., 2010). With this

function, a mapping between nodes of different

types, or between a split and a join, has a

matching score of 0. The matching score of a

mapping between two activities or between two

events is measured by the similarity of their

labels. Given two activities, their semantic

similarity score is the degree of similarity, based

on equivalence between words in their labels.

Words that are identical are given a score of 1,

while words that are synonymous are given a

score of 0.75, a value that was determined

experimentally by (Dongen et al., 2008). Thus, an

exact match is preferred over a synonym match.

The semantic similarity score of two activities a

and a

is defined in (1).

12 21

(,) \ \

1* 0,75* ( , )

(, )

max( , )

sl a a a a

map

a a synonym s l

faa

∈×

∩+

∑

(1)

In equation (1) synonym is a function that returns 1

if the given words are synonyms and 0 if they are

not. This measure considers a synonym relationship

of two instances, the number of synonyms that are

proposed for one term by the ontology of the domain

and weights the number of synonyms against the

maximum sense cardinality of these two terms.

Frequently occurring words are skipped, such as “a”,

“an” and “for”.

To find similar business process fragments, we

first transform each pair of process models into a

matrix where the lines and columns correspond to

activities of the compared process models. Each

element in the comparison matrix represents the

value of the mapping function of the corresponding

activities.

To illustrate our approach, we consider the two

models in fig. 1describing the process of “obtaining

a loan”. The corresponding comparison matrix is

given in Table 2.

Given a comparison matrix, we consider a block

as a set of adjacent cells. To extract semantic

process fragments from the comparison matrix, we

first permute its lines and columns to form cell

blocks with non zero values. Then, we use the

following rules:

1. If a block consists of only one cell C

i,j

with C

i,j

=1 then activity a

in the first process model is

equivalent to activity a

in the second model.

We take this activity as it is in the pattern.

2. If a block consists of only one cell

ji,

with

[0.89,1[C

ji,

∈

then the label of a

in the first

process model is semantically very close to the

label of a

in the second one. The cut off value

0.89 is determined experimantelly by (Dongen et

al., 2008). We take one of these activities in the

pattern.

3. If a block has a 1*k or a k*1 (k≠0) dimension

and consists of cells C

i,j

with

[0.5,0.89[C

ji,

∈

, we

consider the row (or the column) activity as a

refined one. If k=1 then the label of a

in the first

process model has the same meaning as the label

of a

in the second one. We take one of these

activities in the pattern.

Figure 1: Examples of BPM from the repository.

Model 2

Model 1

SEMANTIC DESIGN PATTERNS FOR BUSINESS PROCESSES

Table 2: Comparison matrix for models 1 and 2.

Model 2

Model 1

Revise

fulfillment

of loan

request

Make

client

details

Check

credit

Check

loans

Check

changes

Pass to car

manufacturer

Make

changes

Decide

mandate

Notify

sales

Check

completeness

of loan

request

0,875

0 0

Check

existing

client

0,1875

0,583

0,33 0,33 0,33 0 0 0,25 0 0

Add client

information

0,583

0 0 0 0 0 0,25

0 0

Produce

approval

0 0 0,325 0 0 0 0 0

0 0

Check credit

0,375

1 0,875 0,5 0 0 0 0 0

Checking

module

0,1875

0,5

0,5 0,5 0 0 0,325 0 0

Pass to car

manufacturer

0 0 0 0

0 0

Make

changes

0 0 0,325 0,325

0,875

0 0

1 0 0

Check

changes

0,1625 0 0,5 0,5

0,325

0 0

Print 0 0 0 0 0 0 1 0 0 0

Plan

appointment

0 0 0 0 0

0 0 0 0

Figure 2: The resulting SB2P: Loan pattern.

4. If an activity in a model has an equivalent one

in the other and has also refined activities, then

we consider the refined one as additional

dependencies to the activity.

5. If a block consists of only one cell

ji,

with

ji,

then the label of a

in the first process

model haven’t a corresponding activity in the

second model. If a line or a column contains

only 0s, we consider the corresponding activity

as a skipped one.

We replace a skipped activity by silent one. A

silent activity in the business model is an empty

activity without added value. So, it does not have

label which describes his function in the model. It

can be replaced by the designer during modeling.

By applying construction rules 1-5 on the example

of fig. 1, we obtain the SB2P of fig. 2 which we

baptize “Loan pattern”.

4 CONCLUSIONS

The main contributions of this paper are to propose a

new reuse concept for business processes, called

Semantic Business Process Patterns (SB2P), and an

approach for its construction. The proposed

approach uses semantic relations to compare BPM in

a given domain and to determine common fragments

that are semantically close. In addition, it tolerates

structural and behavioral differences among the

process fragments as long as they are conflict-free.

Our SB2P concept resembles more the reference

modeling: they both offer process fragments. But, in

contrast to the reference model construction

approach which merges process fragments (Rosa et

al., 2010), our SB2P construction approach

factorizes fragments by taking only semantically

close elements in the resulting pattern; this

difference is justified by the genericity/abstraction

property behind an SB2P.

On the other hand, while SB2P accounts for

modeling element semantics, workflow patterns (der

Aalst et al., 2003) and workflow activity patterns

(Rosa et al., 2010) do not, they rather focus on

specific aspects like control and data flows and

resource assignments. Consequently, these patterns

are more appropriate to the development of business

Skipped Activities

Semantically close activities

Refined Activity

Additional De

endencies

Identical Activities

ICSOFT 2011 - 6th International Conference on Software and Data Technologies

process modeling tools than the design of business

processes. We are currently automating the presented

SB2P construction approach in order to evaluate its

advantages and limits. In addition, we are examining

the benefits of SB2P in the design of business

processes.

REFERENCES

Müller, D., Reichert, M., Herbst, J.: Data-driven modeling

and coordination of large process structures. LNCS,

4803:131, 2007.

Buschmann, F., Henney, K., Schmidt, D.: Past, present and

future trends in software patterns, IEEE Software, 24(7/8)

31–37, (2007).

Tran, H., Coulette, B., Thuy, D.: Broadening the use of

process patterns for modeling processes. In: Proc. SEKE,

Knowledge Systems Institute Graduate School, 57–62,

(2007).

Thom, L., Reichert, M., Iochpe, C.: On the Support of

Workflow Activity Patterns in Process Modeling Tools:

Purpose and Requirements, (2009).

Smirnov, S., Weidlich, M., Mendling, J., Weske, M.: Action

patterns in business process models. In Baresi, L., Chi,

C.H., Suzuki, J., eds.: ICSOC/ServiceWave. Volume of

5900 LNCS, 115-129, (2009).

Van der Aalst, W. M. P., Ter Hofstede, A. H. M.,

Kiepuszewski, B., Barros, A. P.: Workflow patterns.

Distrib. Parallel Databases, 14(1), (2003).

La Rosa, M., Dumas, M., Uba, R., Dijkman, R.M.: Merging

business process models. In Proc. of OTM, volume 6426

of LNCS, pages 96–113, (2010).

Li, C., Reichert, M., Wombacher, A.: Discovering reference

models by mining process variants using a heuristic

approach. In Proc. of BPM, volume 5701 of LNCS, pages

344-362, Springer, (2009).

Dijkman, R.: A Classification of Differences between Similar

Business Processes, In Proceedings of the 11th IEEE

EDOC Conference (EDOC’07), pages 37–50, (2007).

Montero, I., Pẽna, J., Ruiz-Cortés, A.: A Methodological

Framework for Obtaining the Core Architecture of

Business Information Systems Families. CAISE

conference. (2010).

van Dongen, B. F., Dijkman, R. M., Mendling, J.: Measuring

similarity between business process models. vol. 5074 of

LNCS, pp. 450–464, Springer, (2008).

SEMANTIC DESIGN PATTERNS FOR BUSINESS PROCESSES