=Paper=
{{Paper
|id=None
|storemode=property
|title=LiProMo-Literate Process Modeling
|pdfUrl=https://ceur-ws.org/Vol-855/paper20.pdf
|volume=Vol-855
|dblpUrl=https://dblp.org/rec/conf/caise/PinggeraPZW12
}}
==LiProMo-Literate Process Modeling==
https://ceur-ws.org/Vol-855/paper20.pdf
LiProMo—Literate Process Modeling
Jakob Pinggera, Thomas Porcham, Stefan Zugal, and Barbara Weber
University of Innsbruck, Austria
{jakob.pinggera, thomas.porcham, stefan.zugal, barbara.weber}@uibk.ac.at
Abstract. Recently, research on quality issues of business process mod-
els has begun to investigate the process of process modeling, i.e., the
process of creating process models. In particular, it has been recognized
that during this process, well-functioning communication between do-
main experts and system analysts is essential for understandable process
models. This paper proposes the LiProMo approach to foster commu-
nication among system analysts and domain experts by flexibly inter-
linking textual descriptions and formal process models. The feasibility
of LiProMo is shown by a prototypical implementation as well as a vi-
sionary scenario that illustrates the usage and benefits of LiProMo. The
adoption of Cheetah Experimental Platform as basis for the prototye will
support empirical evaluation of LiProMo, as planned for future work.
Key words: business process modeling, process of process modeling,
literate process modeling
1 Introduction
Business process models play an important role for managing business pro-
cesses [1]. Business process models, or process models for short, are for example
used to support the analysis and design of process-aware information systems,
service-oriented architectures, and web services. In addition, they help to obtain
a common understanding of core processes of a business [2] and enable us to
identify problems and to discover opportunities for improvement [3].
The process of creating process models, denoted as process of process model-
ing [4], can be characterized as an iterative and collaborative process which typ-
ically involves several stakeholders like domain experts and system analysts [5].
It has been recognized that this process of process modeling influences the qual-
ity of the resulting process model [4–6]. During this process, information about
the domain to be modeled is transferred from the domain experts, who have
the knowledge about the domain, but usually lack formal modeling skills, to the
system analysts, who select appropriate modeling constructs and formalize this
information. This communication, however, is often hampered by the fact that
different vocabularies are used, leading to misunderstandings and faulty process
models. Similarly, without information from a domain expert, a system analyst
may find it difficult to infer the business rules behind modeling constructs [7],
bearing a potential source of error. Given the fact that a considerable percent-
age of lifecycle costs are related to maintenance [8], there is strong demand for
better understandable process models reducing the time needed for conducting
changes and decreasing the risk of introducing errors.
In this paper, we introduce a technique called Literate Process Modeling
(LiProMo), which aims to improve communication during the process of process
modeling as well as the maintainability of resulting process models. To this end,
LiProMo interweaves the textual descriptions of business processes and their
formal business process models. In this way, arbitrary formal process models
can be annotated with text fragments, presumably providing a discussion basis
for domain experts and system analysts. To put the concepts of LiProMo into
practice, we developed a prototypical implementation of an editor for LiProMo.
Future validation of the LiProMo approach will be based on this editor.
The paper is structured as follows. Section 2 introduces LiProMo. Section 3
presents the LiProMo prototype. Section 4 describes how we envision the usage of
LiProMo. The paper is concluded with related work in Section 5 and a summary
and future work in Section 6.
2 Literate Process Modeling
LiProMo is based on the idea of combining graphical process models and infor-
mal textual descriptions (cf. Fig. 1A). This combination is motivated by dual
channel theory [9], which states that pictorial and textual representations are
processed differently by the human mind. Pictorial information is processed in
parallel by the visual system whereas textual representations are processed se-
rially by the auditory system [10]. This fact is exploited by dual coding theory,
suggesting that conveying information is more efficient when images and text are
combined [11]. [12] goes even further by claiming that “textual encoding is most
effective when used in a supportive role: to supplement rather than to substitute
for graphics”. This is underpinned by the findings presented in [13] stating that
the understanding of a business problem is significantly increased when reading
a BPMN model and the corresponding written use case description.
State of the art process modeling environments like Signavio1 or IBM Web-
sphere2 provide means for adding textual descriptions to activities and including
comments either directly in the process model or on separate pages. Similarly,
wiki-based process modeling systems allow users to link parts of the process
model to wiki pages (for an overview see [14]). The major disadvantage of this
approach is that by incorporating comments directly into the process model “vi-
sual clutter” is added, which might “confound their interpretation by making it
more likely they will be interpreted as constructs” [12]. On the contrary, attach-
ing comments to activities or adding them on separate pages makes them more
difficult to access and therefore prone to split-attention effect [15], hampering
the understanding of process models [16].
LiProMo follows the idea of Literate Programming [17], which was designed
to foster program comprehension. It was later introduced in UML modeling,
combining textual descriptions and UML models to create more comprehensive
documentations [7]. We adopt this idea for business process modeling to sup-
port domain experts and system analysts when collaboratively creating process
1
www.signavio.com
2
www.ibm.com/software/websphere
A)
Literate Process Model
Process Model Dialogue Document
Quality Assurance
Deliver
First the quality of the product
to be delivered is evaluated.
Evaluate X X After evaluating the quality, the
product is either delivered to
the customer or send back for
Revise another revision of the product.
Generate Process Generate Process
Documentation Executable
B) C)
Process Documentation Deliver
Quality Assurance Evaluate X X
First the quality of the product to be Revise
delivered is evaluated.
Evaluate
After evaluating the quality, the product is
either delivered to the customer or send Workflow Engine
back for another revision of the product.
Deliver
X X
Revise
Fig. 1. Literate Process Modeling
models and to improve process model maintainability. Fig. 1 sketches the basic
idea of LiProMo. The process modeling editor depicted in Fig. 1A consists of
two separate areas holding the process model and the corresponding textual de-
scription. To avoid split attention effect, the LiProMo approach juxtaposes the
complete textual description and the graphical process model and links model
elements with the corresponding task descriptions. The explicit links between
process model and textual description can also be exploited for generating pro-
cess documentations by interweaving the process model and the corresponding
parts of the informal specification in a single document (cf. Fig. 1B). When re-
visiting the process model for conducting changes, the process documentation
provides valuable knowledge about modeling choices made in the past, since not
only the information contained in elements of the formal process model, but also
additional information is readily available and linked to the corresponding model
elements, e.g., explanatory examples. The additional information provided by the
documentation reduces the risk of introducing errors. Efforts needed for creating
additional documentation are expected to be regained as less time is spent on
fixing errors [17]. LiProMo models can also serve as executable specifications,
i.e., the process model can be fed into a workflow engine providing execution
support for process models (cf. Fig. 1C).
3 Literate Process Modeling Editor
We developed a prototypical editor for LiProMo to assess its feasibility. As illus-
trated in Fig. 2, in a LiProMo model, the textual description of the whole process
model and the actual process model are juxtaposed. During the creation of the
process model, system analysts and domain experts work together in creating
a process description tightly interconnected with the graphical process model
(for details on how we envision such a scenario, see Section 4). The LiProMo
editor allows for explicitly linking model elements, i.e., single activities or edges,
but also whole process fragments that should be documented, to arbitrary pas-
sages in the textual description. No restrictions are imposed on either the size
and shape of the process fragments or the linked text fragments. The editor au-
tomatically highlights the associated textual descriptions for selected modeling
elements and vice versa, e.g., in Fig. 2 the edge labeled “special conditions re-
quired” is selected, resulting in the highlighted passage of the textual description
on the right. The text gives examples for special conditions that would result in
taking this execution path.
Fig. 2. Literate Process Modeling Editor
Another benefit of making associations between modeling elements and tex-
tual descriptions explicit is the possibility of generating structured documen-
tation. For every association, the textual description and the process fragment
are displayed next to each other, resulting in a step-by-step explanation of the
process model. The textual information documents the modeling elements and
gives additional information that cannot be derived from activity names or edge
descriptions.
In order to be able to evaluate the potential benefits of the LiProMo ap-
proach, we built the editor on top of Cheetah Experimental Platform [18]. By
logging all interactions, i.e., changes to textual descriptions and graphical process
models with the modeling environment to a central database, we are able per-
form a step-by-step replay of the process underlying the creation of the LiProMo
model at any point in time, enabling us to perform analysis similar to [4].
4 Our Vision: Literate Process Modeling in Use
This section describes how we envision the interactions among system analysts,
domain experts and the LiProMo editor. For this purpose, we provide a short
example describing the collaborative creation of a LiProMo model. In particular,
assume that a domain expert and a business analyst document the process of
consumer loan applications in a banking institution.
Initially, the domain expert indicates that “the process always starts with
a check of the loan application. In case any required information is missing,
the employee contacts the customer right away to acquire the missing informa-
tion”. So the system analyst enters the textual description and starts to create
the graphical process model. To this end, the business analyst creates the first
activity “review loan application” by selecting the relevant piece of textual infor-
mation and choosing the activity name. Based on this information, the LiProMo
editor creates the activity and links it to the relevant piece of text. This way, the
activity name can be kept short, still providing additional information for future
users, e.g., “in case any required information is missing, the employee contacts
the customer right away to acquire the missing information”. The domain experts
sees the changes in the process models and the highlighted textual description
and explains that “depending on the outcome of the review, one of the following
tasks is executed. In case the financial status does not allow for an additional
loan, the application is rejected and the customer is notified”. The system ana-
lyst updates the textual description and decides to model the described scenario
using the exclusive choice pattern. Hence, the business analyst creates an XOR
split and an activity for rejecting the application and informing the customer,
which is linked to the respective passage in the textual description. The domain
expert adds “in most cases we reject loans because customers do not fulfill the
required financial security guarantees”. The system analysts adds an additional
comment to the reject activity and the edge connecting the XOR split and the
activity including the examples given by the domain expert. The domain expert
continues his explanations and states that “in case a new loan is granted the cus-
tomer will be notified and the funds will be disbursed. In some situations it may
be necessary to agree on special terms for a new loan”. As before, the business
analyst first updates the textual information and adds an activity for agreeing
on special conditions. The business analysts asks for examples of these special
conditions. The domain experts answers “there might be several reasons, but the
most common are that the applicant is underage or that the customer fails to
fulfill the required guarantees but has a guarantor for the loan”. The business
analysts links given examples to the edge between the XOR split and the special
terms activity, only adding the phrase “special conditions required” to the edge
instead of the lengthy examples given by the domain expert. Then the business
analyst completes the process model by creating an XOR join and the end event
(cf. Fig. 2). The business analyst and the domain expert go through the process
model step by step. Since the domain expert is not familiar with BPMN, the sys-
tem analyst selects the modeling elements they are currently talking about. The
LiProMo editor highlights the corresponding textual descriptions, helping the
domain expert in understanding the process model and enabling him to identify
potential errors.
5 Related Work
We relate our work to four streams of research: research on understandability
and maintainability of process models, the process of process modeling, the auto-
matic generation of process models from natural language and research targeting
communication between domain experts and system analysts.
Understandability and Maintainability of Process Models. The impact on model
understanding and model maintenance has already been examined from various
angles. For instance, [19] looks into the effect of modeling expertise, [20] discusses
the influence of domain information, [16] investigates hierarchy, whereas [21] de-
scribes the impact of activity names. Similarly, [12, 22] discuss the relation be-
tween cognitive aspects and the understanding of process models. Like LiProMo,
all these works deal with understandability and maintainability of process mod-
els, however, LiProMo rather focuses on the process of process modeling than on
the outcome of process modeling, i.e., the resulting process model.
The Process of Process Modeling. The LiProMo approach focuses on improving
the process of process modeling. Similarly, [23, 24] discuss the interaction of
system analysts and domain experts. However, these works focus rather on the
negotiation than on the creation of the process model, as done in LiProMo. The
process of process modeling was investigated in [6, 18]. In contrast to LiProMo,
they embrace a descriptive point of view on the process of process modeling,
rather than trying to improve it.
Process Model Generation from Natural Language. There has been considerable
research in the area of automatically deriving process models from natural lan-
guage. [25] proposes a technique to automatically create BPMN models from
natural language. [26] describes the creation of BPMN models based on group
stories. Even though the automated generation of process models seems promis-
ing it is not clear—as argued in [27]—in how far these process models are well
understandable. Moreover, several approaches impose restrictions on textual de-
scriptions to provide sufficient structure to be able to derive a process model.
Hence, we do not aim to automatically create process models from natural lan-
guage, but rather support modelers in creating well documented process models
in an iterative process involving domain experts and system analysts.
Improving Communication between Domain Expert and System Analyst. As mo-
tivated in this work, communication between domain experts and system ana-
lysts is often impaired by a different set of skills and vocabulary. For declarative
process models, this problem has been tackled by the Test Driven Modeling
(TDM) methodology [28, 29]. TDM combines test cases and process model to
provide a common vocabulary for domain experts and system analysts. Besides
improving communication such a combination improves the maintainability of
declarative process models, as shown in [30]. In contrast, LiProMo focuses on
supporting the creation and maintainability of imperative process models. In the
upcoming evaluation we will strive for similar effects when utilizing LiProMo.
6 Summary and Outlook
In this paper we presented LiProMo—a technique that tightly interweaves graph-
ical process models with their textual description. Presumably, the advantage
of such an integration is threefold. First, according to dual coding theory, it
allows for more efficient processing of information, hence directly supporting
system analysts in creating the process models. Second, the tight integration of
the textual description provides a common vocabulary, hence improving com-
munication between domain experts and system analysts. Third, during model
evolution, the interweaved availability of visual process model and textual de-
scription presumably lowers the chance of misinterpretation, hence improving
process model maintenance.
So far, however, these conjectures are based on theoretical considerations
only. To corroborate them, we are currently planning an empirical evaluation,
in which the prototypical LiProMo editor will be used in real-world modeling
sessions. Therein, we will specifically investigate the communication patterns
between domain experts and system analyst, allowing us to taylor the editor
towards specific usage scenarios. Additionally, we will conduct controlled ex-
periments to assess the impact of LiProMo on the maintainability of process
models.
Acknowledgements. Gefördert aus Mitteln des vom Land Tirol eingerichteten Wis-
senschaftsfonds.
This research was funded by the Austrian Science Fund (FWF): P23699-N23.
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