JP2009026078A - Pattern definition generating program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To generates a pattern definition to identify a function installed to an application system. <P>SOLUTION: In this pattern definition generation device 100, a function name determination part 162 determines a function name based on log data 151, and a pattern definition generation part 163 generates a use history storage table 153 based on the log data 151 and the function name. Based on the use history memory table 153, the pattern definition generation part 163 extracts minimum items necessary to identify a function name from a combination of values of parameters corresponding to the function name, and generates a pattern definition table wherein the extracted items and the function name are associated with each other. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a pattern definition generation program for generating a pattern definition table for specifying an application function.

  In recent years, due to diversification of needs by users, Web (World Wide Web) application systems have various functions and provide various services according to user requests. The administrator of the Web application system has to check the usage status of the functions provided in the Web application system in order to evaluate the service provided to the user.

  When examining the usage status of functions provided in a Web application system, a method is known that uses the result of analyzing the access log information of a Web server and measuring the access frequency of a specific URL (Uniform Resource Locator). (For example, refer to Patent Document 1).

JP 2000-293423 A

  However, the function is not uniquely determined by the URL, and in the Web application system that provides a different function depending on the parameter even if the URL is the same, there is a problem in that the usage status of the function cannot be determined by the conventional method described above. .

  It is also possible for the system administrator to create a table in which URLs and combinations of various parameters are associated with functions, and to determine the usage status of functions using such tables. However, the types of parameters are enormous. For this reason, manually creating such a table has not been practical.

  That is, a pattern definition for specifying a function by extracting a combination of parameters such as a URL from access log information can be created so that the usage status of the function provided in the Web application system can be acquired and aggregated. This is an extremely important issue.

  The present invention has been made to solve the above-described problems caused by the prior art, and is capable of creating a pattern definition that can create a pattern definition for specifying a function by extracting a combination of URL and parameters from access log information. The purpose is to provide a program.

  In order to solve the above-described problems and achieve the object, the present invention provides a computer that can access a storage device and a plurality of parameters that are left as a history when an application having a plurality of functions is accessed. An access log storage procedure for storing the included access log in a storage device, a function name determination procedure for determining a function name corresponding to the function of the application from a character string included in a parameter item of the access log, and the function name A table generation procedure for extracting a minimum item necessary for specifying the function name from a combination of parameter items corresponding to the item, and generating a pattern definition table in which the extracted item is associated with the function name; , Is executed.

  Further, the present invention is the above invention, wherein the storage device stores dictionary data including a plurality of words that are candidates for the function name, and the function name determination procedure is stored in the storage device. The function name is determined based on a matching rate between a word / phrase included in the dictionary data and a character string included in the parameter item of the access log stored in the storage device.

  Further, the present invention is the above invention, wherein the character string for which the function name is determined is stored in association with the tag of the page source of the access log, and the function name determination procedure includes the match rate and the match rate. The function name is determined based on the priority of the tag.

  According to the present invention, an access log including a plurality of parameters remaining as a history when an application having a plurality of functions is accessed is stored in the storage device, and is included in the parameter item of the access log. The function name corresponding to the application function is determined from the character string. Then, the minimum items necessary for specifying the function name are extracted from the combination of the parameter items corresponding to the determined function name, and a pattern definition table in which the extracted item is associated with the function name is generated. Therefore, by using such a pattern definition table, it is possible to acquire and aggregate the usage status of the functions of the Web application.

  Further, according to the present invention, the storage device stores dictionary data including a plurality of words that are candidate function names, and compares the words included in the dictionary data with the character string of the parameter. Since the function name is determined based on the matching rate between the word / phrase included in the dictionary data and the parameter character string, the function name can be determined appropriately.

  Further, according to the present invention, the character string for which the function name is determined is stored in association with the tag of the page source of the access log, and the matching rate between the word / phrase included in the dictionary data and the parameter character string Since the function name is determined based on the priority of the tag, the function name can be appropriately determined.

  Exemplary embodiments of a pattern definition generation program according to the present invention will be explained below in detail with reference to the accompanying drawings.

  First, an outline and features of the pattern definition generation apparatus according to the first embodiment will be described. The pattern definition generation apparatus according to the first embodiment includes a plurality of parameters (URL, session parameter, page source, etc.) that are retained as a history when a client accesses a Web application having a plurality of functions. The access log is stored, and the function name corresponding to the function of the Web application is determined from the character string included in the parameter item of the access log.

  Then, the pattern definition generation device extracts the minimum items necessary for specifying the function name from the parameter item combination corresponding to the function name, and associates the extracted item with the function name. Generate a table.

  As described above, the pattern definition generation apparatus according to the first embodiment extracts the minimum items necessary for specifying the function name, and generates a pattern definition table in which the extracted items are associated with the function names. Therefore, by using such a pattern definition table, it is possible to acquire and aggregate the usage status of the functions of the Web application.

  Next, the configuration of the pattern definition generation device 100 according to the first embodiment will be described. FIG. 1 is a functional block diagram of the configuration of the pattern definition generation device 100 according to the first embodiment. As shown in the figure, the pattern definition generation device 100 is connected to a Web application system 50, and includes an input unit 110, an output unit 120, an input / output control IF unit 130, a communication control IF unit 140, and a storage unit. 150 and a control unit 160.

  Here, the Web application system 50 has various functions for providing various services, and provides a service corresponding to the access request when an access request from a client (not shown) is acquired via the network. It is a device to do. In addition, the Web application system 50 accumulates log data that is a history of accesses performed with the client, and outputs the log data to the pattern definition generation apparatus 100.

  Turning to the description of the pattern definition generating apparatus 100, the input unit 110 is an input unit for inputting various types of information, and includes a keyboard, a mouse, a microphone, and the like. A monitor (output unit 120), which will be described later, also realizes a pointing device function in cooperation with the mouse. The output unit 120 is an output unit that outputs various types of information, and includes a monitor (or display, touch panel), a speaker, and the like.

  The input / output control IF unit 130 is means for controlling input / output of data by the input unit 110, the output unit 120, the communication control IF unit 140, the storage unit 150, and the control unit 160. The communication control IF unit 140 is means for controlling communication with the Web application 50.

  The storage unit 150 is a unit (storage unit) that stores data and programs necessary for various processes performed by the control unit 160. In particular, as shown in FIG. 1, the log data 151 is closely related to the present invention. A synonym dictionary data 152, a usage history storage table 153, and a pattern definition table 154.

  The log data 151 is log data that becomes a history when the client accesses the Web application 50. FIG. 2 is a diagram illustrating an example of a data structure of the log data 151 according to the first embodiment. As shown in the figure, the log data 151 includes identification information for identifying each log, a caller URL (REF_URL), a called URL (CALL_URL), a session parameter, a page source, and a client access. And a request time indicating the received time.

  Here, the caller URL corresponds to, for example, the URL of the top page of the Web site provided by the Web application system 50, and the called URL corresponds to the URL of the page generated from the top page.

  The session parameter is a parameter indicating the ID or password of the client that has accessed the site, and the page source is the page source of the site provided by the Web application system 50.

  The synonym dictionary data 152 is data used when determining the function name of the function provided in the Web application system 50, and includes various phrases. FIG. 3 is a diagram illustrating an example of the data structure of the synonym dictionary data 152 according to the first embodiment.

  The use history storage table 153 is a table that stores function names and parameter items corresponding to the function names in association with each other. FIG. 4 is a diagram illustrating an example of a data structure of the usage history storage table 153 according to the first embodiment.

  As shown in FIG. 4, the usage history storage table 153 includes a function name, a URL, a mode, an initialization, a user ID, and a path. Here, data included in each parameter of the log data 151 is registered in the items of URL, mode, initialization, and user ID. A method of creating the usage history storage table 153 will be described later.

  The pattern definition table 154 is a table in which function names are associated with items that are necessary to specify the function name. FIG. 5 is a diagram illustrating an example of the data structure of the pattern definition table 154 according to the first embodiment.

  As shown in FIG. 5, the pattern definition table 154 includes a function name, a URL, a mode, an initialization, a user ID, and a path. Here, among the items of URL, mode, initialization, and user ID, only the items that are at least necessary for specifying the function name are registered.

  For example, in the first row of FIG. 5, the parameter items that are at least necessary to specify the function name “create new deposit” are URL “http: //local/ap002.aspx” and mode “new”. It shows that it becomes. A method for creating the pattern definition table 154 will be described later.

  The control unit 160 has an internal memory for storing programs and control data that define various processing procedures, and is a control means for executing various processes by these, and is particularly closely related to the present invention. 1 includes a log data management unit 161, a function name determination unit 162, and a pattern definition generation unit 163.

  The log data management unit 161 is means for managing the log data 151 stored in the storage unit 150. When the log data management unit 161 acquires log data from the Web application system 50, the log data management unit 161 updates the log data 151 with the acquired log data.

  The function name determination unit 162 is a means for determining the function name based on the matching rate between the character string included in the log data 151 and the word / phrase included in the synonym dictionary data 152. Hereinafter, the process of the function name determination unit 162 will be specifically described.

  First, the function name determination unit 162 refers to the page source of the log data 151 and generates function name candidate data in which a character string sandwiched between tags of the page source is associated with the tag. FIG. 6 is a diagram illustrating an example of the data structure of the function name candidate data according to the first embodiment.

  As shown in FIG. 6, the function name candidate data stores a tag and a character string sandwiched between the tags in association with each other. Also, priority is set for each tag, and it is assumed that the higher priority tag is located in the upper part of the function name candidate data.

  The function name determination unit 162 compares the candidate character string of the function name candidate data with the synonym dictionary data 152 to obtain the matching rate. For example, “Create new deposit” is composed of the words “deposit”, “new”, and “create”, and two of these three phrases are included in the synonym dictionary data 152. The matching rate is “2/3”.

  The function name determination unit 162 determines the candidate character string having the highest matching rate among the candidate character strings as the function name. When there are a plurality of character strings having the same match rate, the character string sandwiched between the tags having the highest priority is determined as the function name. For example, if the match rate between the candidate character strings “create new deposit” and “create new” is the same, “create new deposit” with a higher tag priority is used as the function name.

  Then, the function name determination unit 162 outputs the function name extraction data in which the determined function name is associated with the identification information of the log data 151 from which the function name is determined, to the pattern definition generation unit 163. FIG. 7 is a diagram of an example of function name extraction data according to the first embodiment. As shown in the figure, the function name extraction data stores identification information for identifying log data and a function name corresponding to the log data in association with each other.

  Returning to the description of FIG. 1, the pattern definition generation unit 163 is means for generating the pattern definition table 154. Hereinafter, the process performed by the pattern definition generation unit 163 will be specifically described. First, the pattern definition generation unit 163 generates a use history storage table 153 in which a function name and a parameter item corresponding to the function name are associated with each other based on the function name extraction data and the log data 151.

  For example, when the pattern definition generating unit 163 associates the function name “create new deposit” with the parameter item corresponding to the function name, the identification information “1001” of the function name “create new deposit” in the function name extraction data. Are extracted from the log data corresponding to “(1st row in FIG. 2)” and registered in the usage history storage table 153.

  For example, in the usage history storage table 153, the URL “http: //local/ap002.aspx” for which the log data 151 is called is registered in the URL corresponding to the function name “create new deposit”. The mode “new” of the called URL is registered, “TRUE” included in the called URL is registered for initialization, the user ID “user1” of the session parameter is registered for the user ID, and the path Is registered with the session parameter path “user1pass”. The pattern definition generation unit 163 registers each parameter item for other function names in the same manner as described above.

  The pattern definition generation unit 163 generates the pattern definition table 154 based on the usage history storage table 153 after generating the usage history storage table 153. Hereinafter, a specific process in which the pattern definition generation unit 163 generates the pattern definition table 154 will be described. Here, for convenience of explanation, the pattern definition generation unit 163 will be described using the use history storage table 153 shown in FIG. FIG. 8 is a diagram illustrating an example of a usage history storage table for explaining the processing of the pattern definition generation unit 163.

  First, the pattern definition generation unit 163 refers to the function name in the usage history storage table 153 and extracts all rows with a specific function name. In the example illustrated in FIG. 8, the pattern definition generation unit 163 takes out a row (from the first level to the fifth level) corresponding to “customer reference”.

  The pattern definition generation unit 163 selects one parameter from the extracted rows, and if there are a plurality of types of values in the selected parameters, extracts all the rows corresponding to the one value. For example, in FIG. 8, when the parameter “URL” is selected, the URL has a plurality of values “http: //local/ms001.aspx” and “http: //remote/mstv001.aspx”. A row corresponding to one value, for example, “http: //local/ms001.aspx”, that is, the first row to the third row is taken out.

  Then, the pattern definition generation unit 163 has one parameter other than the “URL” included in the extracted line (in the example illustrated in FIG. 8, the mode “ref” is the corresponding value). ) And a URL are generated as a pattern. Other parameters include multiple values (parameter "initialization" includes "TRUE", "FALSE", parameter "user ID" includes "user1," "user2," "user3", parameter "path ”Includes“ user1pass ”,“ user2pass ”,“ user3pass ”), so the combination of URL“ http: //local/ms001.aspx ”and mode“ ref ”identifies the function name“ customer reference ” Pattern.

  On the other hand, the pattern definition generation unit 163 takes out the line corresponding to “http: //remote/mstv001.aspx”, that is, the 4th to 5th rows, and uses the same method as described above, the URL “http: The combination of //remote/mstv001.aspx ”, mode“ ref ”and initialization“ TRUE ”is a pattern for identifying the function name“ customer reference ”.

  The pattern definition generation unit 163 registers the generated pattern in the pattern definition table. FIG. 9 is a diagram showing an example of a pattern definition table generated from the usage history storage table shown in FIG. As shown in the figure, the minimum combination of items required for specifying the function name “customer reference” is a combination pattern of URL “http: //local/ms001.aspx” and mode “ref” And a combination pattern of URL “http: //remote/mstv001.aspx”, mode “ref”, and initialization “TRUE”.

  Next, a processing procedure of the pattern definition generation device 100 according to the first embodiment will be described. FIG. 10 is a flowchart of a process procedure of the pattern definition generation device 100 according to the first embodiment. As shown in the figure, in the pattern definition generation device 100, the pattern definition generation unit 163 refers to the use history storage table 153 and extracts a line with a specific function name (the function name line is set as group A). (Step S101), one parameter is extracted from the group A (the parameter is set to p1) (step S102).

  Then, the pattern definition generation apparatus 100 determines whether or not the value of p1 is two or more types (step S103), and if it is less than two types (step S104, No), the process proceeds to step S102.

  On the other hand, when there are two or more values of p1 (step S104, Yes), pattern addition analysis processing is executed (step S105), and it is determined whether or not parameters other than p1 exist in the A group (step S105). Step S106).

  If a parameter other than p1 exists in the A group (step S107, Yes), the process proceeds to step S102. On the other hand, if there is no parameter other than p1 in the group A (step S107, No), a pattern including one type of parameter value is used (step S108), and there is an unprocessed function name. It is determined whether or not (step S109).

  If an unprocessed function name exists (step S110, Yes), an unprocessed function name line is extracted (step S111), and the process proceeds to step S102. On the other hand, when there is no unprocessed function name (step S110, No), the process is terminated.

  Here, the process procedure of the pattern addition analysis process shown in step S105 of FIG. 10 will be described. 11 and 12 are flowcharts showing the pattern addition analysis process. As shown in the figure, the pattern definition generation unit 163 selects one value from p1 (value is α) (step S201), and extracts all rows where the value of p1 is α (extracted rows). (Group S) (Step S202).

  Then, the pattern definition generation unit 163 selects a parameter other than p1 (the parameter is set to p2) (step S203), determines whether the value of p2 is one type (step S204), and the value of p2 is 1. When it is not a type (step S205, No), it transfers to step S203.

  On the other hand, when the value of p2 is one type (the value of p2 is β) (step S205, Yes), the pattern is determined from the value of p1 (α) and the value of p2 (β) (pattern is r1). (Step S206), all the rows that match r1 are extracted from the usage history storage table 153 (the extracted rows are set as group D) (Step S207).

  The pattern definition generation unit 163 selects a parameter not used for r1 from the D group (the parameter is set to p3) (step S208), and determines whether or not the value of p3 is one type (step S209). When the value of p3 is not one type (No at Step S210), the process proceeds to Step S208.

  On the other hand, when the value of p3 is one type (the value of p3 is γ) (step S210, Yes), r1 and γ are combined into a pattern (pattern is set to r1) (step S211), D It is determined whether a parameter other than p3 exists in the group (step S212).

  When a parameter other than p3 exists in the D group (step S213, Yes), the process proceeds to step S207. On the other hand, if there is no parameter other than p3 in group D (step S213, No), the pattern (r1) is registered in the pattern definition table 154 (step S214), and there is an unselected parameter in group C. Is determined (step S215).

  If there is an unselected parameter in the C group (step S216, Yes), the process proceeds to step S203. On the other hand, if there is no unselected parameter in group C (No in step S216), it is determined whether there is an unselected value in p1 (step S217).

  If there is an unselected value in p1 (step S218, Yes), the process proceeds to step S201. On the other hand, when there is no unselected value for p1 (step S218, No), the pattern addition analysis process is terminated.

  As described above, the pattern definition generation unit 163 extracts the minimum items for specifying the function name (the function of the Web application system 50) based on the use history storage table 153, and extracts the extracted item, the function name, and the like. Since the pattern definition table 154 in which the URL is associated is created, the function can be specified even when the URL and the function are not one-to-one by using the pattern definition table 154.

  As described above, in the pattern definition generation device 100 according to the first embodiment, the function name determination unit 162 determines the function name based on the log data 151, and the pattern definition generation unit 163 determines the log data 151 and the function name. Based on the above, the usage history storage table 153 is created, and based on the usage history storage table 153, the minimum items necessary for specifying the function name are extracted from the combination of parameter values corresponding to the function name Then, since the pattern definition table 154 in which the extracted item and the function name are associated with each other is generated, the usage status of the function of the Web application system 50 can be acquired and aggregated by using the pattern definition table 154. can do. In addition, since the pattern definition generation device 100 automatically generates the pattern definition table 154, the burden on the administrator can be reduced.

  Although the embodiments of the present invention have been described so far, the present invention may be implemented in various different forms other than the first embodiment described above. Therefore, another embodiment included in the present invention will be described below as a second embodiment.

(1) Usage Example of Pattern Definition Table Various processes can be performed using the pattern definition table 154 generated by the pattern definition generation apparatus 100 according to the first embodiment. For example, the Web application system 50 can hold the pattern definition table 154 in advance, and compare the pattern definition table 154 with the log data 151 to determine the function usage status.

  Further, the web application system 50 compares the access log with the pattern definition table 154 to identify a function used when performing a specific business process and determine a related function among a plurality of functions. Can do. In addition, authentication information in which a specific function is associated with a user who can use such a function and a usage time is stored, and after specifying the function in the pattern definition table, the user who performed the access, the usage time, and the authentication information By comparing with, unauthorized use can be prevented.

(2) System configuration, etc. Of the processes described in this embodiment, all or part of the processes described as being automatically performed can be performed manually, or can be performed manually. All or part of the described processing can be automatically performed by a known method. In addition, the processing procedure, control procedure, specific name, and information including various data and parameters shown in the above-described document and drawings can be arbitrarily changed unless otherwise specified.

  Each component of the illustrated devices is functionally conceptual and does not necessarily need to be physically configured as illustrated. That is, the specific form of distribution / integration of each device is not limited to the illustrated one, and for example, the Web application system 50 and the pattern definition generation device 100 may be integrated. Further, all or a part of each processing function performed in each device may be realized by a CPU and a program that is analyzed and executed by the CPU, or may be realized as hardware by wired logic.

  FIG. 13 is a diagram illustrating a hardware configuration of a computer included in the pattern definition generation device 100 illustrated in FIG. The computer 30 includes an input device 31 that receives data input from a user, a monitor 32, a RAM (Random Access Memory) 33, a ROM (Read Only Memory) 34, a medium reading device 35 that reads data from a storage medium, a communication IF 36, A central processing unit (CPU) 37 and a hard disk drive (HDD) 38 are connected by a bus 39.

  The HDD 38 stores a pattern definition processing program 38b that exhibits the same function as the function of the pattern definition generation apparatus 100 described above. Then, when the CPU 37 reads the pattern definition processing program 38b from the HDD 38 and executes it, the pattern definition processing process 37a that realizes the function of the functional unit of the pattern definition generation apparatus 100 described above is activated. The pattern definition processing process 37a corresponds to the log data management unit 161, the function name determination unit 162, and the pattern definition generation unit 163 shown in FIG.

  The HDD 38 stores various data 38a corresponding to the data stored in the storage unit 150 of the pattern definition generation apparatus 100 described above. The various data 38a corresponds to the log data 151, the synonym dictionary data 152, the usage history storage table 153, and the pattern definition table 154 shown in FIG.

  The CPU 37 stores various data 38 a in the HDD 38, reads the various data 38 a from the HDD 38, stores the data 38 a in the RAM 33, and performs a pattern definition table generation process using the various data 33 a stored in the RAM 33.

(Appendix 1) To a computer that can access a storage device,
An access log storage procedure for storing, in the storage device, an access log including a plurality of parameters that are retained as a history when an application having a plurality of functions is accessed;
A function name determination procedure for determining a function name corresponding to the function of the application from a character string included in the parameter item of the access log;
A table that extracts a minimum item necessary for specifying the function name from a combination of parameter items corresponding to the function name, and generates a pattern definition table in which the extracted item is associated with the function name Generation procedure,
Pattern definition generation program to execute

(Supplementary Note 2) The storage device stores dictionary data including a plurality of words and phrases that are candidates for the function name, and the function name determination procedure includes words and phrases included in the dictionary data stored in the storage device. 2. The pattern definition generation program according to claim 1, wherein the function name is determined based on a match rate between the character string included in the parameter item of the access log stored in the storage device.

(Supplementary note 3) The character string to be determined for the function name is stored in association with the tag of the page source of the access log, and the function name determination procedure is based on the match rate and the priority of the tag. The pattern definition generation program according to appendix 2, wherein the function name is determined based on the function name.

(Additional remark 4) The said table production | generation procedure selects the item from which the type of the said item is single among the parameter items corresponding to the said function name, and matches a selected item and the said function name, and pattern definition The pattern definition generation program according to any one of appendices 1 to 3, wherein a table is generated.

(Supplementary Note 5) An access log storage step of storing in the storage device an access log including a plurality of parameters remaining as a history when an application having a plurality of functions is accessed;
A function name determination step of determining a function name corresponding to the function of the application from a character string included in the parameter item of the access log;
A table that extracts a minimum item necessary for specifying the function name from a combination of parameter items corresponding to the function name, and generates a pattern definition table in which the extracted item is associated with the function name Generation process;
A pattern definition generating method characterized by including

(Supplementary Note 6) The storage device stores dictionary data including a plurality of words that are candidates for the function name, and the function name determination step includes words and phrases included in the dictionary data stored in the storage device. The pattern definition generation method according to appendix 5, wherein the function name is determined based on a matching rate with a character string included in the parameter item of the access log stored in the storage device.

(Supplementary note 7) The character string to be determined for the function name is stored in association with the tag of the page source of the access log, and the function name determination step determines the match rate and the priority of the tag. The pattern definition generation method according to appendix 6, wherein the function name is determined based on the function name.

(Additional remark 8) The said table production | generation process selects the item from which the type of the said item is single among the parameter items corresponding to the said function name, and matches a selected item and the said function name, and pattern definition The pattern definition generation method according to any one of appendices 5 to 7, wherein a table is generated.

(Supplementary Note 9) An access log storage unit that stores an access log including a plurality of parameters that are left as a history when an application having a plurality of functions is accessed;
A function name determination means for determining a function name corresponding to the function of the application from a character string included in the parameter item of the access log;
A table that extracts a minimum item necessary for specifying the function name from a combination of parameter items corresponding to the function name, and generates a pattern definition table in which the extracted item is associated with the function name Generating means;
A pattern definition generating apparatus comprising:

(Supplementary Note 10) The access log storage unit stores dictionary data including a plurality of words and phrases that are candidates for the function name, and the function name determination unit includes words and phrases included in the dictionary data and the parameters of the access log. The pattern definition generation device according to appendix 9, wherein the function name is determined based on a matching rate with a character string included in the item.

(Additional remark 11) The character string used as the determination target of the function name is stored in association with the tag of the page source of the access log, and the function name determination means determines the match rate and the priority of the tag. The pattern definition generation device according to attachment 10, wherein the function name is determined based on the function name.

(Additional remark 12) The said table production | generation means selects the item from which the kind of the said item is single among the items of the parameter corresponding to the said function name, A pattern definition is matched with the selected item and the said function name The pattern definition generation device according to any one of appendices 9 to 11, wherein the table is generated.

  As described above, the pattern definition generation program according to the present invention is useful for an application system having a plurality of functions, and is particularly suitable for examining the usage status of each function.

1 is a functional block diagram illustrating a configuration of a pattern definition generation device according to a first embodiment; FIG. 3 is a diagram illustrating an example of a data structure of log data according to the first embodiment. It is a figure which shows an example of the data structure of the synonym dictionary data concerning the present Example 1. It is a figure which shows an example of the data structure of the use log | history storage table concerning the present Example 1. FIG. It is a figure which shows an example of the data structure of the pattern definition table concerning the present Example 1. FIG. It is a figure which shows an example of the data structure of the function name candidate data concerning the present Example 1. FIG. It is a figure which shows an example of the function name extraction data concerning the present Example 1. FIG. It is a figure which shows an example of the use log | history storage table for demonstrating the process of a pattern definition production | generation part. It is a figure which shows an example of the pattern definition table produced | generated from the use log | history storage table shown in FIG. 3 is a flowchart illustrating a processing procedure of the pattern definition generation device according to the first embodiment. It is a flowchart (1) which shows a pattern addition analysis process. It is a flowchart (2) which shows a pattern addition analysis process. It is a figure which shows the hardware constitutions of the computer with which the pattern definition production | generation apparatus shown in FIG. 1 is provided.

Explanation of symbols

30 Computer 31 Input Device 32 Monitor 33 RAM
33a Various data 38a Various data 34 ROM
35 Media reader 36 Communication IF
37 CPU
37a Pattern definition processing process 38 Pattern definition program 50 Web application system 100 Pattern definition generation device 110 Input unit 120 Output unit 130 Input / output control IF unit 140 Communication control IF unit 150 Storage unit 151 Log data 152 Synonym dictionary data 153 Usage history storage table 154 Pattern Definition Table 160 Control Unit 161 Log Data Management Unit 162 Function Name Determination Unit 163 Pattern Definition Generation Unit

Claims (3)

To a computer that can access the storage device,
An access log storage procedure for storing, in the storage device, an access log including a plurality of parameters that are retained as a history when an application having a plurality of functions is accessed;
A function name determination procedure for determining a function name corresponding to the function of the application from a character string included in the parameter item of the access log;
A table that extracts a minimum item necessary for specifying the function name from a combination of parameter items corresponding to the function name, and generates a pattern definition table in which the extracted item is associated with the function name Generation procedure,
Pattern definition generation program to execute   The storage device stores dictionary data including a plurality of words that are candidates for the function name, and the function name determination procedure includes words and phrases included in the dictionary data stored in the storage device. The pattern definition generation program according to claim 1, wherein the function name is determined based on a matching rate with a character string included in the parameter item of the access log stored in the function log.   The character string for which the function name is determined is stored in association with the tag of the page source of the access log, and the function name determination procedure is based on the match rate and the priority of the tag. The pattern definition generation program according to claim 2, wherein:

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