Constructs competition miner: process control-flow discovery of BP-domain constructs

This article discusses the algorithm Constructs Competition Miner for discovering business process domain constructs. It focuses on the top-down approach and the constructs needed for determining noise and non-supportive behavior. The article also discusses the suitability of the supported BP constructs and the competitive algorithm. The article sheds light on process delivery techniques, which enhances the awareness of the personnel regarding the actual workflow. The article also discusses the difficulties encountered by business analysts in comprehending the importance of Petri nets or casual nets in completion of the business activities. The article is relevant for business process management courses in universities and colleges.

Running head: BUSINESS PROCESS ENGINEERING
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Table of contents
Introduction................................................................................................................................2
Body...........................................................................................................................................3
Process models and event logs...............................................................................................3
State of art..............................................................................................................................6
Construct Competition Miner................................................................................................9
Suitability of the supported BP Constructs..........................................................................10
Competitive algorithm.........................................................................................................10
Conclusion................................................................................................................................12
References................................................................................................................................13

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Source: Redlich, D., Molka, T., Gilani, W., Blair, G. and Rashid, A., 2014, September.
Constructs competition miner: process control-flow discovery of BP-domain constructs.
In International Conference on Business Process Management(pp. 134-150). Springer,
Cham
Introduction
The article sheds light on process delivery techniques, which enhances the awareness
of the personnel regarding the actual workflow. This is carried out through the maintenance
of log events. In most of the cases, the organizations make use of Petri nets or casual nets for
delivering the business processes. The academic scholars prefer these nets, as they assist in
enhancing the productivity (Redlich et al. 2014). On the contrary, business analysts encounter
difficulties comprehending the importance of these nets in completion of the business
activities. As a matter of specification, the focus of the article is on algorithm, which reflects
the top down approach. In this proposal, the article upholds the constructs, needed for
determining the noise and the non-supportive behaviour. Conglomeration of the constructs
helps the personnel in seeking suitable solutions for the top down behaviour approximations.
Formal descriptions of the algorithm along with the results seem beneficial in determining the
constructs and behaviour adopted for delivering the business process techniques in an
efficient and efficient and effective manner (Redlich et al. 2014).
In an ambience of competition, the companies and organizations need to be conscious
about the process delivery techniques, which they are using. This in terms of improving the
standards and quality of the business operations. Development of realistic and achievable
goals improves the focus of the personnel on executing the activities according to the
requirements. The main aim of Process Discovery Techniques is to gain an understanding
about the actual working processes from the created logs. Typical components of the log are
identification of the bottlenecks for improving the business processes. This improvement,

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further, enhances the productivity, providing the companies and organizations with an
opportunity to enjoy competitive advantage over the contemporary brands (Redlich et al.
2014).
In the actual process of executing the business activities, the personnel realize the
difference between the design time of the product specification and the time when the product
specifications re discovered. Complying with the standards of business processes like BPMN
and EPC are subjected to the domain of business operations. The results of the algorithms for
process deliver techniques are dependent on independent representations of the Petri nets,
which are discovered by the alpha algorithms. On the other hand, casual nets are discovered
by Heuristic Miners.
The article projects the difficulties of a business analyst in terms of decision making.
This is in terms of unfamiliarity with the representation of the process; mapping the process
at the design time and process discovered at the running time. This mapping is difficult, as
both the design time and process discovered are subjected to different linguistic
representations (Redlich et al. 2014). The article proposes that transformation to different
representation can prove effective in terms of solving the discrepancies related to the
representations. One of the other problems here is mining a model for conforming to the
representing the domain for the business processes. Mining a model possesses flexibility
towards making the analysts aware of process for formulating the requirements for
representing the results.
Body
Process models and event logs
The article forms an exemplar in terms of reflecting the existence of different
standards and models for the business processes. Mention can be made of Business Process

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Model and Notation (BPMN). Along with this, Yet Another Workflow Language (YAWL) is
a significant model in terms of creating the log events for the operations. The article mainly
focuses on a set of control flow elements, which supports the major workplace standards.
These elements include start and end activities (process steps); parallel gateways (XOR split
or join) among others. According to the formal definition, business process model is the
combination of a set of activities, finite set of splits, finite set of joins, finite set of start and
end event and connecting the path of operations (Redlich et al. 2014).
C = {(c1, c2) ∈ F × F | c1 6= c2 ∧ c1 ∈/ Ee ∧ c2 ∈/ Es},
– ∀a ∈ A ∪ J ∪ Es : |{(a, b) ∈ C | b ∈ F}| = 1,
– ∀a ∈ A ∪ S ∪ Ee : |{(b, a) ∈ C | b ∈ F}| = 1,
– ∀a ∈ J : |{(b, a) ∈ C | b ∈ F}| ≥ 2,
– ∀a ∈ S : |{(a, b) ∈ C | b ∈ F}| ≥ 2, and
– all elements e ∈ F in the graph (F, C) are on a path from a start event a ∈ Es
to an end event b ∈ Ee.
Figure 1: Formula of business process model
(Source: Redlich et al. 2014)

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The above diagram is the summarization of the formula stated for business process
model. The integrated structure is represented from the hierarchical representation of the
structures, joining the entry and the exit points. Within this structure, the business process
constructs occupy an important position. These constructs- Choice, Parallel among others are
non-sequential and possess similarity with the process tree, which is defined according to the
performance of the Petri nets or workflow nets. Information systems helps in maintaining the
event logs and the transactions for each event. This article specifically deals with the features
needed for discovery of the control flow (Redlich et al. 2014). Every event needs to have the
reference to the identifier, who provides instance to the processes. Along with this, reference
is also needed to the corresponding activities. This reference and correspondence provides the
processes with an unique name.
The processes in a single events are captured in a trace, which are represented by pairs
(t and a). Here, t stands for trace and a stands for the activity). As two traces are considered to
independent of each other, the interesting point here is the order of the activities within the
trace. Based on the above aspects, one of the other definition of a business process model can
be as follows:

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Figure: Second formula for business process model
(Source: Redlich et al. 2014)
Traces consisting only of activity orders are known as simple traces. The logs, which
consist of simple traces are called simple event logs. One of the examples of the simple event
logs for the business process can be as follows:
Figure: Example of simple event log
(Source: Redlich et al. 2014)
State of art
Process discovery relates with the act of extracting the business model from he
created logs without the consideration of a-priori information. Process discovery is the main
term, which includes unleashing all the angles from which the business operations can be
executed. However, the article focuses on discovery of control flow perspective. BPMN and
EPC helps the personnel in creating the design-time models. Here the focus is on
interoperability, which improves the public relations with the stakeholders. Here, the
propositions of Van der Aalst can be linked. This is because mapping the process helps in

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preparing the reports. Sending the reports on the workflow process and models to the
stakeholders enhances their awareness about the business dynamics (Aalst 2016).
Extraction of process model through the process discovery techniques aligns with the
time management, which is needed in terms of completing the processes. Evaluation of the
proposed plans and processes well in advance helps the personnel in maintaining the
sequence between the project related activities. According to the arguments of Batoulis et al.
(2015), extracting the business models through the techniques of BPMN helps the personnel
in undertaking logical decisions for executing the project related activities. This is in terms of
devoting quality time to the consideration of the prospective sources through which the
revenue and the profit can be enhanced. As a matter of specification, evaluation of the
process delivery techniques helps the personnel in deciding which methods would be
effective for enhancing the efficiency within the business activities.
Actual run-time is important for extracting the business processes through the
discovery techniques. The personnel lack the understanding about the standards of the
business model prior to the extraction. As a result of this, they conform to the use of the Petri
nets and casual nets for extracting the business process models. This relates with the logical
decision-making, which enhances the personality of the personnel in terms of the enhancing
the productivity (Leemans, Fahland and Aalst 2015). The research journals consist of the
evidences related to the existence of algorithms for discovering the efficient techniques
related to the delivering the processes. These researches also project the strengths and
weakness of the algorithms, enabling the personnel in undertaking logical decisions towards
delivering the processes in an efficient and effective manner.
Footprint of the logs forms the base for construction of the business processes. The
authors of the researches agree to the representation of the footprint through direct neighbour

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matrix, which consists of the information about the interconnectedness between the activities.
Some of the algorithms deal with the process of discovering blocked structured processes,
which have certain specific characteristics. Most of the genetic process delivery restricts the
space for exploring the unknown domains of the process delivery techniques (Redlich et al.
2014). In absence of space, time becomes a constraint, even if plans have been constructed
well in advance. This results in the creation of research trees, which can be considered
beneficial in terms of projecting the conceptual framework for the process delivery
techniques.
One of the weakness of the algorithms is that they prove ineffective in terms of
determining the outcomes of the process delivery techniques. Along with this, these does not
guarantee suitable run times for the personnel in terms of seeking effective business models.
One of the other approaches in this context is the Inductive Miner, where top down approach
is followed for untangling the blocked structures of Petri nets. Usage of the original algorithm
assists the personnel in evaluating the constraints within the relationships and the constructs.
One of the striking facts about Inductive Miner (IM) is that it acquires extension due to its
deals with noise (Redlich et al. 2014). One of the other options is creation of the lock
structured processes from the logs. This results in the discovery of arbitrary Petri nets, which
have undergone transformations.
There are different approaches to dealing with the business process models, which
consists of noise and logs, not conforming to the target process language. These are:
 Simple techniques for filtering the logs for removing the non-frequent traces. These
techniques prove beneficial in terms of upgrading the understanding related to the
Petri nets. As these techniques not always apply to the readable language, therefore,

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they are usually avoided, as they prove ineffective in determining the behaviours,
which lack expression.
 Fuzzy miners create confusion among the personnel in terms of determining the
behaviours needed for discovering the efficient process delivery techniques.
 Working on a similar principle is assistance in terms of promoting the shared values
and mutual understanding towards conducting the projects (Batoulis et al. 2015).
Correlation and the significant process models simplifies the model, which supports the
main behaviour needed for discovering the process delivery techniques. Mention can be
made of the Heuristics Miner, where project mapping is done for the causal net. This net is
them transformed for providing the clients and the customers an enhanced understanding of
the representations regarding the process delivery techniques. Relation between the activities
is not the base for footprints used in the Heuristic Miner (HM) (Redlich et al. 2014).
However, relative relation values are important in terms of excavating the correlation
between the activities of process delivering. Indulging in alliances helps in simplifying the
process of extracting the business model for extracting the process delivery techniques.
Construct Competition Miner
Through the use of Construct Competition Miner, the personnel get the motivation for
developing different discovery algorithms. These algorithmic representations is a support for
the BP constructs in terms of establishing the relationship between each other. This is derived
from the challenging conventions regarding the noisy logs, which often encounter conflicting
behaviours. One of the typical components of Construct Competitive Miner is the Footprint,
which is multiplied during the actual process of discovering the delivery techniques (Redlich
et al. 2014). At the initial stage, the footprint of the activities is essential in terms of carrying
out the activities according to the identified and the specified requirements. The nature of

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operation in the algorithm is divide and conquer, which gives rise to new subsets. For
example:
for A = {a, b, c, d, e} : (a, b, c, d, e) → ((a, b, c),(d, e)) → (((a),(b, c)),((d),(e))) → (((a),((b),
(c))),((d),(e)))4 nine different footprints for sets {a, b, c, d, e}, {a, b, c}, {d, e}, {b, c}, {a},
{b}, {c}, {d}, {e} need to be created.
Focusing on the global relations between the activities, acts as an expansion for the
project delivery techniques. The following can be one of the examples of business process
with two nested parallel constructs:
Figure 1: Example business process with parallel nested constructs
(Source: Redlich et al. 2014)
Suitability of the supported BP Constructs
Consideration of the footprints between the activity sets {a,b,c,d and e} and {f,g and
h} reflect the sequential representation of the choice constructs. This is because all the value
set are null in the matrix. The personnel possess the liberty to make additions in the matrix
sets. The workings of CM bears resemblance to the processes identified in the Decision and
Sequence Constructs. Constraints for the constructs requires the appear before values for
bringing the value of the process delivering techniques to 0. In order to deal with the noises in
an efficient and effective manner, CCM considers the following definition:

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Fig: Definition of CCM for dealing with the noise
(Source: Redlich et al. 2014)
Competitive algorithm
Though the consideration of competitive algorithm, the personnel intend to fulfil the
goal of excavate the best combination of sequence, loop and Choice. One of the effective
solutions is creation and compilation of the splits within the process delivering techniques.
Projection of the splits helps the personnel in undertaking logical decisions for delivering the
processes through efficient and effective techniques. Apart from this, projecting the possible
splits is assistance in terms of establishing comparative study, which proves effective in
extracting the best possible business models. In a competitive algorithm, the competition is
denoted by “Ch”. For this, the log would be Am = A = {a, b, c, d, e, f, g, h}. The algorithmic
function would therefore be a follows:

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Figure: Competitive algorithm: Traversing to the best split-up
(Source: Redlich et al. 2014)
Additional BP constructs can enter into this chain through three simple modifications
in the algorithms:
 The tuple in the priority technique needs to possess the construct types: Choice,
Loopover Sequence among others
 Adding an empty tuple per construct to the priority queue before its entry into the
loop.
 The penalty calculation needs to be carried out in the relationship matrix, which
possesses relation to the specified construct type (Redlich et al. 2014).
Conclusion
The article emerges successful in projecting the essential techniques needed for
delivering the business processes. Consideration of time and space are essential in term of

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projecting the possible splits, which may arise in the processes. Modification in the
algorithms is assistance for the personnel in terms of extracting the appropriate business
models for enhancing the productivity.

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References
Batoulis, K., Meyer, A., Bazhenova, E., Decker, G. and Weske, M., 2015, June. Extracting
decision logic from process models. In International conference on advanced information
systems engineering (pp. 349-366). Springer, Cham.
Leemans, S.J., Fahland, D. and van der Aalst, W.M., 2015, August. Using life cycle
information in process discovery. In International Conference on Business Process
Management(pp. 204-217). Springer, Cham.
Redlich, D., Molka, T., Gilani, W., Blair, G. and Rashid, A., 2014, September. Constructs
competition miner: process control-flow discovery of BP-domain constructs. In International
Conference on Business Process Management(pp. 134-150). Springer, Cham.
Van der Aalst, W., 2016. Process discovery: An introduction. In Process Mining (pp. 163-
194). Springer, Berlin, Heidelberg.