CN109685453B - Method for intelligently identifying effective paths of workflow - Google Patents
Method for intelligently identifying effective paths of workflow Download PDFInfo
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- CN109685453B CN109685453B CN201811493222.6A CN201811493222A CN109685453B CN 109685453 B CN109685453 B CN 109685453B CN 201811493222 A CN201811493222 A CN 201811493222A CN 109685453 B CN109685453 B CN 109685453B
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- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
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Abstract
The invention relates to the technical field of workflow, in particular to a method for intelligently identifying effective paths of workflows. Traversing a workflow, and reading all paths in the workflow; taking the intersection of parameter conditions among nodes on each path as a path condition; splitting each path condition to obtain a plurality of parameter conditions; decomposing parameter conditions to obtain characteristic information, and calculating a test value of the factor parameter according to the characteristic information; carrying out Cartesian product operation on the obtained test value to obtain a workflow key value set; and sequentially replacing each key value into the path condition, calculating the replaced path condition, and judging that the path is an effective path if only one path is true as a result of substituting a group of key values into each path condition calculation. In the path searching process, the connection between every two nodes is not required to be judged once, and only whether the whole path is unobstructed or not is judged, so that the path searching method can be suitable for effective path selection of complex multipath workflow.
Description
Technical Field
The invention relates to the technical field of workflow, in particular to a method for intelligently identifying effective paths of workflows.
Background
The workflow is a calculation model of the workflow, and the work nodes in the workflow are displayed in a computer by adopting different logic rules and are calculated by using an appropriate model. The workflow modeling abstracts the business flow in the actual working process, establishes an information model which can be identified and processed by a computer, realizes the automatic circulation process of the business flow, and enables documents, information or tasks to be transferred and executed among different executors. The active path is a sequence of workflow nodes with correctness, integrity, executability, and reliability.
Enterprise information management systems may involve workflow design and application. The application of the workflow in the enterprise information management system follows the related management rules, and the same workflow signing node has multiple combined sequences. Only a portion of the multiple combined sequences is determined to be a valid path based on the traffic logic.
At present, most information systems adopt if/else or switch/case to judge the signature turning in a certain signature node, and signature turning conditions are all solidified in a program, so that excessive condition judgment is nested in a workflow path searching method, the program code quantity is emphasized, the program readability is reduced, the program execution efficiency is affected, the accuracy is lower, errors are easy to occur, the integrity and the accuracy of a workflow path are judged manually, the frequent change of a service cannot be adapted, and the maintenance is difficult. And if a more complex workflow is encountered, once the flow branches are adjusted, the amount of work to modify based on the existing flow design may be greater than the amount of work to redesign according to the new flow.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a method for intelligently identifying the effective path of a workflow, which is suitable for the effective path selection of a complex multipath workflow, has simple logic and accurate path searching.
The invention discloses a method for intelligently identifying effective paths of workflows, which has the technical scheme that:
traversing a workflow, and reading all paths in the workflow;
taking the intersection of parameter conditions among nodes on each path as a path condition;
splitting each path condition to obtain a plurality of parameter conditions;
decomposing the parameter conditions to obtain a plurality of characteristic information including parameter names of factor parameters, and calculating test values of the factor parameters according to the characteristic information;
carrying out Cartesian product operation on the obtained test values of each factor parameter to obtain a workflow key value set;
and sequentially replacing each key value in the workflow key value set into a path condition, calculating the replaced path condition, and judging that the path is an effective path if only one path is true as a result of substituting a group of key values into each path condition calculation.
Preferably, the characteristic information includes a parameter name and a parameter type of the factor parameter, or further includes character string data or a numerical range;
wherein the parameter types include a string type, a boolean type, and a numeric type.
Preferably, each parameter condition in the path conditions is connected through an and or;
splitting each path condition, and splitting with an and or as a separator when a plurality of parameter conditions are obtained.
Preferably, when the parameter condition format is [ parameter name ] [ operator ] [ character string data ], the type of the parameter condition is character string;
when the parameter condition format is [ parameter name ] or ]! When the parameter name is, the type of the parameter condition is Boolean type;
when the parameter condition format is [ parameter name ] [ operator ] [ value ], the type of the parameter condition is numerical.
Preferably, when the type of the certain parameter condition a is a character string type, calculating the test value of the factor parameter according to the feature information includes:
defining a factor parameter queue ParamList and a test value queue ParamValueList;
adding the parameter name P of the parameter condition A factor parameter into a factor parameter queue ParamList, and adding the character string data of the parameter condition A into a test value queue ParamValueList;
searching other parameter conditions with the same parameter name except the parameter condition A, and adding any one character string data except the character string data of the parameter condition A into a test value queue ParamValueList;
and performing de-duplication treatment on the test value queue ParamValueList to obtain a test value of the factor parameter P.
Preferably, when the type of the certain parameter condition a is boolean, calculating the test value of the factor parameter according to the feature information includes:
defining a factor parameter queue ParamList and a test value queue ParamValueList;
and adding the parameter name P of the parameter condition A factor parameter into a factor parameter queue ParamList, and adding true and false into a test value queue ParamValueList, wherein the true and false are test values of the factor parameter P.
Preferably, when the type of the certain parameter condition a is a numerical value, calculating the test value of the factor parameter according to the feature information includes:
defining a factor parameter queue ParamList, a test value queue ParamValueList and a boundary value queue ParamEdgeList;
adding the parameter name P of the parameter condition A factor parameter into a factor parameter queue ParamList, and adding the numerical value data of the parameter condition A into a boundary value queue ParamEdgeList;
searching other parameter conditions with the same parameter name except the parameter condition A, and adding the numerical value data of the other parameter conditions into a boundary value queue ParamEdgeList;
adding all values in the boundary value queue into a test value queue ParamValueList; in addition, the values in the boundary value queue are arranged from small to large, random numbers between two adjacent values are sequentially selected, and random numbers smaller than the minimum boundary value and larger than the maximum boundary value are added into the test value queue ParamValueList.
Preferably, the workflow is traversed by means of depth-first search
The beneficial effects of the invention are as follows: the invention has clearer logic, adopts computer automatic calculation, and has higher readability and executable performance.
1. The invention supports a plurality of parameter types such as numerical type, boolean type, character type, enumeration type and the like.
2. The system automatically analyzes the branch conditions, generates factor parameters, intelligently analyzes and generates test values of each parameter according to the parameter value range, wherein the test values comprise boundary values of the parameters, and the generated test values can completely represent each condition range of the parameters, so that the accuracy of path finding is ensured.
3. In the path searching process, the connection between every two nodes is not required to be judged once, and only whether the whole path is unobstructed or not is judged, so that the path searching method can be suitable for effective path selection of complex multipath workflow.
4. When encountering a more complex workflow, the invention can rapidly verify the accuracy of workflow design even if the flow branches are adjusted.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of a multipath workflow of the present invention;
fig. 3 is a diagram of a specific example of the application of the present invention to a multipath workflow F1;
FIG. 4 is an example F1 path condition set diagram;
FIG. 5 is a graph showing the effect of the filtering paths of the parameter test values of the example F1.
Fig. 6 is an effective path output diagram of example F1.
Detailed Description
The invention will now be described in further detail with reference to the drawings and specific examples, which are given for clarity of understanding and are not to be construed as limiting the invention.
As shown in fig. 1, the workflow of the present invention is:
traversing a workflow, and reading all paths in the workflow;
taking the intersection of parameter conditions among nodes on each path as a path condition;
splitting each path condition to obtain a plurality of parameter conditions;
decomposing the parameter conditions to obtain a plurality of characteristic information including parameter names of factor parameters, and calculating test values of the factor parameters according to the characteristic information;
carrying out Cartesian product operation on the obtained test values of each factor parameter to obtain a workflow key value set;
sequentially replacing each key value in the workflow key value set into a path condition, calculating the replaced path condition, and judging that a path is an effective path if only one path is true as a result of substituting a group of key values into each path condition calculation;
and returning to the effective path set.
The characteristic information comprises a parameter name and a parameter type of a factor parameter or further comprises character string data or a numerical range;
wherein the parameter types include a string type, a boolean type, and a numeric type.
Preferably, each parameter condition in the path conditions is connected through an and or;
splitting each path condition, and splitting with an and or as a separator when a plurality of parameter conditions are obtained.
Preferably, when the parameter condition format is [ parameter name ] [ operator ] [ character string data ], the type of the parameter condition is character string;
when the parameter condition format is [ parameter name ] or ]! When the parameter name is, the type of the parameter condition is Boolean type;
when the parameter condition format is [ parameter name ] [ operator ] [ value ], the type of the parameter condition is numerical.
Preferably, when the type of the certain parameter condition a is a character string type, calculating the test value of the factor parameter according to the feature information includes:
defining a factor parameter queue ParamList and a test value queue ParamValueList;
adding the parameter name P of the parameter condition A factor parameter into a factor parameter queue ParamList, and adding the character string data of the parameter condition A into a test value queue ParamValueList;
searching other parameter conditions with the same parameter name except the parameter condition A, and adding any one character string data except the character string data of the parameter condition A into a test value queue ParamValueList;
and performing de-duplication treatment on the test value queue ParamValueList to obtain a test value of the factor parameter P.
Preferably, when the type of the certain parameter condition a is boolean, calculating the test value of the factor parameter according to the feature information includes:
defining a factor parameter queue ParamList and a test value queue ParamValueList;
and adding the parameter name P of the parameter condition A factor parameter into a factor parameter queue ParamList, and adding true and false into a test value queue ParamValueList, wherein the true and false are test values of the factor parameter P.
Preferably, when the type of the certain parameter condition a is a numerical value, calculating the test value of the factor parameter according to the feature information includes:
defining a factor parameter queue ParamList, a test value queue ParamValueList and a boundary value queue ParamEdgeList;
adding the parameter name P of the parameter condition A factor parameter into a factor parameter queue ParamList, and adding the numerical value data of the parameter condition A into a boundary value queue ParamEdgeList;
searching other parameter conditions with the same parameter name except the parameter condition A, and adding the numerical value data of the other parameter conditions into a boundary value queue ParamEdgeList;
adding all values in the boundary value queue into a test value queue ParamValueList; in addition, the values in the boundary value queue are arranged from small to large, random numbers between two adjacent values are sequentially selected, and random numbers smaller than the minimum boundary value and larger than the maximum boundary value are added into the test value queue ParamValueList.
Preferably, the workflow is traversed by means of a depth-first search.
As shown in fig. 2, which is a schematic diagram of a workflow F, the present invention applies the method to the workflow F, and explains as an embodiment:
example 1
S1: firstly, traversing a workflow F by utilizing depth-first search, and reading out all paths in the flow, wherein the paths at the moment contain effective paths and ineffective paths:
①N1-N2-N3-N5-N6-N7；
②N1-N2-N3-N5-N7；
③N1-N2-N5-N6-N7；
④N1-N2-N5-N7；
⑤N1-N2-N4-N3-N5-N6-N7；
⑥N1-N2-N4-N3-N5-N7；
⑦N1-N2-N4-N5-N6-N7；
⑧N1-N2-N4-N5-N7；
s2: taking the intersection of parameter conditions among nodes on each path as the path conditions:
①N1-N2-N3-N5-N6-N7：C1and C6→(P1>＝100and P2)and(P1<100or P1>＝200)
②N1-N2-N3-N5-N7；C1and C7→(P1>＝100and P2)and(P1>＝100and P1<200)
③N1-N2-N5-N6-N7；C2and C6→(P1>＝100and！P2)and(P1<100or P1>＝200)
④N1-N2-N5-N7；C2and C7→(P1>＝100and！P2)and(P1>＝100and P1<200)
⑤N1-N2-N4-N3-N5-N6-N7；C3and C4and C6→(P1<100)and(P2)and(P1<100or P1>＝200)
⑥N1-N2-N4-N3-N5-N7；C3and C4and C7→(P1<100)and(P2)and(P1>＝100and P1<200)
⑦N1-N2-N4-N5-N6-N7；C3and C5and C6→(P1<100)and(！P2)and(P1<100or P1>＝200)
⑧N1-N2-N4-N5-N7；C3and C5and C7→(P1<100)and(！P2)and(P1>＝100and P1<200)
s3: taking ' and ' or ' as a separator, splitting a single parameter condition in an acquisition path, and performing duplication removal operation to obtain the following parameter condition queues:
①P1>＝100
②P1<100
③P2
④！P2
⑤P1>＝200
⑥P1<200
s4: and (3) traversing the parameter condition queue obtained in the step (3), taking an operator as a separator to decompose the parameter condition to obtain factor parameters, parameter types and numerical ranges of the workflow F, and then obtaining a test value of the workflow F. In this process, the factor parameter queue ParamList, the test value queue ParamValueList, integer, floating point and other numerical parameters need to be defined, and the boundary value queue ParamEdgeList needs to be defined.
(1) P1> =100: the operator is "> =", P1 is a parameter name, and 100 is an integer value, so that P1 is an integer parameter, P1 is added to the factor parameter queue ParamList, and 100 is added to the boundary value queue ParamEdgeList of P1.
(2) Find parameter conditions related to P1 other than the condition P1> =100:
p1<100:100 is already in the boundary value queue of P1 and no further joins are repeated.
P1> =200: 200 is added to the boundary value queue of P1.
P1<200:200 is already in the boundary value queue of P1 and no further joins are repeated.
At this time, the P1 parameter condition is traversed.
According to (2), the boundary value queue of P1 is {100,200 }, and first 100,200 is added to the test value queue of P1. Secondly, arranging the numerical values in the P1 boundary value queue from small to large, sequentially taking the random numbers between two adjacent numerical values and the random number smaller than the minimum boundary value, and adding the random number larger than the maximum boundary value into the P1 test value queue, namely:
a. (- ≡100): a random number (- ≡100) is taken (e.g., 90) and added to the P1 test value queue ParamValueList.
b. (100, 200): a random number (e.g., 155) is taken (100, 200) and added to the ParamValueList of the test value queue for parameter P1.
c. (200, ++ -infinity): taking (200, + -infinity) a random number (205, for example) and adding the random number to the test value queue ParamValueList of the parameter P1;
and after the P1 test value is generated, obtaining the P1 test value {100,200,90,155,205}.
(3) P2: no operator =, i! =, <, <=, >, are=, are boolean type parameter, add P2 to the factor parameter queue ParamList, test values are true and false, add respectively to the test value queue ParamValueList of parameter P2. The boolean type parameter does not need to repeatedly traverse the analytical test values.
And after the P2 test value is generated, obtaining the P2 test value { true, false }.
From the above, the factor parameter queue { P1, P2} and the test value queue { {100,200,90,155,205}, { true, false }, are obtained.
S5: the obtained parameter test values are subjected to a Cartesian product calculation method, and the following data sets are obtained and used as workflow key value sets:
AxB= { (P1, P2) |P1 ε A ∈P2 ε B }, where A= (100,200,90,155,205), B= (true, false), then A x B= { (100, true), (100, false), (200, true), (200, false), (90, true), (90, false), (155, true), (155, false), (205, true), (205, false) } is the workflow key value set.
S6: and sequentially replacing the workflow key values into path conditions, calculating the replaced path conditions, and if only one path is true as a result of substituting a group of key values into each path condition calculation, then the path is an effective path.
S7: returning an effective path set:
①N1-N2-N3-N5-N7
②N1-N2-N5-N7
③N1-N2-N4-N3-N5-N6-N7
④N1-N2-N4-N5-N6-N7
⑤N1-N2-N3-N5-N6-N7
⑥N1-N2-N5-N6-N7
fig. 3 is a schematic diagram of a workflow F1, and fig. 4 to 5 are schematic diagrams of the present invention applying the method to the workflow F, and the present invention explains the application as a second embodiment:
example two
S1: first, the workflow F1 is traversed by depth-first search, and all paths in the flow are read out, as shown in fig. 4.
S2: taking the intersection of parameter conditions among nodes on each path as the path conditions, as shown in fig. 5:
s3: according to the condition definition specification, taking an ' and ' or ' as a separator, splitting a single parameter condition in an acquisition path, and performing a duplicate removal operation, thereby obtaining the following parameter conditions:
(1) type= "investment"
(2) type-! = "investment"
③isNeedLegal
④！isNeedLegal
⑤money>0
⑥money<200
⑦money>＝200
⑧money<500
⑨money>＝500
S4: and (3) traversing the parameter condition queue obtained in the step (3), taking an operator as a separator to decompose the parameter condition to obtain factor parameters, parameter types and numerical ranges of the workflow F1, and then obtaining a test value of the workflow F1. In this process, the factor parameter queue ParamList, the test value queue ParamValueList, integer, floating point and other numerical parameters need to be defined, and the boundary value queue ParamEdgeList needs to be defined.
(1) type= "invest", string type parameter, so type is added to the factor parameter queue ParamList, and "invest" is added to the test value queue ParamValueList for parameter type.
(2) Look up parameter conditions related to type except for the condition type= "invest":
type ≡! = "invest", any character string data (e.g. "non-invest") other than "invest" is added to the test value queue of the parameter type.
After the generation of the type test value is completed and the weight is removed, the type test value is obtained as { "invested", "non-invested" }.
(3) isceedleg: and adding the parameters of the Boolean type into a factor parameter queue ParamList, wherein the test values are true and false, and respectively adding the parameters into a test value queue ParamValueList of the parameters isneedleLegal. The boolean type parameter does not need to repeatedly traverse the analytical test values.
After the completion of the generation of the isneedledLegal test value, the isneedledLegal test value { true, false } is obtained.
(4) money <200: integer parameters, adding money into a factor parameter queue ParamList, and adding 200 into a parameter money boundary value queue ParamEdgeList.
(5) Find the parameter conditions related to money except for the condition money <200:
money > =200: 200 have been in the money's boundary value team and are not added repeatedly.
money <500: and adding 500 to the boundary value queue of the parameter money.
money > =500: 500 have been in the money's boundary value team and no further additions are repeated.
At this time, the money parameter condition is traversed.
According to (5), obtaining a money boundary value queue {200,500}, firstly adding 200,500 into the money test value queue, secondly arranging according to the numerical values in the money boundary value queue from small to large, sequentially taking random numbers before two adjacent numerical values, and adding a random number smaller than the minimum boundary value and a random number larger than the maximum boundary value into the money test queue, namely:
a. (- ≡200): taking a random number (- ≡200) (such as 131), and adding the random number into a ParamValueList of a test value queue of a parameter money;
b. (200, 500): a random number (e.g., 317) is taken (200, 500) and added to the test value queue ParamValueList for the parameter money.
c. (500, ++ -infinity): (500, + -infinity) of a random number (e.g.: 948) adding a ParamValueList into a test value queue of the parameter money;
and after the money test value is generated, obtaining the money test value of {200,500,131,317,948 }.
From the above, the factor parameter queue { type, isneedledLegal, money } and the test value queue { { "invest", "non-invest" }, { true, false }, {200,500,131,317,948 }, are obtained.
S5: the obtained parameter test values are subjected to a Cartesian product calculation method, and the following data sets are obtained and used as workflow key value sets: a×b×c= { (X, Y, Z) |x e a Y e B Z e C }, where a= ("investment", "non-investment"), b= (true, false), c= (200, 500,131,317,948).
The a×b×c= { ("investment", true, 131), ("investment", true, 200), ("investment", true, 317), ("investment", true, 500), ("investment", true, 948), ("investment", false, 131), ("investment", false, 200), ("investment", false, 317), ("investment", false, 500), ("investment", false, 948), ("non-investment", true, 131), ("non-investment", true, 200), ("non-investment", true, 317), ("non-investment", true, 500), ("non-investment", false, 948), ("non-investment", false, 131), ("non-investment", false, 200), ("false, 317), (" non-investment ", false, 500)," non-investment ", false,1, i.e., the working stream is the set of values.
S6: and sequentially replacing the workflow key values into path conditions, calculating the replaced path conditions, and if only one path is true as a result of substituting a group of key values into the calculation results of each path condition, the path is an effective path, and the verification result is shown in fig. 6.
S7: returning an effective path set:
(1) start-application unit leader-subject unit leader-business administration authority leader-end
(2) Start-application unit leader-subject unit leader-business administration authority leader-branch pipe leader-end
(3) Start-application unit leader-subject unit leader-business administration authority leader-branch leader-general manager-end
(4) Start-application unit leader-subject unit leader-business administration authority leader-legal auditor-branch administration leader-end
(5) Start-application unit leader-subject unit leader-business administration authority leader-legal auditor-branch leader-general manager-end
(6) Start-application unit leader-subject unit leader-investment department leader-business administration authority leader-branch pipe leader-general manager-end
(7) Start-application unit leader-subject unit leader-investment department leader-business administration authority leader-end
(8) Start-application unit leader-subject unit leader-investment department leader-business administration authority leader-legal auditor-branch leader-general manager-end
What is not described in detail in this specification is prior art known to those skilled in the art.
Claims (5)
1. A method for intelligently identifying a workflow effective path, comprising:
traversing a workflow, and reading all paths in the workflow;
taking the intersection of parameter conditions among nodes on each path as a path condition;
splitting each path condition to obtain a plurality of parameter conditions;
decomposing parameter conditions obtained by splitting each path condition to obtain a plurality of characteristic information including parameter names of factor parameters, and calculating test values of the factor parameters according to the characteristic information;
carrying out Cartesian product operation on the obtained test values of each factor parameter to obtain a workflow key value set;
sequentially replacing each key value in the workflow key value set into a path condition, calculating the replaced path condition, and judging that a path is an effective path if only one path is true as a result of substituting a group of key values into each path condition calculation;
when the type of a certain parameter condition A is a character string type, calculating the test value of the factor parameter according to the characteristic information comprises the following steps:
defining a factor parameter queue ParamList and a test value queue ParamValueList;
adding the parameter name P of the parameter condition A factor parameter into a factor parameter queue ParamList, and adding the character string data of the parameter condition A into a test value queue ParamValueList;
searching other parameter conditions with the same parameter name except the parameter condition A, and adding any one character string data except the character string data of the parameter condition A into a test value queue ParamValueList;
performing de-duplication treatment on the test value queue ParamValueList to obtain a test value of the factor parameter P;
when the type of a certain parameter condition A is Boolean type, calculating the test value of the factor parameter according to the characteristic information comprises the following steps:
defining a factor parameter queue ParamList and a test value queue ParamValueList;
adding a parameter name P of the parameter condition A factor parameter into a factor parameter queue ParamList, and adding true and false into a test value queue ParamValueList, wherein the true and false are test values of the factor parameter P;
when the type of a certain parameter condition A is numerical, calculating the test value of the factor parameter according to the characteristic information comprises the following steps:
defining a factor parameter queue ParamList, a test value queue ParamValueList and a boundary value queue ParamEdgeList;
adding the parameter name P of the parameter condition A factor parameter into a factor parameter queue ParamList, and adding the numerical value data of the parameter condition A into a boundary value queue ParamEdgeList;
searching other parameter conditions with the same parameter name except the parameter condition A, and adding the numerical value data of the other parameter conditions into a boundary value queue ParamEdgeList;
adding all values in the boundary value queue into a test value queue ParamValueList; in addition, the values in the boundary value queue are arranged from small to large, random numbers between two adjacent values are sequentially selected, and random numbers smaller than the minimum boundary value and larger than the maximum boundary value are added into the test value queue ParamValueList.
2. The method for intelligently identifying a workflow effective path of claim 1, wherein: the characteristic information comprises a parameter name and a parameter type of a factor parameter, and also comprises character string data or a numerical range;
wherein the parameter types include a string type, a boolean type, and a numeric type.
3. The method for intelligently identifying a workflow effective path of claim 1, wherein: each parameter condition in the path conditions is connected through an and or;
splitting each path condition, and splitting with an and or as a separator when a plurality of parameter conditions are obtained.
4. The method for intelligently identifying a workflow effective path of claim 2, wherein:
when the parameter condition format is [ parameter name ] [ operator ] [ character string data ], the type of the parameter condition is character string;
when the parameter condition format is [ parameter name ] or ]! When the parameter name is, the type of the parameter condition is Boolean type;
when the parameter condition format is [ parameter name ] [ operator ] [ value ], the type of the parameter condition is numerical.
5. The method for intelligently identifying a valid path of a workflow as claimed in claim 1, wherein the workflow is traversed by means of a depth-first search.
Priority Applications (1)
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