WO2014125836A1

WO2014125836A1 - Test data generating device

Info

Publication number: WO2014125836A1
Application number: PCT/JP2014/000777
Authority: WO
Inventors: 崇師北村; ティビッチゴックドウ; 大崎　人士
Original assignee: 独立行政法人産業技術総合研究所
Priority date: 2013-02-15
Filing date: 2014-02-14
Publication date: 2014-08-21
Also published as: JP6037307B2; JP2014157473A

Abstract

In an inputted parameter data (20) logic structure, an AND-AND hierarchy leveling means (4) switches a condition of a portion wherein an AND relation and an AND relation are contiguous from a subject node as a hierarchy, and deletes a subject child node (Ta). An OR-OR hierarchy leveling means (6) switches a condition of a portion wherein an OR relation and an OR relation are contiguous from a subject node as a hierarchy, and deletes a subject child node (ISR). A raising leveling means (8) finds a portion (34) wherein the AND relation and the OR relation are contiguous from the subject node (Ta) as a lower-order hierarchy and the OR relation and the AND relation are contiguous from the subject node as a higher-order hierarchy, switches the condition, and carries out leveling. It is thus possible to obtain standardized parameter data.

Description

Test data generator

This invention relates to an apparatus for generating test data for testing whether a program or the like operates normally.

In order to test the operation of software, a combination of data that may be input is created, and the test data is input to determine whether or not a desired operation is achieved.

Conventionally, test data is created by generating a combination of data that may be input by an all-pair method (pair-wise method) or the like. As a tool for test data generation using the all-pair method or the like, Microsoft's PICT (trademark) is sold.

For example, in PICT, as shown in FIG. 21, by defining parameters, values, and constraint conditions, test data based on combinations of values can be generated.

Here, a, b... M are parameters, and a1, a2... An are the values of the parameter a. The parameter a takes one of the values a1, a2,..., An by a: a1, a2,. The same applies to the second and subsequent lines.

Further, If m = m1 then a = an indicates that a is an when the parameter m is m1. Further, If b = b2 then NOT a = a2 and If a = a2 then NOT b = b2 show that the parameter b is b2 and the parameter a is a2.

∙ If parameters are given to the PICT program using data in this format, test data is generated and output.

As described above, in the test data generation tool using the all-pair method or the like, data having a logical structure as shown in FIG. 21 must be given. For this reason, the tool cannot be used for events that are not defined in such a logical structure.

Fig. 12 shows the logical structure of a certain event in a tree format. In this tree structure, input to a tool such as PICT is not possible.

Therefore, an object of the present invention is to make it possible to use a test data generation tool without expressing parameters with a predetermined logical structure.

(1) (2) A test data generation device according to the present invention includes a node arranged in a plurality of layers having an upper node indicating a target feature and a lower node indicating a lower-order feature of the upper-node feature. The upper node and the lower node are combined in an AND relationship in which all of the lower nodes must be established with respect to the upper node, or an OR relationship in which one of the lower nodes is established with respect to the upper node. Feature data that defines at least one of a requirement condition that determines whether the establishment or non-establishment of one node in between determines the establishment or non-establishment of the other node, and an exclusive condition that determines the simultaneous establishment or non-establishment of both nodes between nodes At least one of the following: (a) and-and-level flattening means; (b) or-or-layer flattening means; and (c) lifting flattening means. Test data generation comprising: flattening means for flattening a hierarchical structure of input feature data; and test data generating means for generating test data based on the combination of features based on the flattened feature data A device,
(a) The AND-and-level flattening means (a1) in the feature data, the target node defines an AND relationship, the child node of the target node is set as a target child node, and the target child node has an AND relationship. And-and-relation extraction means for finding a defined part; and (a2) if a required condition or an exclusion condition is attached to the target child node at the position found by the AND-and-relation extraction means, the request A request / exclusive condition allocating means for replacing a condition or an exclusive condition with the target node; and (a3) deleting the target child node at a location found by the AND-and-relation extracting means; A target child node deleting means for adding a target grandchild node as a child node to the AND relationship as a child node of the target node;
(b) The or-or hierarchy flattening means (b1) in the feature data, the target node defines an OR relationship, a child node of the target node is a target child node, and the target child node has an OR relationship. OR or OR relationship extraction means for finding a defined location, and (b2) if an exclusion condition is attached to the target child node in the location found by the OR or OR relationship extraction means, the exclusion condition is An exclusive condition allocating means for allocating to a target grandchild node that is a child node of the target child node, and (b3) a requirement condition is attached to the target child node at a location found by the or-or relationship extracting means. For example, the requirement condition allocating means for allocating the requirement condition to the target node, and (b4) the target child node at the location found by the OR-OR relationship extracting means. If the request condition that the target child node is a request destination is attached, an exclusion condition that sets an exclusion condition between a child node other than the target child node in the target node and the request source node of the request condition And (b5) the target child node is deleted at a location found by the OR-OR relationship extracting unit, and the target grandchild node that is a child node of the target child node is changed to a child node of the target node. And a target child node deletion means to be added to the OR relationship as
(c) The lifting flattening means (c1) in the feature data, the target node defines an AND relationship, a target child node that is a child node of the target node defines an OR relationship, and In the AND or AND relationship extraction means for finding the location where the target parent parent node that is the parent node of the parent node defines an AND relationship, and (c2) in the location found by the AND or AND relationship extraction means, From a target grandchild node that is a child node of the target child node, a request condition setting unit that sets a request condition for the target node, and (c3) in a place found by the AND-OR AND relationship extraction unit, As a child node of the target child node, a node having a feature of “not one of the target grandchild nodes” is added, and the target node and the added node are added A node adding means for setting an exclusion condition, and (c4) an AND relation as a child node of the target parent-parent node at the place found by the AND-OR AND relation extracting means And a target child node moving means to be added.

Therefore, the structure of the feature data given to the test data generating means can be flattened, and the processing in the test data generating means becomes easy.

(3) (4) A feature data processing apparatus according to the present invention includes nodes arranged in a plurality of hierarchies having a higher-level node indicating a target feature and a lower-level node indicating a lower-level feature of the higher-level node feature. The upper node and the lower node are combined in an AND relationship in which all of the lower nodes must be established with respect to the upper node, or an OR relationship in which one of the lower nodes is established with respect to the upper node. Feature data that defines at least one of a requirement condition that determines whether the establishment or non-establishment of one node in between determines the establishment or non-establishment of the other node, and an exclusive condition that determines the simultaneous establishment or non-establishment of both nodes At least one of the following input means, (a) and-and-level flattening means, (b) or-or-level flattening means, and (c) lifting flattening means For example, a characteristic data processing device and a flattening means for flattening the hierarchical structure of the input feature data,
(a) The AND-and-level flattening means (a1) in the feature data, the target node defines an AND relationship, the child node of the target node is set as a target child node, and the target child node has an AND relationship. And-and-relation extraction means for finding a defined part; and (a2) if a required condition or an exclusion condition is attached to the target child node at the position found by the AND-and-relation extraction means, the request A request / exclusive condition allocating means for replacing a condition or an exclusive condition with the target node; and (a3) deleting the target child node at a location found by the AND-and-relation extracting means; A target child node deleting means for adding a target grandchild node as a child node to the AND relationship as a child node of the target node;
(b) The or-or hierarchy flattening means (b1) in the feature data, the target node defines an OR relationship, a child node of the target node is a target child node, and the target child node has an OR relationship. OR-OR relationship extraction means to find out the defined place,
(b2) If an exclusion condition is attached to the target child node at a location found by the or-or relationship extraction means, an exclusion condition distribution means for replacing the exclusion condition with the target node; and (b3 ) If the request condition is attached to the target child node at the location found by the or-or-relation extracting means, the request condition is replaced with the target grandchild node that is a child node of the target child node. (B4) In the place found by the OR-OR relationship extracting means, if the target child node is attached with a request condition that the target child node is a request destination, An exclusion condition setting means for setting an exclusion condition between a child node other than the target child node and the request source node of the request condition; and (b5) the or-or relationship extracting means Thus, the found child node is deleted at the found location, and the target child node deleting means for adding the target grandchild node that is a child node of the target child node to the OR relationship as a child node of the target node is provided. And
(c) The lifting flattening means (c1) in the feature data, the target node defines an AND relationship, a target child node that is a child node of the target node defines an OR relationship, and In the AND or AND relationship extraction means for finding the location where the target parent parent node that is the parent node of the parent node defines an AND relationship, and (c2) in the location found by the AND or AND relationship extraction means, From a target grandchild node that is a child node of the target child node, a request condition setting unit that sets a request condition for the target node, and (c3) in a place found by the AND-OR AND relationship extraction unit, As a child node of the target child node, a node having a feature of “not one of the target grandchild nodes” is added, and the target node and the added node are added A node adding means for setting an exclusion condition, and (c4) an AND relation as a child node of the target parent-parent node at the place found by the AND-OR AND relation extracting means And a target child node moving means to be added.

(5) A test data generation server device according to the present invention comprises a node arranged in a plurality of hierarchies having an upper node indicating a target feature and a lower node indicating a lower feature of the upper node feature. The upper node and the lower node are combined in an AND relationship in which all of the lower nodes must be established with respect to the upper node, or an OR relationship in which one of the lower nodes is established with respect to the upper node. Feature data in which at least one of a requirement condition that determines the establishment / non-establishment of one node and the exclusive condition that determines the simultaneous establishment / non-establishment of both nodes between nodes is defined as a terminal Receiving means for receiving from the apparatus; (a) and-and-level flattening means; (b) or-or-level flattening means; and (c) lifting flattening means. A flattening unit for flattening a hierarchical structure of received feature data, a test data generating unit for generating test data based on a combination of features based on the flattened feature data, and A test data generation server device comprising a transmission means for transmitting test data to the terminal device,
(a) The AND-and-level flattening means (a1) in the feature data, the target node defines an AND relationship, the child node of the target node is set as a target child node, and the target child node has an AND relationship. And-and-relation extraction means for finding a defined part; and (a2) if a required condition or an exclusion condition is attached to the target child node at the position found by the AND-and-relation extraction means, the request A request / exclusive condition allocating means for replacing a condition or an exclusive condition with the target node; and (a3) deleting the target child node at a location found by the AND-and-relation extracting means; A target child node deleting means for adding a target grandchild node as a child node to the AND relationship as a child node of the target node;
(b) The or-or hierarchy flattening means (b1) in the feature data, the target node defines an OR relationship, a child node of the target node is a target child node, and the target child node has an OR relationship. OR or OR relationship extraction means for finding a defined location, and (b2) if an exclusion condition is attached to the target child node in the location found by the OR or OR relationship extraction means, the exclusion condition is An exclusive condition allocating means for allocating to the target node; and (b3) if a required condition is attached to the target child node at a location found by the or-or relationship extracting means, the required condition is set to the target (B4) In the location found by the or-or relationship extracting means, the target child node is assigned to the target child node at a location found by the target grandchild node that is a child node of the child node. If the request condition that the target child node is a request destination is attached, an exclusion condition that sets an exclusion condition between a child node other than the target child node in the target node and the request source node of the request condition And (b5) the target child node is deleted at a location found by the OR-OR relationship extracting unit, and the target grandchild node that is a child node of the target child node is changed to a child node of the target node. And a target child node deletion means to be added to the OR relationship as
(c) The lifting flattening means (c1) in the feature data, the target node defines an AND relationship, a target child node that is a child node of the target node defines an OR relationship, and In the AND or AND relationship extraction means for finding the location where the target parent parent node that is the parent node of the parent node defines an AND relationship, and (c2) in the location found by the AND or AND relationship extraction means, From a target grandchild node that is a child node of the target child node, a request condition setting unit that sets a request condition for the target node, and (c3) in a place found by the AND-OR AND relationship extraction unit, As a child node of the target child node, a node having a feature of “not one of the target grandchild nodes” is added, and the target node and the added node are added A node adding means for setting an exclusion condition, and (c4) an AND relation as a child node of the target parent-parent node at the place found by the AND-OR AND relation extracting means And a target child node moving means to be added.

(6) A feature data processing server device according to the present invention includes a node arranged in a plurality of hierarchies having an upper node indicating a target feature and a lower node indicating a lower feature of the upper node feature. The upper node and the lower node are combined in an AND relationship in which all of the lower nodes must be established with respect to the upper node, or an OR relationship in which one of the lower nodes is established with respect to the upper node. Feature data in which at least one of a requirement condition that determines the establishment / non-establishment of one node and the exclusive condition that determines the simultaneous establishment / non-establishment of both nodes between nodes is defined as a terminal Receiving means for receiving from the apparatus, (a) and-and-level flattening means, (b) or-or-level flattening means, and (c) lifting flattening means A feature data processing server device comprising at least one, flattening means for flattening a hierarchical structure of input feature data, and transmitting means for transmitting the flattened feature data to a terminal device. There,
(a) The AND-and-level flattening means (a1) in the feature data, the target node defines an AND relationship, the child node of the target node is set as a target child node, and the target child node has an AND relationship. And-and-relation extraction means for finding a defined part; and (a2) if a required condition or an exclusion condition is attached to the target child node at the position found by the AND-and-relation extraction means, the request A request / exclusive condition allocating means for replacing a condition or an exclusive condition with the target node; and (a3) deleting the target child node at a location found by the AND-and-relation extracting means; A target child node deleting means for adding a target grandchild node as a child node to the AND relationship as a child node of the target node;
(b) The or-or hierarchy flattening means (b1) in the feature data, the target node defines an OR relationship, a child node of the target node is a target child node, and the target child node has an OR relationship. OR or OR relationship extraction means for finding a defined location, and (b2) if an exclusion condition is attached to the target child node in the location found by the OR or OR relationship extraction means, the exclusion condition is An exclusive condition allocating means for allocating to the target node; and (b3) if a required condition is attached to the target child node at a location found by the or-or relationship extracting means, the required condition is set to the target (B4) In the location found by the or-or relationship extracting means, the target child node is assigned to the target child node at a location found by the target grandchild node that is a child node of the child node. If the request condition that the target child node is a request destination is attached, an exclusion condition that sets an exclusion condition between a child node other than the target child node in the target node and the request source node of the request condition And (b5) the target child node is deleted at a location found by the OR-OR relationship extracting unit, and the target grandchild node that is a child node of the target child node is changed to a child node of the target node. And a target child node deletion means to be added to the OR relationship as
(c) The lifting flattening means (c1) in the feature data, the target node defines an AND relationship, a target child node that is a child node of the target node defines an OR relationship, and In the AND or AND relationship extraction means for finding the location where the target parent parent node that is the parent node of the parent node defines an AND relationship, and (c2) in the location found by the AND or AND relationship extraction means, From a target grandchild node that is a child node of the target child node, a request condition setting unit that sets a request condition for the target node, and (c3) in a place found by the AND-OR AND relationship extraction unit, As a child node of the target child node, a node having a feature of “not one of the target grandchild nodes” is added, and the target node and the added node are added A node adding means for setting an exclusion condition, and (c4) an AND relation as a child node of the target parent-parent node at the place found by the AND-OR AND relation extracting means And a target child node moving means to be added.

(7) In the test data generation device according to the present invention, the flattening means includes (a) the AND-and-hierarchy flattening means, (b) the or-or-hierarchy flattening means, and (c) the lifting A flattening means, wherein the lift flattening means processes the feature data processed by the and-and-hierarchical flattening means and the or-or-hierarchical flattening means. Yes.

Therefore, it can be flattened as feature data of a three-layer structure combined by an AND relationship and an OR relationship.

(8) In the test data generation device according to the present invention, when the request source node is satisfied, the request condition is that the request destination node is also satisfied.

(9) In the test data generation device according to the present invention, the exclusion condition is characterized in that when one node is established, the other node is not established.

(10) The test data generating apparatus according to the present invention is characterized in that the AND relationship indicates that all nodes must be established.

(11) The test data generating device according to the present invention is characterized in that the OR relationship indicates that only one of the nodes is established.

(12) A feature data processing method according to the present invention is a method of processing feature data by a computer, wherein the computer includes a higher-order node indicating a target feature and a lower-order feature indicating a lower-order feature of the higher-order node. An AND relationship in which all the lower nodes must be established with respect to the upper node, and any one of the lower nodes with respect to the upper node may be established. The upper node and lower node are connected in a relationship, and the establishment condition of one node between nodes establishes the requirement for determining the establishment / non-establishment of the other node, and the simultaneous establishment / non-establishment of both nodes between nodes Input feature data that defines at least one of the exclusion conditions
The computer executes at least one of the following (a) and-and-level flattening processing, (b) or-or-level flattening processing, and (c) lifting flattening processing, and is input A feature data processing method for flattening a hierarchical structure of feature data,
(a) The AND-and-hierarchy flattening process is as follows: (a1) In the feature data, the target node defines an AND relationship, the child node of the target node is a target child node, and the target child node (A2) If a request condition or an exclusion condition is attached to the target child node, the request condition or the exclusion condition is replaced with the target node, and (a3) the target child node is deleted. A target grandchild node that is a child node of the target child node is added to the AND relationship as a child node of the target node,
(b) The or-or-layer flattening process is as follows: (b1) In the feature data, the target node defines an OR relationship, the child node of the target node is set as the target child node, and the target child node has an OR relationship. (B2) If an exclusive condition is attached to the target child node, the exclusive condition is replaced with the target node, and (b3) a required condition is attached to the target child node. For example, the request condition is replaced with a target grandchild node that is a child node of the target child node. (B4) If the target condition that the target child node is a request destination is attached to the target child node, An exclusion condition is set between the child node other than the target child node in the target node and the request source node of the request condition, and (b5) the target child node is deleted and the child node of the target child node A certain grandchild node Add to the OR relationship as a child node of the target node,
(c) In the lifting flattening process, (c1) in the feature data, the target node defines an AND relationship, and the target child node that is a child node of the target node defines an OR relationship. Find the location where the target parent-parent node that is the parent node of the parent node defines an AND relationship, and (c2) set the requirements for the target node from the target grandchild node that is a child node of the target child node (C3) As a child node of the target child node, a node having a feature of “not one of the target grandchild nodes” is added, and an exclusion condition is set between the target node and the added node (C4) The target child node is added to the AND relationship as a child node of the target parent node.

Therefore, the structure of the feature data given to the test data generation process can be flattened, and the process in test data generation becomes easy.

In this invention, “input means” corresponds to step S1.

"And-and-level flattening means" corresponds to step S2.

“Or or hierarchical leveling means” corresponds to step S3.

“The lifting flattening means” corresponds to step S4.

“Test data generation means” corresponds to step S5.

“Program” is a concept that includes not only a program that can be directly executed by the CPU but also a source-format program, a compressed program, an encrypted program, and the like.

1 is a functional block diagram of a test data generation device according to an embodiment of the present invention. FIG. It is a hardware configuration of a test data generation device. 4 is a flowchart of a test data generation program 44. It is a flowchart of flattening processing of an AND-AND hierarchy. It is a flowchart of flattening processing of an AND-AND hierarchy. It is a flowchart of the flattening process of a XOR-XOR hierarchy. It is a flowchart of the flattening process of a XOR-XOR hierarchy. It is a flowchart of the flattening process of a XOR-XOR hierarchy. It is a flowchart of the flattening process by lifting. It is a flowchart of the flattening process by lifting. It is an example of the parameter data input. The input parameter data is illustrated. It is a figure which shows replacement of the requirement conditions in an AND-AND hierarchy. It is a figure which shows the parameter data planarized by the AND-AND hierarchy planarization process. It is a figure which shows replacement of the requirement conditions in a XOR-XOR hierarchy. It is a figure which shows replacement of the requirement condition in an XOR-XOR hierarchy, and the improper exclusion condition. It is a figure which shows the parameter data planarized by the XOR-XOR hierarchy planarization process. It is a figure which shows the parameter data planarized by the lifting planarization process. It is a figure which shows the parameter data planarized by the lifting planarization process. It is a flowchart of a test data generation server apparatus. This is a standard parameter data structure in a conventional test data generation apparatus. FIG. 2 is a diagram showing a structure of standard parameter data in a conventional test data generation apparatus.

1. Overview FIG. 12 shows the logical structure of a certain event in a tree format. In this tree structure, input to a tool such as PICT is not possible.

On the other hand, the data defined for PICT shown in FIG. 21 is shown in a tree structure as shown in FIG.

Parameters a1, a2,... An are connected to a group by exclusive OR (XOR). In other words, any one of the parameters a1, a2,. Similarly, the parameters b1, b2,... Bn are coupled to the group of b by exclusive OR (XOR). Further, the parameters m1, m2,... Mn are connected to the group of m by exclusive OR (XOR).

A, b, c ... m are connected to group r by AND. That is, a, b, c... M are all in a “established” relationship.

In FIG. 22, an AND relationship is shown by adding dots to elements. Further, the XOR relationship is shown by adding an arc to the line.

The req line from parameter m1 to parameter an indicates that when parameter m1 is established, parameter an is also established. A mutex line between the parameter a2 and the parameter b2 indicates that the parameter a2 and the parameter b2 are not simultaneously established.

If the data shown in the tree structure as shown in FIG. 12 can be converted into the tree structure as shown in FIG. 22, a tool such as PICT can be used.

2. 1 is a functional block diagram showing the overall configuration of a test data generating apparatus according to an embodiment of the present invention. The input means 2 inputs parameter data 20 expressed in a logical structure.

The AND-and-layer flattening means 4 finds a portion in the logical structure of the input parameter data 20 where the AND relationship and the AND relationship are continuous as a layer from the target node. In FIG. 1, the target node is AT, and a portion where the AND relationship and the AND relationship are continuous as a hierarchy is indicated by 30.

If the request condition or the exclusion condition is added to the target child node Ta (the node corresponding to the child of the target node AT) in the portion 30, the AND-and-level flattening means 4 further sets the request condition or the exclusion condition. To the target node AT. In the example of FIG. 1, no request condition or exclusion condition is attached to the target child node Ta, so nothing is performed here. Subsequently, the AND and hierarchy leveling means 4 deletes the target child node Ta.

The AND-and-layer flattening means 4 executes the above-described processing for all the portions where the found AND relationship and the AND relationship are continuous as a layer. As a result, AND-and-level flattening parameter data 22 is obtained.

The or-or hierarchy flattening means 6 finds a portion in the logical structure of the AND-and-layer flattening parameter data 22 where the OR relationship and the OR relationship are continuous as a hierarchy from the target node. In FIG. 1, the target node is El, and a portion where the OR relationship and the OR relationship are continuous as a hierarchy is indicated by 32.

Further, if the exclusion condition is added to the target child node ISR in the part 32, the OR-or-layer flattening means 6 replaces it with the target grandchild nodes ISR1, ISR2 (child nodes of the target child node). In FIG. 1, the exclusion condition set between the target child node ISR and the node WA is replaced between each of the target grandchild nodes ISR1 and ISR2 and the node WA. Further, in the portion 32, if the required condition is attached to the target child node ISR, the required condition is replaced with the target node El. At this time, if the request condition is the target child node as a request destination, an exclusion condition is set between a child node other than the target child node and the request source node of the request condition. Subsequently, the or-or hierarchy flattening means 6 deletes the target child node ISR. *

The or-or hierarchy flattening means 6 performs the above-described processing for all the portions where the found OR relationship and the OR relationship are continuous as a hierarchy. As a result, OR-or-layer flattening parameter data 24 is obtained.

The lifting flattening means 8 finds a portion 34 in which the AND relationship and the OR relationship are continuous as a lower hierarchy from the target node Ta, and the OR relationship and the AND relationship are continued from the target node as an upper hierarchy.

In the portion 34, the lifting flattening means 8 sets a request condition for the target node Ta from the target grandchild nodes Y and N. Further, a target grandchild node YN “None of the target grandchild nodes Y and N” is added, and an exclusion condition is set between the target node Ta and the target grandchild node YN.

The lifting flattening means 8 further moves to add the target child node Pre as a child node of the target parent-parent node AT (parent node El of the target node Ta) to the AND relationship. At this time, the structure below the target child node Pre is also moved. Thereby, the lifting flattening parameter data 26 shown in FIG. 1 is obtained.

The lifting flattening parameter data 26 is a parameter having a logical structure defined by a hierarchy of an AND relationship and an XOR relationship. Therefore, the test data can be obtained by giving this to the test data generating means 10 realized by PICT or the like.

3. Hardware Configuration FIG. 2 shows a hardware configuration of the test data generation apparatus. A memory 32, a display 34, a hard disk 36, a DVD-ROM drive 38, and a keyboard / mouse 46 are connected to the CPU 30. The hard disk 36 stores an operating system 42 such as WINDOWS (trademark) and a test data generation program 44. The test data generation program 44 performs its function in cooperation with the operating system 42. The operating system 42 and the test data generation program 44 are those recorded on the DVD-ROM 40 and installed on the hard disk 36 via the DVD-ROM drive 38.

4). Processing of Test Data Generation Program FIG. 3 shows a flowchart of the test data generation program 44.

4.1 Input Process The CPU 30 inputs parameter data and records it on the hard disk 36 (step S1). The parameter data may be input from the keyboard / mouse 46 or the DVD-ROM drive 38.

Here, it is assumed that parameter data as shown in FIG. 11 is input. This is schematically shown in FIG. In this embodiment, the parameter data is input in a format as shown in FIG. However, a tree structure as shown in FIG. 12 may be displayed on the display 34 and input while editing with the keyboard / mouse 46 or the like.

This parameter data shows the possible state of input data for the activateTask program in the operating system. For example, in FIG. 12, an AND relationship is connected from a node activateTask to a node Executionlevel (execution level) and a node Task (task to be activated). This indicates that both activatelevel and Task must be established for activateTask. That is, it is shown that activateTask needs to determine both Executionlevel and Task.

Also, an XOR relationship is connected from the node execution level to the node ExTask (task execution level) and the node ISR (interrupt). This indicates that only one of ExTask and ISR must be established for Executionlevel. In other words, Executionlevel indicates that only one of ExTask and ISR needs to be determined.

Similarly, it is indicated that Task needs to determine all of TaskID (task identification code), status (task status after activation execution), and priority (execution priority). It is indicated that TaskID must be determined as either valid (valid ID) or invalid (invalid ID). It is indicated that the status should be determined as one of suspended (running), run (operation), ready (ready), and wait (wait). It is indicated that the pariority must be determined as one of high, low, and equiv.

4.2 And-and-level flattening process Next, the CPU 30 performs an and-and-level flattening process on the input parameter data (step S2). As described above, flattening is performed by finding a portion where AND relationships are continuous as a hierarchy. FIG. 4 shows details of the flattening process of the AND AND hierarchy.

CPU 30 first sets the root node activateTask as the target node (step S201). Next, it is determined whether or not a child node is defined in an AND relationship from the target node (step S202). Here, as shown in FIG. 12, a child node Executionlevel and a child node Task are defined in an AND relationship from the target node activateTask. Therefore, the CPU 30 proceeds to step S203 and sets the first child node Executionlevel as the target child node.

Subsequently, the CPU 30 determines whether a grandchild node is defined in an AND relationship from the target child node (step S204). Here, since the XOR relationship is defined and not satisfied from the target child node Execution level to the grandchild nodes Extask and ISR, the process proceeds to step S205. In step S205, it is determined whether all child nodes have been processed as target child nodes. Here, since the process for the child node Task is not yet performed, this is set as the target child node (step S206).

CPU30 judges whether the grandchild node is defined by AND relationship from an object child node (step S204). Here, grandchild node TaskID, status, and priority are defined in an AND relationship from the target child node Task. Therefore, since satisfied, it progresses to step S209.

In step S209, the CPU 30 determines whether a condition is attached to the target child node Task. Here, since no condition is attached, step S211 is executed. In step S211, the CPU 30 deletes the target child node Task and sets the grandchild node TaskID, status, and priority as child nodes of the target node activateTask. Thereby, as shown in FIG. 14, the object child node Task is deleted.

Next, the CPU 30 determines whether or not all child nodes have been processed as target child nodes (step S205). Here, since all child nodes have been processed, the process proceeds to step S207.

In step S207, the CPU 30 determines whether or not all nodes have been processed as target nodes. Here, since there is an unprocessed node, the node Executionlevel is set to the target node (step S208).

The CPU 30 determines whether or not a child node is defined in an AND relationship from the target node Executionlevel (step S202). Here, since the XOR relationship is defined and not satisfied from the target node Execution level to the child nodes Extask and ISR, the process proceeds to step S207. Since there are still unprocessed nodes, the node TaskID is set as the target node (step S208). Since the node Task has already been deleted and is in a state as shown in FIG. 14, the node TaskID is set as the target node.

CPU30 judges whether the child node is defined by AND relationship from object node TaskID (step S202). Here, since the child nodes “valid” and “invalid” are defined in the XOR relationship from the target node TaskID, and the processing is not satisfied, the process proceeds to step S208 (step S207). In step S208, the node status is set as the target node.

Again, since step S202 is not satisfied, the node priority is set as the target node (steps S202, S207, and S208).

If the above processing is repeated and all nodes are processed as target nodes, the AND-and-hierarchy flattening processing is terminated (step S207).

FIG. 14 shows the parameter data after performing the above-described AND-and-level flattening process.

In step S209, if a condition is attached to the target child node that satisfies the AND-and-hierarchy condition, the CPU 30 replaces the condition with the target node. For example, as shown in FIG. 13A, if the target condition is attached to the target child node C, the request condition is changed to the target node A as shown in FIG. 13B. The same applies not only when the target child node C is the request source as shown in FIG. 13 but also when the target child node is the request destination. Further, when an exclusion condition is attached to the target child node C, the replacement is performed in the same manner.

4.3 XOR / XOR Hierarchization Flattening Process When the AND-and-hierarchy flattening process ends as described above, the CPU 30 next executes the XOR / XOR hierarchy flattening process (FIG. 3, step S3). ). Details of the flattening process of the XOR / XOR hierarchy are shown in FIGS.

The CPU 30 first sets the root node actiavteTask as a target node in step S301 for the flattened data in FIG. Next, it is determined from this target node actiavteTask whether or not a child node is defined in an XOR relationship (step S302). Here, child nodes Executionlevel, TaskID, status, and priority are defined in an AND relationship, which is not satisfied. Accordingly, the process proceeds to step S307.

In step S307, the CPU 30 determines whether all nodes have been processed as target nodes. Here, since there is an untargeted node, the next node Executionlevel is set as the target node (step S308).

In step S302, the CPU 30 determines from the target node Executionlevel whether a child node is defined in an XOR relationship. Here, the child nodes ExTask and ISR are defined in the XOR relationship, which is satisfied. Therefore, the CPU 30 sets the child node ExTask as the target child node (step S303).

Next, the CPU 30 determines whether a grandchild node is defined in the XOR relationship from the target child node ExTask (step S304). Here, since the grandchild node Preemptive is defined in the AND relationship and is not satisfied, the process proceeds to step S305.

In step S305, the CPU 30 determines whether or not all child nodes are the target child nodes. Since the child node ISR has not yet been set as the target child node, this is set as the target child node (step S306).

The CPU 30 determines whether or not a grandchild node is defined in an XOR relationship from the target child node ISR (step S304). Here, since the grandchild nodes ISR1 and ISR2 are defined in the XOR relationship, they are satisfied. Accordingly, the process proceeds to step S309.

In step S309, it is determined whether a condition is attached to the target child node ISR. Here, since the condition is attached to the target child node ISR, the process proceeds to step S310. In step S310, the CPU 30 determines whether the condition is an exclusive condition. Here, since an exclusion condition is attached, step S311 is executed. In step S311, the exclusion condition attached to the target child node ISR is changed to the grandchild nodes ISR1 and ISR2. That is, the exclusion condition between the node priority and the target child node ISR is replaced with the exclusion condition between the node priority and the target grandchild node ISR1, and the exclusion condition between the node priority and the target grandchild node ISR2.

Next, the CPU 30 determines whether or not the condition attached to the target child node ISR is a request condition (step S312). Here, since the required condition is not attached, the process proceeds to step S317. In step S317, the CPU 30 deletes the target child node ISR and sets the grandchild nodes ISR1 and ISR2 as child nodes of the target node Executionlevel. Therefore, as shown in FIG. 17, the exclusion condition is changed and the target child node ISR is deleted.

Next, the CPU 30 determines whether or not processing has been performed for all child nodes (step S305). Here, since there is an unprocessed child node, the process from step S304 onward is executed with the child node TaskID as the target child node. Similarly, the other child nodes “status” and “priority” are also sequentially processed as target child nodes, and the processing from step S304 is executed.

When the processing for all the child nodes of the target node is completed, the next node is set as the target node (step S308), and the processing from step S302 is executed. When all nodes are processed as target nodes in this way, the XOR / XOR hierarchy flattening process is terminated (step S307).

In step S310, when an exclusion condition is attached to the target child node, the exclusion condition is changed to all the grandchild nodes of the child node. At this time, if the target condition is attached to the target child node (step S312), the CPU 30 performs the following processing.

CPU 30 determines whether or not the request source of the request condition is a child node (step S313). If so, the CPU 30 replaces the request condition from the child node with the request condition from the grandchild node of the child node (step S314).

For example, as shown in FIG. 15A, it is assumed that a request condition is set for the node E from the target child node C in a continuous portion of the XOR hierarchy. In this case, as shown in FIG. 15B, the CPU 30 sets a request condition for the node E with the request source as a grandchild node of the target child node. Thereafter, the target child node C is deleted, and the grandchild nodes F, G, and H are added to the child nodes of the target node A (step S317).

If the CPU 30 determines in step S313 that a request condition that sets the target child node as a request destination is attached, the CPU 30 proceeds to step S315. In step S315, the CPU 30 replaces the request condition attached to the target child node with the target node. Further, an exclusion condition is set for each of the child nodes of the target node (excluding the target child node) from the request source node of the request condition (step S316).

For example, as shown in FIG. 16A, it is assumed that a request condition is set from the node E for the target child node C in a continuous portion of the XOR hierarchy. In this case, the CPU 30 changes the request destination of the request condition to the target node A as shown in FIG. 16B. Further, between all of the child nodes B and C of the target node A except the target child node C (here, only the child node B) and the node E that is the request source of the request condition Set the exclusion condition. Thereafter, the target child node C is deleted, and the grandchild nodes F, G, and H are added to the child nodes of the target node A (step S317).

4.4 Flattening Process by Lifting When the flattening process of the XOR / XOR hierarchy is finished as described above, the CPU 30 next executes the flattening process by lifting (FIG. 3, step S4). That is, it is flattened to parameter data consisting of three layers defined by the AND relationship and the XOR relationship. Details of the flattening process by lifting are shown in FIGS.

First, the CPU 30 sets the first node below the third hierarchy as the target node in the flattened parameter data of FIG. 17 (step S401). Here, the node ExTask is the target node.

Next, the CPU 30 determines whether a child node is defined in an AND relationship from the target node ExTask (step S402). Here, since the child node preemptive is defined, it is satisfied, so the process proceeds to step S403. In step S403, the first child node is set as a target child node. Here, the child node preemptive is the target child node.

Next, the CPU 30 defines the structure below the target child node preemptive as an AND relationship as a child node of the parent node (parent parent node or grandparent node) activateTask of the target node ExTask (see FIG. 18).

Subsequently, a request condition is set for the target node ExTask from each of the grandchild nodes Yes and No (step S405) (hereinafter, child nodes, grandchild nodes, etc. are represented based on the state of FIG. ing). Furthermore, the CPU 30 adds a grandchild node with the content “None of other grandchild nodes” in an XOR relationship (step S406). Here, as shown in FIG. 8, a node YesNo that is neither Yes nor No is defined.

Next, the CPU 30 sets an exclusion condition between the added grandchild node YesNo and the target node ExTask (step S407). Thereby, the parameter data as shown in FIG. 18 is obtained.

Next, the CPU 30 determines whether or not all child nodes are the target child nodes (step S408). If there is a child node that has not been processed, the next child node is set as the target child node, and step S402 and subsequent steps are executed. Here, since all the child nodes have been processed, the process proceeds to step S410.

In step S410, the CPU 30 determines whether or not all nodes in the third hierarchy and below are the target nodes. If there is a node below the third hierarchy that is not the target, the next node is set as the target node (step S411). Here, since there is no node below the third hierarchy, the flattening process by lifting ends.

As described above, the flattened parameter data as shown in FIG. 18 can be obtained. This is represented in the data format as shown in FIG.

3.5 Generation of Test Data Based on Flattening Parameter Data Next, the CPU 30 performs test data generation processing based on the parameter data generated in this way (FIG. 3, step S5). In this embodiment, test data is generated based on the all-pair method.

Here, the flattened parameter data is standardized as three-layer data consisting of an AND relationship and an XOR relationship. Therefore, the test data generation process by the all-pair method is easy. In addition, a test data generation program (for example, Microsoft's PICT) based on the all-pair method or the like can be used.

Test data can be generated as described above.

5. Other embodiments
(1) In the above embodiment, test data is generated. However, the parameter data flattened by the processes in steps S2 to S4 may be output. In this case, the user can input the output parameter data to a tool such as PICT to obtain test data.

(2) In the above embodiment, the case where test data is generated by a stand-alone computer has been described. However, each of the above processes may be performed by a server device connected to the Internet or the like. A processing flowchart of the server program in the server device in this case is shown in FIG.

First, the CPU of the server device receives parameter data from the terminal device via the Internet (step S50). Subsequently, flattening of the AND-AND hierarchy (step S2), flattening of the XOR-XOR hierarchy (step S3), flattening by lifting (step S4), and generation of test data (step S5) are executed. These processes are the same as those in FIG. Subsequently, the generated test data is transmitted to the terminal device (step S51).

In this way, test data can be obtained without preparing a program in the terminal device.

Further, the flattened parameter data may be transmitted to the terminal device. In this case, the user can input this into a tool such as PICT on the terminal device side to obtain test data.

(3) In the above embodiment, processing is performed in the order of AND-AND hierarchy flattening and XOR-XOR hierarchy flattening. However, XOR-XOR hierarchy flattening may be executed prior to AND-AND hierarchy flattening.

(4) In the above embodiment, all processes of flattening by AND-AND hierarchy flattening and XOR-XOR hierarchy flattening lifting are performed. However, only the AND-AND hierarchy flattening, the XOR-XOR hierarchy flattening, or the flattening by lifting may be executed. Also, only two of these may be executed.

Claims

It is composed of nodes arranged in multiple hierarchies that have a higher-level node that indicates the target feature and a lower-level node that indicates a lower-level feature of the higher-level node. The upper node and the lower node are combined in an OR relationship that requires one of the lower nodes to be established with respect to the upper node, and the establishment / non-establishment of one node is established between the nodes. An input means for inputting feature data in which at least one of a requirement condition for determining failure and a exclusion condition for determining simultaneous establishment / failure of both nodes between nodes is defined;
It comprises at least one of the following (a) and-and-level flattening means, (b) or-or-level flattening means, and (c) lifting flattening means, and flattenes the hierarchical structure of input feature data Flattening means for
Test data generating means for generating test data based on a combination of features based on the flattened feature data;
A test data generation device comprising:
(a) The AND and hierarchy flattening means is:
(a1) In the feature data, an AND-and-extraction extracting unit that finds a location where the target node defines an AND relationship, the child node of the target node is a target child node, and the target child node defines an AND relationship; ,
(a2) Request / exclusion to replace the request condition or exclusion condition with the target node if the target child node is attached with a request condition or exclusion condition at the location found by the AND-and-relation extraction means Condition distribution means,
(a3) Deletes the target child node at the location found by the AND-and-extraction extraction means, and adds a target grandchild node that is a child node of the target child node to the AND relationship as a child node of the target node And a target child node deleting means
(b) The or-or hierarchy flattening means is
(b1) In the feature data, the target node defines an OR relationship, and a child node of the target node is set as a target child node, or or OR relationship extraction means for finding a location where the target child node defines an OR relationship; ,
(b2) If an exclusion condition is attached to the target child node at the location found by the or-or-relation extracting means, the exclusion condition is replaced with a target grandchild node that is a child node of the target child node. Exclusive condition distribution means;
(b3) If a requirement condition is attached to the target child node at a location found by the or-or-relation extraction means, a requirement condition displacing means that replaces the requirement condition with the target node;
(b4) Other than the target child node in the target node if the target child node is attached with a request condition that the target child node is a request destination in a place found by the or-or-relation extracting unit Exclusive condition setting means for setting an exclusive condition between the child node of the request and the request source node of the request condition;
(b5) Delete the target child node at the location found by the or-or relationship extracting means, and add the target grandchild node that is a child node of the target child node to the OR relationship as a child node of the target node And a target child node deleting means
(c) The lifting flattening means
(c1) In the feature data, the target node defines an AND relationship, the target child node that is a child node of the target node defines an OR relationship, and the target parent-parent node that is a parent node of the parent node of the target node AND or AND relationship extraction means to find the location where the AND relationship is defined,
(c2) A request condition setting means for setting a request condition for the target node from a target grandchild node that is a child node of the target child node at a place found by the AND or AND relation extraction means;
(c3) In a place found by the AND-or-and-relation extraction unit, a node indicating the characteristic of “not one of the target grandchild nodes” is added as a child node of the target child node, and the target node Node adding means for setting an exclusion condition between the node and the added node;
(c4) A target child node moving unit that adds the target child node to the AND relationship as a child node of the target parent-parent node at a location found by the AND-or-and-relation extraction unit. A test data generation device characterized by the above.
A test data generation program for realizing a test data generation device by a computer,
It is composed of nodes arranged in multiple hierarchies that have a higher-level node indicating the target feature and a lower-level node indicating the lower-level feature of the higher-level node, and all lower-level nodes must be established with respect to the higher-level node The upper node and the lower node are combined in an OR relationship that requires one of the lower nodes to be established with respect to the upper node, and the establishment / non-establishment of one node is established between the nodes. An input means for inputting feature data in which at least one of a requirement condition for determining failure and a exclusion condition for determining simultaneous establishment / failure of both nodes between nodes is defined;
It comprises at least one of the following (a) and-and-level flattening means, (b) or-or-level flattening means, and (c) lifting flattening means, and flattenes the hierarchical structure of input feature data Flattening means for
A test data generation program for functioning as test data generation means for generating test data based on a combination of features based on the flattened feature data,
(a) The AND and hierarchy flattening means is:
(a1) In the feature data, an AND-and-extraction extracting unit that finds a location where the target node defines an AND relationship, the child node of the target node is a target child node, and the target child node defines an AND relationship; ,
(a2) Request / exclusion to replace the request condition or exclusion condition with the target node if the target child node is attached with a request condition or exclusion condition at the location found by the AND-and-relation extraction means Condition distribution means,
(a3) Deletes the target child node at the location found by the AND-and-extraction extraction means, and adds a target grandchild node that is a child node of the target child node to the AND relationship as a child node of the target node And a target child node deleting means
(b) The or-or hierarchy flattening means is
(b1) In the feature data, the target node defines an OR relationship, and a child node of the target node is set as a target child node, or or OR relationship extraction means for finding a location where the target child node defines an OR relationship; ,
(b2) In the place found by the OR-OR relationship extraction means, if an exclusive condition is attached to the target child node, an exclusive condition distribution means for changing the exclusive condition to the target node;
(b3) If a requirement condition is attached to the target child node at the location found by the or-or-relation extracting means, the requirement condition is replaced with a target grandchild node that is a child node of the target child node. A requirement condition distribution means;
(b4) Other than the target child node in the target node if the target child node is attached with a request condition that the target child node is a request destination in a place found by the or-or-relation extracting unit Exclusive condition setting means for setting an exclusive condition between the child node of the request and the request source node of the request condition;
(b5) Delete the target child node at the location found by the or-or relationship extracting means, and add the target grandchild node that is a child node of the target child node to the OR relationship as a child node of the target node And a target child node deleting means
(c) The lifting flattening means
(c1) In the feature data, the target node defines an AND relationship, the target child node that is a child node of the target node defines an OR relationship, and the target parent-parent node that is a parent node of the parent node of the target node AND or AND relationship extraction means to find the location where the AND relationship is defined,
(c2) A request condition setting means for setting a request condition for the target node from a target grandchild node that is a child node of the target child node at a place found by the AND or AND relation extraction means;
(c3) In a place found by the AND-or-and-relation extraction unit, a node indicating the characteristic of “not one of the target grandchild nodes” is added as a child node of the target child node, and the target node Node adding means for setting an exclusion condition between the node and the added node;
(c4) A target child node moving unit that adds the target child node to the AND relationship as a child node of the target parent-parent node at a location found by the AND-or-and-relation extraction unit. Test data generation program characterized by
It is composed of nodes arranged in multiple hierarchies that have a higher-level node that indicates the target feature and a lower-level node that indicates a lower-level feature of the higher-level node. The upper node and the lower node are combined in an OR relationship that requires one of the lower nodes to be established with respect to the upper node, and the establishment / non-establishment of one node is established between the nodes. An input means for inputting feature data in which at least one of a requirement condition for determining failure and a exclusion condition for determining simultaneous establishment / failure of both nodes between nodes is defined;
It comprises at least one of the following (a) and-and-level flattening means, (b) or-or-level flattening means, and (c) lifting flattening means, and flattenes the hierarchical structure of input feature data Flattening means for
A feature data processing device comprising:
(a) The AND and hierarchy flattening means is:
(a1) In the feature data, an AND-and-extraction extracting unit that finds a location where the target node defines an AND relationship, the child node of the target node is a target child node, and the target child node defines an AND relationship; ,
(a2) Request / exclusion to replace the request condition or exclusion condition with the target node if the target child node is attached with a request condition or exclusion condition at the location found by the AND-and-relation extraction means Condition distribution means,
(a3) Deletes the target child node at the location found by the AND-and-extraction extraction means, and adds a target grandchild node that is a child node of the target child node to the AND relationship as a child node of the target node And a target child node deleting means
(b) The or-or hierarchy flattening means is
(b1) In the feature data, the target node defines an OR relationship, and a child node of the target node is set as a target child node, or or OR relationship extraction means for finding a location where the target child node defines an OR relationship; ,
(b2) In the place found by the OR-OR relationship extraction means, if an exclusive condition is attached to the target child node, an exclusive condition distribution means for changing the exclusive condition to the target node;
(b3) If a requirement condition is attached to the target child node at the location found by the or-or-relation extracting means, the requirement condition is replaced with a target grandchild node that is a child node of the target child node. A requirement condition distribution means;
(b4) Other than the target child node in the target node if the target child node is attached with a request condition that the target child node is a request destination in a place found by the or-or-relation extracting unit Exclusive condition setting means for setting an exclusive condition between the child node of the request and the request source node of the request condition;
(b5) Delete the target child node at the location found by the or-or relationship extracting means, and add the target grandchild node that is a child node of the target child node to the OR relationship as a child node of the target node And a target child node deleting means
(c) The lifting flattening means
(c1) In the feature data, the target node defines an AND relationship, the target child node that is a child node of the target node defines an OR relationship, and the target parent-parent node that is a parent node of the parent node of the target node AND or AND relationship extraction means to find the location where the AND relationship is defined,
(c2) A request condition setting means for setting a request condition for the target node from a target grandchild node that is a child node of the target child node at a place found by the AND or AND relation extraction means;
(c3) In a place found by the AND-or-and-relation extraction unit, a node indicating the characteristic of “not one of the target grandchild nodes” is added as a child node of the target child node, and the target node Node adding means for setting an exclusion condition between the node and the added node;
(c4) A target child node moving unit that adds the target child node to the AND relationship as a child node of the target parent-parent node at a location found by the AND-or-and-relation extraction unit. A feature data processing device.
A feature data processing program for realizing a feature data processing device by a computer, the computer comprising:
It is composed of nodes arranged in multiple hierarchies that have a higher-level node that indicates the target feature and a lower-level node that indicates a lower-level feature of the higher-level node. The upper node and the lower node are combined in an OR relationship that requires one of the lower nodes to be established with respect to the upper node, and the establishment / non-establishment of one node is established between the nodes. An input means for inputting feature data in which at least one of a requirement condition for determining failure and a exclusion condition for determining simultaneous establishment / failure of both nodes between nodes is defined;
It comprises at least one of the following (a) and-and-level flattening means, (b) or-or-level flattening means, and (c) lifting flattening means, and flattenes the hierarchical structure of input feature data A feature data processing program for functioning as a flattening means
(a) The AND and hierarchy flattening means is:
(a1) In the feature data, an AND-and-extraction extracting unit that finds a location where the target node defines an AND relationship, the child node of the target node is a target child node, and the target child node defines an AND relationship; ,
(a2) Request / exclusion to replace the request condition or exclusion condition with the target node if the target child node is attached with a request condition or exclusion condition at the location found by the AND-and-relation extraction means Condition distribution means,
(a3) Deletes the target child node at the location found by the AND-and-extraction extraction means, and adds a target grandchild node that is a child node of the target child node to the AND relationship as a child node of the target node And a target child node deleting means
(b) The or-or hierarchy flattening means is
(b1) In the feature data, the target node defines an OR relationship, and a child node of the target node is set as a target child node, or or OR relationship extraction means for finding a location where the target child node defines an OR relationship; ,
(b2) In the place found by the OR-OR relationship extraction means, if an exclusive condition is attached to the target child node, an exclusive condition distribution means for changing the exclusive condition to the target node;
(b3) If a requirement condition is attached to the target child node at the location found by the or-or-relation extracting means, the requirement condition is replaced with a target grandchild node that is a child node of the target child node. A requirement condition distribution means;
(b4) Other than the target child node in the target node if the target child node is attached with a request condition that the target child node is a request destination in a place found by the or-or-relation extracting unit Exclusive condition setting means for setting an exclusive condition between the child node of the request and the request source node of the request condition;
(b5) Delete the target child node at the location found by the or-or relationship extracting means, and add the target grandchild node that is a child node of the target child node to the OR relationship as a child node of the target node And a target child node deleting means
(c) The lifting flattening means
(c1) In the feature data, the target node defines an AND relationship, the target child node that is a child node of the target node defines an OR relationship, and the target parent-parent node that is a parent node of the parent node of the target node AND or AND relationship extraction means to find the location where the AND relationship is defined,
(c2) A request condition setting means for setting a request condition for the target node from a target grandchild node that is a child node of the target child node at a place found by the AND or AND relation extraction means;
(c3) In a place found by the AND-or-and-relation extraction unit, a node indicating the characteristic of “not one of the target grandchild nodes” is added as a child node of the target child node, and the target node Node adding means for setting an exclusion condition between the node and the added node;
(c4) A target child node moving unit that adds the target child node to the AND relationship as a child node of the target parent-parent node at a location found by the AND-or-and-relation extraction unit. A feature data processing program characterized by
It is composed of nodes arranged in multiple hierarchies that have a higher-level node indicating the target feature and a lower-level node indicating the lower-level feature of the higher-level node, and all lower-level nodes must be established with respect to the higher-level node The upper node and the lower node are combined in an OR relationship that requires one of the lower nodes to be established with respect to the upper node, and the establishment / non-establishment of one node is established between the nodes. Receiving means for receiving from the terminal device feature data in which at least one of a requirement condition for determining failure and an exclusive condition for determining simultaneous establishment / failure of both nodes between nodes is defined;
It comprises at least one of the following (a) and-and-level flattening means, (b) or-or-level flattening means, and (c) lifting flattening means, and flattens the hierarchical structure of received feature data Flattening means to
Test data generating means for generating test data based on a combination of features based on the flattened feature data;
Transmitting means for transmitting the generated test data to the terminal device;
A test data generation server device comprising:
(a) The AND and hierarchy flattening means is:
(a1) In the feature data, an AND-and-extraction extracting unit that finds a location where the target node defines an AND relationship, the child node of the target node is a target child node, and the target child node defines an AND relationship; ,
(a2) Request / exclusion to replace the request condition or exclusion condition with the target node if the target child node is attached with a request condition or exclusion condition at the location found by the AND-and-relation extraction means Condition distribution means,
(a3) Deletes the target child node at the location found by the AND-and-extraction extraction means, and adds a target grandchild node that is a child node of the target child node to the AND relationship as a child node of the target node And a target child node deleting means
(b) The or-or hierarchy flattening means is
(b1) In the feature data, the target node defines an OR relationship, and a child node of the target node is set as a target child node, or or OR relationship extraction means for finding a location where the target child node defines an OR relationship; ,
(b2) In the place found by the OR-OR relationship extraction means, if an exclusive condition is attached to the target child node, an exclusive condition distribution means for changing the exclusive condition to the target node;
(b3) If a requirement condition is attached to the target child node at the location found by the or-or-relation extracting means, the requirement condition is replaced with a target grandchild node that is a child node of the target child node. A requirement condition distribution means;
(b4) Other than the target child node in the target node if the target child node is attached with a request condition that the target child node is a request destination in a place found by the or-or-relation extracting unit Exclusive condition setting means for setting an exclusive condition between the child node of the request and the request source node of the request condition;
(b5) Delete the target child node at the location found by the or-or relationship extracting means, and add the target grandchild node that is a child node of the target child node to the OR relationship as a child node of the target node And a target child node deleting means
(c) The lifting flattening means
(c1) In the feature data, the target node defines an AND relationship, the target child node that is a child node of the target node defines an OR relationship, and the target parent-parent node that is a parent node of the parent node of the target node AND or AND relationship extraction means to find the location where the AND relationship is defined,
(c2) A request condition setting means for setting a request condition for the target node from a target grandchild node that is a child node of the target child node at a place found by the AND or AND relation extraction means;
(c3) In a place found by the AND-or-and-relation extraction unit, a node indicating the characteristic of “not one of the target grandchild nodes” is added as a child node of the target child node, and the target node Node adding means for setting an exclusion condition between the node and the added node;
(c4) A target child node moving unit that adds the target child node to the AND relationship as a child node of the target parent-parent node at a location found by the AND-or-and-relation extraction unit. A test data generation server device.
It is composed of nodes arranged in multiple hierarchies that have a higher-level node indicating the target feature and a lower-level node indicating the lower-level feature of the higher-level node, and all lower-level nodes must be established with respect to the higher-level node The upper node and the lower node are combined in an OR relationship that requires one of the lower nodes to be established with respect to the upper node, and the establishment / non-establishment of one node is established between the nodes. Receiving means for receiving from the terminal device feature data in which at least one of a requirement condition for determining failure and an exclusive condition for determining simultaneous establishment / failure of both nodes between nodes is defined;
It comprises at least one of the following (a) and-and-level flattening means, (b) or-or-level flattening means, and (c) lifting flattening means, and flattenes the hierarchical structure of input feature data Flattening means for
Transmitting means for transmitting the flattened feature data to a terminal device;
A feature data processing server device comprising:
(a) The AND and hierarchy flattening means is:
(a1) In the feature data, an AND-and-extraction extracting unit that finds a location where the target node defines an AND relationship, the child node of the target node is a target child node, and the target child node defines an AND relationship; ,
(a2) Request / exclusion to replace the request condition or exclusion condition with the target node if the target child node is attached with a request condition or exclusion condition at the location found by the AND-and-relation extraction means Condition distribution means,
(a3) Deletes the target child node at the location found by the AND-and-extraction extraction means, and adds a target grandchild node that is a child node of the target child node to the AND relationship as a child node of the target node And a target child node deleting means
(b) The or-or hierarchy flattening means is
(b1) In the feature data, the target node defines an OR relationship, and a child node of the target node is set as a target child node, or or OR relationship extraction means for finding a location where the target child node defines an OR relationship; ,
(b2) In the place found by the OR-OR relationship extraction means, if an exclusive condition is attached to the target child node, an exclusive condition distribution means for changing the exclusive condition to the target node;
(b3) If a requirement condition is attached to the target child node at the location found by the or-or-relation extracting means, the requirement condition is replaced with a target grandchild node that is a child node of the target child node. A requirement condition distribution means;
(b4) Other than the target child node in the target node if the target child node is attached with a request condition that the target child node is a request destination in a place found by the or-or-relation extracting unit Exclusive condition setting means for setting an exclusive condition between the child node of the request and the request source node of the request condition;
(b5) Delete the target child node at the location found by the or-or relationship extracting means, and add the target grandchild node that is a child node of the target child node to the OR relationship as a child node of the target node And a target child node deleting means
(c) The lifting flattening means
(c1) In the feature data, the target node defines an AND relationship, the target child node that is a child node of the target node defines an OR relationship, and the target parent-parent node that is a parent node of the parent node of the target node AND or AND relationship extraction means to find the location where the AND relationship is defined,
(c2) A request condition setting means for setting a request condition for the target node from a target grandchild node that is a child node of the target child node at a place found by the AND or AND relation extraction means;
(c3) In a place found by the AND-or-and-relation extraction unit, a node indicating the characteristic of “not one of the target grandchild nodes” is added as a child node of the target child node, and the target node Node adding means for setting an exclusion condition between the node and the added node;
(c4) A target child node moving unit that adds the target child node to the AND relationship as a child node of the target parent-parent node at a location found by the AND-or-and-relation extraction unit. A feature data processing server device.
The apparatus or program according to any one of claims 1 to 6,
The flattening means comprises (a) the AND-and-hierarchy flattening means, (b) the or-or-hierarchy flattening means, and (c) the lifting flattening means, and the AND-and-hierarchy An apparatus or a program characterized in that the lifting flattening means processes the characteristic data processed by the flattening means and the or-or-hierarchical flattening means.
The apparatus or program according to any one of claims 1 to 7,
The apparatus or program according to claim 1, wherein the request condition defines that the request destination node is also established when the request source node is established.
The apparatus or program according to any one of claims 1 to 8,
The exclusion condition defines that when one node is established, the other node is not established.
The apparatus or program according to any one of claims 1 to 9,
The AND relationship indicates that all nodes must be established, or a device or program.
The apparatus or program according to any one of claims 1 to 10,
The OR relationship indicates that only one of the nodes is established.
A method of processing feature data by a computer,
The computer is configured to include a node arranged in a plurality of hierarchies having a higher-level node indicating a target feature and a lower-level node indicating a lower-level feature of the higher-level node feature. The upper node and the lower node are combined in an AND relationship that all must be satisfied, or an OR relationship in which one of the lower nodes is satisfied with respect to the upper node, and the establishment / non-establishment of one node between the other nodes Input feature data defining at least one of a requirement condition for determining the establishment / non-establishment of a node and an exclusive condition for determining the simultaneous establishment / non-establishment of both nodes between nodes,
The computer executes at least one of the following (a) and-and-level flattening processing, (b) or-or-level flattening processing, and (c) lifting flattening processing, and is input A feature data processing method for flattening a hierarchical structure of feature data,
(a) The AND and hierarchy flattening process
(a1) In the feature data, the target node defines an AND relationship, the child node of the target node is a target child node, and a location where the target child node defines an AND relationship is found,
(a2) If a request condition or an exclusion condition is attached to the target child node, the request condition or the exclusion condition is changed to the target node,
(a3) deleting the target child node, adding a target grandchild node that is a child node of the target child node to the AND relationship as a child node of the target node;
(b) The or-or hierarchy flattening process is
(b1) In the feature data, the target node defines an OR relationship, the child node of the target node is defined as a target child node, and the location where the target child node defines the OR relationship is found.
(b2) If an exclusion condition is attached to the target child node, the exclusion condition is replaced with the target node,
(b3) If a request condition is attached to the target child node, the request condition is replaced with a target grandchild node that is a child node of the target child node,
(b4) If the target child node has a request condition for which the target child node is a request destination, a child node other than the target child node in the target node and a request source node of the request condition In between, set exclusion conditions
(b5) Delete the target child node, add a target grandchild node that is a child node of the target child node to the OR relationship as a child node of the target node,
(c) The lifting flattening process
(c1) In the feature data, the target node defines an AND relationship, the target child node that is a child node of the target node defines an OR relationship, and the target parent-parent node that is a parent node of the parent node of the target node Finds a place that defines AND relationship,
(c2) From a target grandchild node that is a child node of the target child node, a request condition is set for the target node,
(c3) As a child node of the target child node, a node having a feature of “not one of the target grandchild nodes” is added, and an exclusion condition is set between the target node and the added node. ,
(c4) A feature data processing method, wherein the target child node is added to an AND relationship as a child node of the target parent-parent node.