CN110781616A

CN110781616A - Behavior equivalence process tree generation method based on complete finite prefix expansion

Info

Publication number: CN110781616A
Application number: CN201911016696.6A
Authority: CN
Inventors: 朱锐; 黄月; 李彤; 唐明靖; 马自飞; 郑明�; 汤雅惠
Original assignee: Yunnan University YNU
Current assignee: Yunnan University YNU
Priority date: 2019-10-24
Filing date: 2019-10-24
Publication date: 2020-02-11
Anticipated expiration: 2039-10-24
Also published as: CN110781616B

Abstract

The invention discloses a behavior equivalence process tree generation method based on complete finite prefix expansion. The method comprises the following steps: expanding the process model into a branch process containing a truncation event by using a full prefix expansion method; extracting an activity relation group meeting the reconfigurable condition from the branch process; and according to a preset conflict judgment condition, when the extracted activity relation groups are judged to have no conflict, reconstructing the extracted activity relation groups according to a preset rule to obtain the corresponding process tree. The invention can convert the non-BSPM type process model into the process tree with equivalent behavior, and has high conversion efficiency, high accuracy and simple conversion result structure.

Description

Behavior equivalence process tree generation method based on complete finite prefix expansion

Technical Field

The invention relates to the field of process models, in particular to a process model algorithm for converting a process model described by a Petri net into a process model described by a process tree.

Background

The process model is a special data with both graphic representation and behavior semantics. At present, the Petri net is the most commonly used modeling language when a process model is described, but the Petri net is used for representing the process model, and deadlock, livelock and other exceptions in the model are difficult to avoid. Secondly, when analyzing the behavior structure of the process model described by the Petri net, observing the behavior relation among a group of activities in the Petri net is relatively easy, but observing the behavior structure of the whole Petri net becomes very difficult, and particularly when the Petri net is very complex, a 'pasta-like' process model is formed.

Using the process tree to represent the process model not only avoids these unreasonable constructions, but also integrates the behavior of the process model, simplifying the complexity of the model. The process tree is used as a representation of a tree structure, a process model is described by using the process tree, and the process tree has the advantages of being clear and simple in structure, unified in structure and behavior, capable of determining behavior semantics among activities and capable of meeting basic properties of a Petri net. The use of the process tree to represent the structural information of a Petri net has many advantages, and a BSPM can perform behavior equivalent transformation with the process tree, that is, the process tree can be generated by directly analyzing the structure.

The process tree is a tree structure diagram containing process model information, leaf nodes in the process tree represent activities, branch nodes represent activity relationships, and the relationship between any two activities (leaf nodes) in the process tree is the nearest common parent node. Although the process tree structure is clear and the process model is easy to express, for the process model expressed based on the Petri net, the process model of the following two cases can not be converted into the process tree on the premise of behavior equivalence:

(1) there are a variety of relationships between a certain set of activities;

(2) relationships between a certain set of activities do not belong to a basic relationship.

We classify the process models according to whether they can be equivalently converted into process trees (fig. 1 shows a process model classification diagram which can be equivalently converted into process trees). The slash part is the process model equivalent to the process tree behavior, and refers to the process model without the above two special cases. Currently, the research on the Process tree is mainly based on the Process Model of Block structure (BSPM, see Wilvan der Alst et al for specific references in the literature "methods for Improving the responsiveness of the Process Mining", J.Buijs et al in the literature "agricultural algorithm for Improving the Process Mining", and Zhurui et al in the literature "Mining method for mixed Process supporting complex structure") to discuss the transformation problem of both. However, in a number of studies we have found that some non-BSPMs can be equivalently transformed into process trees, and we therefore classify the process model as fig. 1. FIG. 2 is an example of converting BSPM into a process tree, and FIG. 3 is an example of converting non-BSPM into a process tree.

For the problem of how to convert a Process model described by a Petri Net into a Process model described by a Process Tree, the existing Conversion Algorithm (refer to the literature "Conversion and Conversion Algorithm of Well-Structured Workflow Net to Process Tree") can convert a BSPM into a Process Tree by identifying the basic relationship (occurrence weight relationship) between activities, and the literatures "hybrid Process mining method of Complex Structure", "Conversion and Conversion Algorithm of Well-Structured Workflow Net to Process Tree" and "converting block-Structured Process model from event sources — available Process" propose that the expressive power of a Process Tree can be increased by supplementing basic blocks. However, the above document only discusses the method of converting the BSPM type into the process tree, and in fact, not only the BSPM can be equivalently converted into the process tree, but also some non-BSPM can be equivalently converted into the process tree. For example, process model P1 shown in fig. 3, compared to process model P0 in fig. 2, which includes libraries c7 and c8 in structure, process model P1 is obviously a non-BSPM. However, from the perspective of the Petri net "trace", it can be seen that P1 is trace equivalent to P0. The process model P1 can thus likewise be expressed in a process tree. However, the problem of how to convert the non-BSPM model equivalent to the process tree into the process tree is not solved at present.

Disclosure of Invention

The invention aims to: aiming at the existing problems, the method provides a behavior equivalence process tree generation algorithm which converts a process model equivalent to the process tree behavior into a process tree and is based on complete finite prefix expansion. The problem that non-BSPM equivalent to the process tree can not be converted into the process tree in the prior art is solved.

First, the definition and explanation about technical terms involved in the present invention are as follows:

1. a process model: a quadruple p ═ (C, a; F, M0) as a Petri net, where C is the condition set,

referred to as a condition; a is the active set and the active set is,

referred to as an activity, the occurrence of a is referred to as a being performed or a firing; f is the flow relationship over the Petri net, for the initial regime of p, a d ∈ M0 is called Token.

2. Process tree, for a process model p ═ C, A ═ F, M0, A is the active set, the activity a ∈ A ∪ { τ } is a process tree, the activities M1, M2, … Mn (n >0) are n process trees, the relationship symbols between the process trees are ◎, the relationships ◎ (M1, M2, … Mn) are the process trees, the sequence is defined (→), the sequence is selected (×), and (| |), the iteration (. + -) is carried out for four kinds of relationship symbols, one of the relationship symbols is represented by the symbol ◎, the relationship symbol set is ◎ { →, ×, |, |, +), and }.

3. A presence net: a triplet o ═ (S, T; F') is used as a net of occurrences, in which:

(1) (S, T; F') is a loop-free network, S ∪ T ≠ Φ; S is a finite set of libraries (i.e., conditions),

referred to as a library; t is a finite set of transitions (i.e. events), referred to as a transition; f is the edge set of the presence net, and

(2) the requirement that |. s |, is less than or equal to 1, namely the input of any library is less than or equal to 1;

(3)

x # x, i.e. no self-conflict applies to any element;

(4) satisfy the requirement of

Is limited.

In the presence net, x # y indicates that there is a conflict relationship between x and y, i.e., there is some common repository c in the presence net, and the path from c to x is disjoint from the path from c to y. x < y indicates that there is a causal relationship between x and y, i.e. there is a path from x to y in the presence net. x co y representing there is a co relationship between x and y x, y satisfying x < y < x # y.

4. And (3) branching process: for a process model p ═ (C, a; F, M0), the branching process is a tuple Π ═ (o, h), where o ═ is a net of occurrence and h is a slave (S, T; F')

A mapping to (C, A; F), wherein:

(1)

(2) min (o) is bijective with M0, Min (o) represents the minimum set of elements in the net o according to the proper partial ordering relationship;

(3)

and t1, t2 satisfies t1 ═ t2 ^ h (t1) ═ h (t2), then t1 ═ t 2.

5. Possible extended set of branching processes: the tuple Π ═ (o, h) is a branching process of the process model p ═ (C, a; F, M0), where o ═ is an occurrence net and h is a map. The possible expansion set of the branch process Π is a set of (t, B) pairs, denoted as PE (Π), where B is a co-set of relationship set (co-set) of condition set P in Π, and t is a transition of process model P, where:

(1) h (B) ═ t, B maps to a precursor set in process model p that is t;

(2) p (e) ═ t and · e ═ B, then B does not contain e.

6. Configuration: a configuration C of one presence net o ═ (P, T; G) is a set of transitions, where:

(1)

t' belongs to C, namely the configuration C is a closure consisting of proper partial order;

(2)

i i.e. any elements in the configuration C are non-conflicting.

For one presence net o ═ P, T; G,

the local configuration of transition t is also a set of conflict-free transition sets comprising t itself and consisting of appropriate partial order, denoted as [ t ]]Satisfy t e [ t ∈]And t1 e [ t ∈]T1 satisfies [ t1]]<·[t]Λ any t2 ∈ C having t2# t 1.

7. Proper partial order relationship: the proper partial order relationship on one presence net o ═ (P, T; G) is the relationship between the local configurations, denoted by <.

(1))<Is to

Is improved by

Is provided with

Then [ t]<·[t']；

(2)<Obtain reservations by finite expansion, i.e.

Has a [ t ]]<·[t']And Mark (t) ═ Mark (t '), then for [ t ═ Mark (t') ]]Finite expansion of [ t ]]⊕ E, there is an isomorphic transformation I, such that [ t]⊕E<·[t']⊕I(E)。

8. Cut-set is a finite set C of occurrence net o ═ (P, T; G), whose cut-set cut (C), is a set of conditions that contain co relations only, cut (C) being defined as cut (C) ═ (min (n) ∪ C · C \.

A set of positions C, h (cut (C)) of finite configuration of the presence net o ═ (P, T; G) is an reachable flag, indicating events reachable by the condition set cut (C), and h (cut (C)) is indicated by mark (C).

9. A truncation event: the tuple Π ═ (o, h) is a branching process of the process model p ═ (C, a; F, M0), where o ═ is an occurrence net and h is a map. If Π includes an event e 'such that another event e is a truncation event, denoted corr (e) ═ e', satisfies:

(1) mark ([ e ]) which is the equivalence of the situation reached by e and e';

(2) [ e '] < [ e ], local configuration [ e' ] and local configuration [ e ] are in a proper partial order relationship.

The emotional Cut ([ e ] e) reached by e]) Called truncation condition p, for which the following elements are truncated, i.e. arbitrary truncation condition

10. Anterior and posterior sets: a quadruple of p ═ C, a; F, M ₀) As a Petri net, let x be the same as C ∪ A

Then call ^·x is a preceding or input set of x, x ^·Referred to as the postset or output set of x.

For the analysis of the static process model, the traditional method mainly uses the method of the reachable tree or the reachable graph, and the main problem of the method is the explosion of the state space. To address this problem, Escapza discloses a method of full prefix expansion in An Improvement of McMillan's underfolding Algorithm [ J ]. Lncs, 1996. Through the full prefix expansion of the process model, the process model can be expanded into a branch process pi ═ o, h containing the truncation event, wherein o ═ S (T; F') is an occurrence net, h is a mapping function, for example, for a process model p ═ C, a; F, M0, the corresponding branch process is continuously expanded by using the possible expansion set of the branch process until the process model is expanded to the truncation condition, and finally, a branch process containing the truncation event is obtained.

The technical scheme adopted by the invention is as follows:

a behavior equivalence process tree generation method based on complete finite prefix expansion comprises the following steps:

A. expanding the process model into a branch process containing a truncation event by using a full prefix expansion method;

B. extracting an activity relation group meeting a reconfigurable condition from the branch process;

C. according to a preset conflict judgment condition, when the extracted activity relation groups are judged to have no conflict, executing step D;

D. selecting a group of activity relation groups with the highest priority from the extracted activity relation groups for reconstruction according to a preset priority judgment rule;

and repeating the steps A-D until all the activity relation groups are reconstructed to obtain the corresponding process tree.

The steps A-D are executed once, only one group of activity relation groups are reconstructed, and some activity relations can be found after other activity relation groups are reconstructed, so that the steps A-D need to be executed again after each group of activity relation groups is reconstructed. And after each reconstruction, judging whether the activity number of the process model is greater than 1, if so, jumping to A, and if the activity number is equal to 1, finishing surface reconstruction, wherein the result obtained by reconstruction is the process tree.

By the above method, the non-BSPM model equivalent to the process tree can be converted into an equivalent process tree.

Further, in the step B, the method for determining whether the activity relationship group satisfies the reconfigurable relationship includes:

b1: extracting a transition set from the branch process; the set of transitions is the set of events in the process model.

B2: and respectively distinguishing the relationship of each transition group in the transition set according to the definition of a preset reconfigurable relationship, and if the distinction is passed, judging that the activity relationship group corresponding to the transition group meets the reconfigurable relationship.

Further, the reconfigurable relations include a reconfigurable sequential relation, a reconfigurable iterative relation, a reconfigurable selection relation and a reconfigurable concurrent relation.

Further, the determination condition of the reconfigurable sequential relationship is as follows:

for the process model p, (C, a; F, M0), pi (o, h) is a branch process containing a truncation event corresponding to the process model p, where o (S, T; F') is an occurrence net, h is a mapping function from the transition set to the active set, C is the condition set, a is the active set,

referred to as an activity, M0 is the initial state of p, S is the pool set, T is the set of transitions,

referred to as a transition, is referred to as a transition,

for any one

Its activity mapped into the process model is a1, a2, respectively; when t1 and t2 satisfy the following conditions, activities a1 and a2 have reconfigurable sequential relationship:

1. the configuration of t1 differs from that of t2 only by t 2: [ t1] - [ t2] - { t2 }; .

2. Configuration [ t1]The set of activities mapped into the process model does not contain the activities mapped into the process model by event t 2:

3. if T2 'e T exists, satisfying T2' ≠ T2 ^ h (T2') ═ h (T2), then for all T1' satisfying [ T1'] ∪ { T2' } [ T2'] there must be h (T1') ═ h (T1);

4. t ∈ T does not exist, corr (T) -T1 is satisfied unless h (T) -h (T1) Λt2 ═ T ] - { T };

5. for all T ∈ T, when T ≠ T1 ≠ T2, the relationship between event T and event T1 on the unfolded net is the same as the relationship between event T and event T2.

Further, the determination condition of the reconfigurable iterative relationship is as follows:

referred to as a transition, is referred to as a transition,

for any one The activities mapped into the process model are a1 and a2, namely h (t1) ═ a1 and h (t2) ═ a 2; when t1 and t2 satisfy the following conditions, activities a1 and a2 have reconfigurable iterative relationships:

1. the configuration of t1 differs from the configuration of t2 only by t 2: [ t1] - [ t2] - { t2 };

2. t2 is a truncation event, and its configuration corresponding to event corr (t2) and t1 differ only by corr (t2), i.e., [ t1] ═ corr (t2) ] - { corr (t2) };

3. if h (T2) ≠ h (corr (T2)), then a1 has a reconfigurable iterative relationship with a2, otherwise, if T ∈ T, and T ≠ T1 ^ T ≠ T2, and T has no reconfigurable relationship with T1 and T2, a1 has a reconfigurable iterative relationship with a 2.

Further, the determination condition of the reconfigurable selection relationship is as follows:

referred to as a transition, is referred to as a transition,

for any one

The activities mapped into the process model are a1 and a2, namely h (t1) ═ a1 and h (t2) ═ a 2; the activities a1 and a2 may exist when t1, t2 satisfy the following conditionsReconstructed selection relation:

1. t1 conflicts with t 2;

2. t1 and t2 occur under the same conditions;

3. the last set of t1 and the last set of t2 are both empty or intersect.

Further, the conditions for determining the reconfigurable concurrency relationship are as follows:

for the process model p, (C, a; F, M0), pi (o, h) is a branch process containing a truncation event corresponding to the process model p, where o (S, T; F') is an occurrence net, h is a mapping function from the transition set to the active set, C is the condition set, a is the active set, referred to as an activity, M0 is the initial state of p, S is the pool set, T is the set of transitions,

referred to as a transition, is referred to as a transition,

for any one

The activities mapped into the process model are a1 and a2, namely h (t1) ═ a1 and h (t2) ═ a 2; when t1, t2 satisfy the following conditions, activities a1 and a2 have a reconfigurable selection relationship:

1、t1 co t2；

2. neither t1 nor t2 are truncation events;

3. t1 and t2 occur under the same conditions;

4. the existence of T ∈ T ≠ T1 ≠ T2 satisfies

Or for any T ∈ T ≠ T1 ≠ T2, there are

Further, in step C, the predetermined conflict determination condition is:

referred to as an activity, M0 is the initial state of p, S is the pool set, T is the set of transitions, referred to as a transition, is referred to as a transition,

for any one

The activities mapped into the process model are a1 and a2, namely h (t1) ═ a1 and h (t2) ═ a 2; for any activity a1, a2 ∈ A, t1, t2 satisfy the following condition, there is no conflict between the activity relationship groups:

1. a1, a2 have no relation or only one relation;

2. when a1 and a2 have a reconfigurable sequential relationship, the relationship between a1 and a2 and any a ∈ p.A ^ a ≠ a1 ^ a ≠ a2 can only have the reconfigurable sequential relationship between the activity a and a1, or only have the reconfigurable sequential relationship between the activity a2 and a;

3. when a1 and a2 have a reconfigurable iterative relationship, no relationship can exist between a1 and a2 and any a epsilon p.A ^ a ≠ 1 ^ a ≠ a 2;

4. when a1 and a2 have a reconfigurable selection relationship or a reconfigurable concurrency relationship, the relationship between a1 and a2 and any a ∈ p.A ^ a ≠ a1 ^ a ≠ a2 can have only the selection relationship or the concurrency relationship.

Further, the predetermined priority determination rule in step D specifically is: and judging the priority of the active relationship group according to the type of the reconfigurable relationship to which the active relationship group belongs. Namely, each reconstruction selects a group of reconstruction with the highest priority of the type (the four types are reconfigurable sequential relationship, reconfigurable iterative relationship, reconfigurable selective relationship and reconfigurable concurrent relationship) to which the active relationship group belongs.

The sequence of reconstructing each activity relationship group directly influences the reduction degree of the activity and relationship of the original process model and the complexity of the reconstructed process model. And taking the type to which the activity relation group belongs as the basis of the reconstruction sequence, so that the generated process tree can be logical-smooth.

Further, the priority of the type of the reconfigurable relationship is as follows:

the reconfigurable sequential relationship has a highest priority, followed by a reconfigurable iterative relationship, the priorities of the reconfigurable selection relationship and the reconfigurable concurrency relationship being determined based on the number of active elements involved in the active relationship in the behavioral structure of the process model.

The reconfiguration priority designed by the invention can ensure the consistency of the logic of the process tree and the original process model and the simplification of the process tree structure.

In this specification, "X1", "X2", "X'" and the like (X is t, a, F and the like) do not particularly denote any data, but merely distinguish corresponding parameters, and do not have any other special meaning.

In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:

the method for generating the behavior equivalence process tree based on the complete finite prefix expansion can convert the process model of the non-BSPM model into the behavior equivalence process tree. The generated process tree structure is high in simplification degree and highly consistent with the logic of the original process model (high in accuracy), and no equivalent reconfigurable activity information is lost. In addition, the method has higher equivalent behavior process tree generation efficiency.

Drawings

The invention will now be described, by way of example, with reference to the accompanying drawings, in which:

FIG. 1 is a process model classification that is equivalently convertible to a process tree.

FIG. 2 is one embodiment of a BSPM model being converted into a process tree.

FIG. 3 is one embodiment of a non-BSPM model conversion to a process tree.

FIG. 4 one embodiment of a process model generated by the PLG.

FIG. 5 is a statistical result of the time and corresponding number of activities for extracting a process tree in a PLG-generated process model.

Fig. 6 is the average activity time consumption statistics for the RD group experiments.

FIG. 7 is an embodiment of a partial ED set to generate a process tree, where (a) is an experimental model, (b) is a process tree equivalent to the experimental model in (a), and (c) is a reconstructed process model according to (b).

FIG. 8 is a process model that cannot be converted to a process tree, (a) is an experimental model, and (b) is an expanded mesh corresponding to (a).

FIG. 9 is another process model that cannot be converted to a process tree, (a) is an experimental model, (b) is an expanded mesh corresponding to (a), (c) is a process model reconstructed from (b), and (d) is an expanded mesh corresponding to (c).

FIGS. 10 to 13 show four embodiments of activity relationship determination, wherein (a) is an original Petri net and (b) is an expanded net corresponding to (a).

Fig. 14 is an example of the activity relation priority determination.

Detailed Description

All of the features disclosed in this specification, or all of the steps in any method or process so disclosed, may be combined in any combination, except combinations of features and/or steps that are mutually exclusive.

Any feature disclosed in this specification (including any accompanying claims, abstract) may be replaced by alternative features serving equivalent or similar purposes, unless expressly stated otherwise. That is, unless expressly stated otherwise, each feature is only an example of a generic series of equivalent or similar features.

A. the process model is expanded into a branch process containing truncation events using a full prefix expansion method.

B. And extracting the activity relation group which satisfies the reconfigurability from the branch process. So-called activity relationship groups, i.e., combinations of activities associated in the process model, such as sequential relationships between two activities at adjacent levels, parallel/concurrent/selective relationships between two activities at the same level, etc. The reconfigurable activity relationship group can be judged by the definition of the reconfigurable relationship, that is, by comparing the relationship of the activity relationship component with the defined reconfigurable relationship, whether the activity relationship group is the reconfigurable activity relationship group or not can be determined, or further, which kind of reconfigurable activity relationship is determined.

The reconfigurable relations comprise a reconfigurable sequential relation, a reconfigurable iterative relation, a reconfigurable selection relation and a reconfigurable concurrent relation. The corresponding definitions are as follows:

1. reconfigurable sequential relationship judgment conditions: for the process model p, (C, a; F, M0), pi (o, h) is a branch process containing a truncation event corresponding to the process model p, where o (S, T; F') is an occurrence net, h is a mapping function from the transition set to the active set, C is the condition set, a is the active set,

referred to as a transition, is referred to as a transition,

for any one

The activities mapped into the process model are a1 and a2, namely h (t1) ═ a1 and h (t2) ═ a 2; when t1 and t2 satisfy the following conditions, a1 and a2 have a reconfigurable sequential relationship, which is recorded as → (a1 and a 2).

(1) [ t1] - [ t2] - { t2}, i.e., the configuration of t1 differs from the configuration of t2 only by t 2;

(2) i.e. local configuration t1]The set of activities mapped into the process model p does not contain the activities mapped into the process model p by event t 2.

(3) If T2 'e.t is present, it is satisfied that T2' ≠ T2 ^ h (T2') ═ h (T2), and for all T1' satisfying [ T1'] ∪ { T2' } [ T2'] there must be h (T1') ═ h (T1).

(4) T ∈ T does not exist, corr (T) -T1 is satisfied unless h (T) -h (T1) Λt2 ═ T-T }.

(5) For all T ∈ T, when T ≠ T1 ≠ T2, the relationship between event T and event T1 on the unfolded net is the same relationship as event T and event T2, i.e., T # T1 ^ T # T2 or T co T1 ^ T co T2 or T > T1 ^ T > T2 or T < T1 ^ T < T2.

With a reconfigurable sequential relationship between a1 and a2, a2 must occur after activity a1 occurs. t1 and t2 can determine that a1 and a2 are in sequence relation when four conditions of (1), (2), (3) and (4) of definition 1 are met, but the reconfigurable sequence relation between a1 and a2 can be determined only when (5) is met simultaneously. Condition (1) of definition 1 guarantees that t2 can occur directly after t1, confirming that a2 can be reached directly from a 1; condition (2) ensures that a2 does not occur before a 1; condition (3) condition (4) determines that what happens before a2 must be a1, while excluding the possibility that a2 has an iterative relationship with a 1; condition (5) determines that the a1 and a2 reconstructions do not affect other relationships; when t1 and t2 satisfy the condition of definition 1, the conditions for determining the reconfigurable iterative relationship, selection relationship and concurrency relationship are not satisfied.

The sequential relationship is ordered, with the meaning of existence → (a1, a2) and → (a2, a1) differing. The iterative relationships of all activities can be extracted as long as the sequential relationships are traversed once, but after a plurality of activities are reconstructed, new activities collect direct predecessors of old activities, and new sequential relationships may appear.

For example, in fig. 10(b), event a and event b, [ a ] ═ a }, [ b ] ═ a, b }, and a and b satisfy five conditions defining 1 at the same time, so that a and b have a reconfigurable sequential relationship, i.e., → (a, b), and similarly → (b, c) and → (c, d). Therefore → (a, b) after reconstruction → (b, c) cannot be reconstructed, and therefore the process tree corresponding to fig. 10(a) is → (→ (a, b), → (c, d)).

2. Reconfigurable iterative relationship judgment conditions: for the process model p ═ (C, a; F, M0), where (o, h) is a branch process of the process model p that contains truncation events, where (o ═ is an occurrence net and h is a mapping function.

h (t1) ═ a1 and h (t2) ═ a2, and when t1 and t2 meet the following conditions, a1 and a2 have a reconfigurable iterative relationship, wherein a1 occurs first and is marked as ℃ ([ alpha ] (a1 and a2) and a2 occurs first and is marked as ℃ ([ alpha ] (a2 and a 1).

(1) [ t1] - [ t2] - { t2}, i.e., the configuration of t1 and the configuration of t2 differ only by t 2;

(2) [ t1] - { corr (t2) ] - { corr (t2) }, i.e., t2 is a truncation event, and the configuration of its corresponding event corr (t2) and the configuration of t2 differ only by corr (t 2);

(3) if h (t2) ≠ h (corr (t2)), a1 has a reconfigurable iterative relationship with a2, and a1 occurs first;

(4) if h (T2) ═ h (corr (T2)), only for all T ∈ T and T ≠ T1 ^ T ≠ T2, if T does not have a reconfigurable relationship with T1, T2, then a1 has a reconfigurable iterative relationship with a2, and a2 occurs first.

With a reconfigurable iterative relationship between a1 and a2, it may be selected whether a2 occurs after activity a1, and a1 may occur again after a2 occurs. t1 and t2 can determine that a1 and a2 are iterative relationships when the two conditions of (1) and (2) in definition 2 are met, but only if (3) and (4) are met, the reconfigurable iterative relationship between a1 and a2 can be determined.

Condition (1) of definition 2 guarantees that t2 can occur directly after t1, confirming that a2 can be reached directly from a 1; condition (2) excludes the possibility that t1 and t2 have an order relationship, and determines that a1 can be reached directly from a 2. Condition (3) determines that there is a reconfigurable iterative relationship between a1 and a2, and that a1 occurs first; condition (4) excludes the situation that a1 and a2 are not reconfigurable, and determines that a1 and a2 have a reconfigurable iterative relationship, and that a2 occurs first; when t1 and t2 satisfy the condition of definition 2, the conditions for determining the reconfigurable iterative relationship, selection relationship and concurrency relationship are not satisfied any more. The iterative relationship is ordered, and the existence of ℃. (a1, a2) and ℃. (a2, a1) has different meanings. The priority of the reconfigurable iterative relationship is lower than that of the other three relationships, so that the reconfigurable iterative relationship can be judged only after the other relationships are judged. The reconfigurable iterative relationship can be extracted once through traversal, but when a plurality of activities are reconfigured, new activities collect direct predecessors of old activities, and new iterative relationships may appear.

For example, in fig. 11(b), event a2 and event c, [ a2] ═ a1, c, a2}, [ c ] ═ a1, c }, [ corr (a2) ] ═ a1] ═ a1}, a2 and b satisfy the two conditions (1) and (2) defined in 2, but do not satisfy the conditions (3) or (4), and there is no reconfigurable iterative relationship between a and c. However, when a and b are reconstructed, x (a, b) and c satisfy the condition of definition 2, and a reconfigurable iterative relationship exists between them, so that the process tree corresponding to fig. 11(a) is ∈ (× (a, b), c).

3. Reconfigurable selection relation judgment conditions: for the process model p ═ (C, a; F, M0), where (o, h) is a branch process of the process model p that contains truncation events, where (o ═ is an occurrence net and h is a mapping function.

h (t1) ═ a1, h (t2) ═ a2, and when t1 and t2 satisfy the following conditions, a1 and a2 have a reconfigurable selective relationship, and are marked as x (a1, a2) or x (a2 and a 1).

(1) t1# t2, i.e., the collision of t1 with t 2;

(2) [ t1] - { t1} - [ t2] - { t2}, i.e., the occurrence conditions of t1 and t2 are the same;

(3)

or

That is, the rear set of t1 and the rear set of t2 are both empty orThe two intersect.

When a reconfigurable selection relationship exists between a1 and a2, a1 conflicts with a2, one occurs, the other does not occur, and after a1 or a2 occurs, the reached activities are consistent. t1, t2 can determine that a1 and a2 are selection relations when condition (1) of definition 3 is satisfied, but only if conditions (2) and (3) are satisfied can determine that a1 and a2 have a reconfigurable selection relation.

Condition (1) of definition 3 ensures that t1 is in conflict with t2, one of which occurs and the other does not occur; condition (2) determines that the event experienced when t1 is reached is the same as when t2 is reached; condition (3) determines that a1 is consistent with the activity that can be reached after a 2.

When t1 and t2 satisfy the condition of definition 3, the conditions for determining the reconfigurable selection relationship, and concurrency relationship are not satisfied any more. The selection relationship is disordered, and the meaning of x (a1, a2) is consistent with that of x (a2, a 1). The reconfigurable selection relations can be extracted once through traversal, but when a plurality of activities are reconfigured, new activities collect direct predecessors of old activities, and new selection relations may appear.

For example, event a and event b in fig. 12(b), which satisfy (1) a # b; (2) (3) h (a · ∩ h (b · h) ═ S2}, so there are x (a, b) ×, for f and e the condition (1) of definition 3 is satisfied, but the remaining two conditions are not satisfied, so f and e have an optional relationship but are not reconfigurable.

4. Reconfigurable concurrency relationship judgment conditions: for the process model p ═ (C, a; F, M0), where (o, h) is a branch process of the process model p that contains truncation events, where (o ═ is an occurrence net and h is a mapping function.

h (t1) ═ a1, h (t2) ═ a2, and a1 and a when t1 and t2 satisfy the following conditions2 has a reconfigurable concurrency relationship and is marked as | | (a1, a2) or | | (a2, a 1).

(1)t1 co t2；

(2) Neither t1 nor t2 are truncation events;

(3) the occurrence conditions of [ t1] - { t1} - [ t2] - { t2} t1 ═ t2, that is, t1 and t2 are the same;

(4) the existence of T ∈ T ≠ T1 ≠ T2 satisfies

If T does not satisfy the former, then for any T ∈ T ≠ T1 ≠ T2, there is

When a reconfigurable concurrency relationship exists between a1 and a2, a1 and a2 can occur simultaneously, and after a1 or a2 occurs, the next activity can be reached. t1 and t2 can determine that a1 and a2 are in a concurrency relationship when the condition (1) of definition 3 is met, but can determine that a1 and a2 have a reconfigurable concurrency relationship only when the conditions (2), (3) and (4) are met.

Condition (1) of definition 4 ensures that t1 does not conflict with the occurrence condition of t 2; condition (2) excludes the possibility that t1 or t2 have a selective relationship with other events; condition (3) determines that the event experienced when t1 is reached is the same as when t2 is reached; condition (4) determines that the next event can be reached after both t1 and t2 have occurred.

When t1 and t2 satisfy the condition of definition 4, the conditions for determining the reconfigurable selection relationship, and concurrency relationship are not satisfied any more. The concurrency relationship is unordered, and the meaning of | | (a1, a2) and | (a2, a1) are consistent. The reconfigurable concurrency relationship can extract the concurrency relationship of all activities only through one traversal, but after a plurality of activities are reconfigured, new activities collect direct predecessors of old activities, and new concurrency relationships may appear.

For example, in fig. 13(b), event b and event c satisfy (1) b co c, (2) neither b nor c is a truncation event, (3) [ b ] - { b } - [ c ] - { c } - { a }, and (4) b · ∩ · e } { S5 }' c · ∩ · e } { S6}, so that | | (b, c) satisfies condition (1) (2) (4) of definition 4 for d and e, but does not satisfy condition (3), so d and e have a selective relationship but are not reconstructable.

C. And D, according to a preset conflict judgment condition, when judging that no conflict exists between the extracted activity relation groups, executing.

If there is a conflict between the activity relationship groups, the activity (the elements in the activity relationship group) cannot be reconstructed, and the process model for plan conversion is not the process model equivalent to the process tree behavior.

D. And reconstructing the extracted activity relation group according to a preset rule, wherein the reconstructed process tree is the process tree which is obtained, namely the process tree equivalent to the process model behavior.

Example two

The computer-implemented process of the above-mentioned processes a-D is:

inputting: process model p ═ (C, a; F, M0);

and (3) outputting: a relationship matrix RM;

fair reference definition 1, subsequent judgment is as follows

For the explanation of each parameter in the flow, refer to the explanation section of technical terms above.

For the relationship matrix, it is necessary to determine whether the activities in the relationship matrix conflict, and if so, the activities cannot be reconstructed, that is, the process model is not a process model equivalent to the process tree behavior.

5. Determination conditions as to whether or not the active relationship conflicts (i.e., the above-described predetermined conflict determination conditions): for the process model p being (C, a; F, M0), the Relationship Matrix (RM) is a relationship matrix corresponding to the process model p, and when any of a1, a2 ∈ a, t1, and t2 satisfies the following condition, the active relationships in the relationship matrix do not conflict.

(1) a1, a2 has no relation or only one relation;

(2) when → (a1, a2) is present, the only relationship that can exist between a1 and a2 and any a ∈ p.A ≠ a1 ≠ a2 is → (a, a1) or → (a2, a);

(3) when ℃ ∈ (a1, a2) exists, no relationship can exist between a1 and a2 and any a ∈ p.A ^ a ≠ 1 ^ a ≠ a 2;

(4) when x (a1, a2) or | | (a1, a2) is present, the relationship that can exist between a1 and a2 and any a ∈ p.A ^ a ≠ a1 ^ a ≠ a2 is only a selective relationship or a concurrent relationship.

In step D, the reconstruction for each activity relationship has a definition of priority (i.e., a reconstruction rule). The most preferred is the sequential relationship, after the sequential relationship is reconstructed, new non-sequential relationships are particularly easy to extract, and the new non-sequential relationships may conflict with currently extracted non-sequential relationships, but on the contrary, after the activities of two non-sequential relationships are reconstructed, a part of structural information may be lost, because the reconstruction of the concurrency, selection and iteration relationships may merge arrows respectively pointing to the two activities into one, so that new conflicts are not generated between the reconstructed new activities and the new relationships extracted again, and even conflicts between the activities before reconstruction and the activities of other original non-sequential relationships may disappear, so that the sequential relationship is preferentially reconstructed.

An activity with an iterative relationship does not generate a relationship with other activities, so the iterative relationship is prioritized behind the sequential relationship.

The remainder is to determine the priority of the selection relation and the concurrency relation. Obviously, the priority of both the selection relation and the concurrent relation is after the sequential relation. How to determine the priority relationship between the two is dependent on the behavior structure of the process model.

For example, in the process model in fig. 14, the selection relationship between activity b and activity c is prioritized, and the concurrent relationship between activity b and activity d in the process model (b) is prioritized, how to judge their priority relationship, taking the process model in fig. 14 as an example, three relationships of | | (b, d), | (c, d) and × (b, c) have related activity elements, it is necessary to judge the priority, there is another relationship ◎ 1 between activity d and b, c at the same time, and another relationship ◎ 2 between b, c, and there is the fewest related activity elements with ◎ 2 relationship, so the relationship between b, c is prioritized.

In one embodiment, the computer-implemented process for determining the priority of an activity relationship is:

inputting: the process model p is (C, a; F, M0), and the corresponding relation matrix is RM (see an embodiment above);

and (3) outputting: judging the result back to the relation group RL with the priority reconstruction;

by the method, a group of activities can be reconstructed to obtain a new process model. By continuously reconstructing the process model, when the process model has only one activity left, the name of the activity is the prefix expression of the process tree corresponding to the process model p.

In one embodiment, a computer-implemented method of process tree generation is:

inputting: process model procedure p

And (3) outputting: process tree expressions

The method comprises the following steps:

the pseudo code for the process model reconstruction algorithm delaFromp is shown below.

Input process model p ═ (C, a; F, M0), a1, a2 activities that need reconstruction, ◎ is the relationship between a1 and a2

And (3) outputting: reconstructed Process model p'

The method comprises the following steps:

the method deletes a certain group of activities a1 and a2 in the original process model, adds a reconstructed new activity newA, and the new activity newA is named by prefix expressions of activities a1 and a 2. Then according to the updated activity set, some conditions which do not influence the relationship between the activities are deleted. And secondly, deciding which flow relationships to retain according to the updated activity set and condition set, and noting that although the new activity newA aggregates all the flow relationships of the old activities a1 and a2, these flow relationships still need to be judged whether or not to be retained. Finally, the new process model is returned.

EXAMPLE III

This example discloses the test procedure applied to the method of the present invention. According to this embodiment, the feasibility and effectiveness of the method of the above embodiment can be verified, and the efficiency of the generation can be directly observed.

The present embodiment uses a Process Log Generator (PLG) to generate one hundred different Process models, as shown in fig. 4, the example model includes 4 basic structures used in the analysis of the present invention, and the Process model generated by PLG is denoted as RD group; and constructing ten non-BSPM models equivalent to the process tree, recording the models as ED groups, and testing the two groups of models as test cases. In order to ensure the confidence of the test result, the unification of hardware during the test of the two groups of data is required to be ensured. In this embodiment, an Intel (R) core (TM) i5-6200U CPU @2.30GHz 2.40GHz PC with 8G RAM is selected as the method carrier.

The test procedure was designed as follows: (1) visualizing the process models by using an open-source graphic visualization tool Graphviz for each group of process models; (2) according to the process model activity relation extraction method provided by the invention, the corresponding process tree is extracted and visualized; (3) comparing the process model with the process tree to determine the accuracy of the process tree; (4) and counting the time for extracting the process tree and the activity number of the corresponding process model.

For the accuracy of the behavior equivalence process tree generation method, the process model and the corresponding process tree can be compared in a visualization mode. As shown in FIG. 7, the process tree generated by the method of the present invention is consistent with the logic of the original process model.

For the RD group of experimental models, the time for extracting the process tree and the number of activities corresponding to the process model are counted, and the result is shown in fig. 5. Fig. 6 shows the average activity time consumption statistics of the RD group experimental model, and it can be seen from the figure that the efficiency of the algorithm for converting the BSPM into the process tree is high, and the average time consumption to each activity tends to be 0.5 and also tends to be stable.

Fig. 7 shows the transformation of a part of 10 experimental models in ED experimental data, wherein (a) is an original Petri net, (b) is a process model equivalent to the behavior of the original Petri net, and (c) is a new Petri net constructed from a process tree. It can be seen that for most models, after converting them into a process tree, its overall behavioral structure can be easily observed. After a new Petri network is constructed according to the process tree, the front and rear Petri networks (namely 7a and 7c) are compared, the new Petri network can be found out to simplify partial structures of the original Petri network, so that a plurality of useless library and flow relations on the behavior structure are reduced, the redundancy of an original process model is reduced, and the visualization effect is improved.

Example four

This example separately discloses two process models that are not suitable for the method of the present invention to convert into a behavior equivalence process tree.

1. There are a variety of relationships between a certain set of activities.

As shown in FIG. 8, 8(a) is an original Petri net, and FIG. 8(b) is an expanded net of the original Petri net. In the case of fig. 8, the expanded mesh in (b) obtained by expanding the original model may be detected that events T1 and T0, T1 and T2 satisfy the reconfigurable selective relationship determination condition, T6_1 and T5 satisfy the reconfigurable parallel relationship determination condition, and T6_1 and T2_2, T5 and T0_2 satisfy the reconfigurable iterative relationship determination condition, where × (T0, T1), × (T1, T0), × (T1, T2), × (T2, T1), | (T5, T6), | (T6, T5), | (T5, T0), (+) (T6, T2) may be extracted. Among these, it can be found that ∈ (T5, T0) conflicts with four relationships × (T0, T1), × (T1, T0), | (T5, T6), | (T6, T5), and that relationships ∈ (T6, T2) conflicts with four relationships × (T1, T2), × (T2, T1), | (T5, T6), | (T6, T5), so the case in fig. 8 cannot be converted into a process tree.

2. Relationships between a certain set of activities do not belong to a basic relationship.

Fig. 9(a) is an original Petri net, fig. 9(b) is an expanded net of the original Petri net, fig. 9(c) is a model after active reconstruction, and fig. 9(d) is an expanded net of (c). In case two, the expanded mesh (b) is detected, and it can be found that the events T3 and T2_1, T1 and T0_1 satisfy the reconfigurable iterative relationship judgment condition, and then ∈ (T0, T1) and ∈ (T2, T3) can be extracted. Oc (T0, T1) and oc (T2, T3) do not conflict with each other, and when they are reconstructed, fig. 9(c) is obtained, and when they are expanded, the expanded mesh of fig. 9(d) is obtained, and at this time, a new relationship cannot be detected on the expanded mesh (d), but all the activities on fig. 9(c) have not been reconstructed into one, and therefore the cases in fig. 9 cannot be converted into a process tree.

The invention is not limited to the foregoing embodiments. The invention extends to any novel feature or any novel combination of features disclosed in this specification and any novel method or process steps or any novel combination of features disclosed.

Claims

1. A behavior equivalence process tree generation method based on complete finite prefix expansion is characterized by comprising the following steps:

2. The behavior equivalence process tree generation method according to claim 1, wherein in the step B, the method for determining whether the activity relationship group satisfies the reconfigurable relationship includes:

b1: extracting a transition set from the branch process;

3. The behavior equivalence process tree generation method of claim 2, wherein the reconfigurable relationships comprise reconfigurable sequential relationships, reconfigurable iterative relationships, reconfigurable selection relationships, and reconfigurable concurrent relationships.

4. The behavior equivalence process tree generation method of claim 3, wherein the reconfigurable ordering relationship is determined by:

referred to as a transition, is referred to as a transition,

for any one Its activity mapped into the process model is a1, a2, respectively; when t1 and t2 satisfy the following conditions, activities a1 and a2 have reconfigurable sequential relationship:

5. The behavior equivalence process tree generation method of claim 3, wherein the reconfigurable iterative relationship is determined by:

for any one

The activities mapped into the process model are a1 and a2, namely h (t1) ═ a1 and h (t2) ═ a 2; when t1 and t2 satisfy the following conditions, activities a1 and a2 have reconfigurable iterative relationships:

6. The behavior equivalence process tree generation method of claim 3, wherein the reconfigurable selection relationship is determined by:

referred to as a transition, is referred to as a transition, for any one

1. t1 conflicts with t 2;

2. t1 and t2 occur under the same conditions;

3. the last set of t1 and the last set of t2 are both empty or intersect.

7. The behavior equivalence process tree generation method of claim 3, wherein the reconfigurable concurrency relationship is determined by:

referred to as a transition, is referred to as a transition,

for any one

1、t1 co t2；

2. neither t1 nor t2 are truncation events;

3. t1 and t2 occur under the same conditions;

4. there is a T ∈ T ≠ T1 ≠ T ≠t2 satisfies

Or for any T ∈ T ≠ T1 ≠ T2, there are

8. The behavioral equivalence process tree generation method according to any one of claims 3-7, wherein in step C, the predetermined conflict determination condition is:

for any one

1. a1, a2 have no relation or only one relation;

9. The behavior equivalence process tree generation method according to claim 8, wherein the predetermined priority determination rule in step D specifically is: and judging the priority of the active relationship group according to the type of the reconfigurable relationship to which the active relationship group belongs.

10. The behavior equivalence process tree generation method of claim 9, wherein the types of the reconfigurable relationships have priorities of: