JP7255420B2 - ASSET MANAGEMENT DEVICE, ASSET MANAGEMENT METHOD AND ASSET MANAGEMENT PROGRAM - Google Patents

Description

The present invention relates to an asset management device, an asset management method, and an asset management program.

With the development of computer systems, computer systems are being used in various situations in the world. Even a computer system that has been built once may need to be improved or reviewed as a whole as time passes. At this time, part of the already created program may be modified, and it is necessary to understand the specifications of the existing system. However, when software becomes large, its specifications become complicated, and it is not easy to grasp and change the specifications. In addition, when a huge number of programs are targeted, the number of relationships between programs and data becomes enormous, so it is not easy to divide software based on all the relationships.

In recent years, as a technology for dividing software into comprehensible subsets of service components for large-scale systems, a technology for automatically extracting and clustering subsets based on program call relationships is known. . In addition, when extracting a subset, there is also known a technique of defining externally updated data as common data, defining a new extraction unit excluding common data, and clustering. . Also known is a technology that automatically maps the functional structure of applications in order to intuitively understand the priority of applications targeted for modernization.

JP 2012-098902 A Japanese Patent Application Laid-Open No. 2018-181005

However, with the above technology, when arranging a plurality of programs and data of an application in subsets for each process, which is a component for executing a service, it becomes difficult to understand the structure of the application depending on the arrangement of the programs.

For example, when a certain program is assigned to multiple processes, deadlocks may be induced, and correct clustering cannot be performed in consideration of exclusive management, and as a result, program correction cannot be executed. Also, in order to suppress deadlocks, it is conceivable to cluster a program so that it does not belong to any process.

An object of one aspect is to provide an asset management device, an asset management method, and an asset management program capable of classifying the structure of an application in an easy-to-understand format.

In the first proposal, the asset management apparatus has a first identification unit that identifies a first program called from another program among a plurality of programs and a plurality of data constituting program assets. The asset management device identifies a second program, among the first programs, that internally retains any of the plurality of data or updates any of the plurality of data. It has a second specifying part. The asset management device classifies the second program into an independent service component when classifying the plurality of programs and the plurality of data into service components that associate the programs and data based on dependency relationships. have

According to one embodiment, the structure of an application can be categorized in an easy-to-understand format.

FIG. 1 is a diagram for explaining an analysis apparatus according to a first embodiment; FIG. FIG. 2 is a diagram for explaining problems of a general analysis method. FIG. 3 is a diagram illustrating an example in which duplication becomes a problem. FIG. 4 is a diagram illustrating an example in which overlap facilitates classification. FIG. 5 is a functional block diagram showing the functional configuration of the analysis device according to the first embodiment; FIG. 6 is a diagram showing an example of the entire program stored in the program asset DB. FIG. 7 is a diagram illustrating an example in which duplication is determined to be possible. FIG. 8 is a diagram illustrating an example in which duplication is determined to be impossible. FIG. 9 is a diagram illustrating an example in which duplication is determined to be impossible. FIG. 10 is a diagram illustrating an example in which duplication is determined to be impossible. FIG. 11 is a diagram illustrating an example in which duplication is determined to be impossible. FIG. 12 is a diagram for explaining the calling structure and classification of programs. FIG. 13 is a diagram for explaining the result of generating service component candidates. FIG. 14 is a diagram for explaining analysis results and output examples. FIG. 15 is a flowchart showing the overall flow of processing. FIG. 16 is a flowchart showing the flow of duplication determination processing. FIG. 17 is a flow chart showing the flow of program group generation processing. FIG. 18 is a diagram illustrating a hardware configuration example.

Embodiments of an asset management device, an asset management method, and an asset management program disclosed in the present application will be described below in detail with reference to the drawings. In addition, this invention is not limited by this Example. Moreover, each embodiment can be appropriately combined within a range without contradiction.

[Description of analyzer]
FIG. 1 is a diagram illustrating an analysis device 100 according to Example 1. FIG. As shown in FIG. 1, the analysis apparatus 100 performs loosely coupled analysis on program assets including multiple programs and multiple data, and divides and classifies programs, databases, etc. within program assets such as applications. to generate an analysis result that analyzes the structure of the application. In other words, the analysis apparatus 100 is an example of an asset management apparatus, and grasps the internal structure of program assets, and restructures functions and data into forms that are easy to extract as services.

In general, program assets applied to a certain system are updated along with changes in the surrounding environment such as modification, extension, and network of the system. In other words, as the system is used for many years, parts (elements) such as programs and databases are added to the program assets, and parts in the program assets are changed over time. Since such program assets that are updated over time are updated by multiple people, it is not uncommon for there to be no accurate management data (update data). For this reason, when performing reverse engineering or program structure analysis, etc., the entire program assets can be referred to, and how parts within the program assets are related to other parts, and how to update a certain part. It is not easy even for system engineers and programmers to analyze and understand what affects parts.

In recent years, there has been a demand to quickly change systems in accordance with rapidly changing business. For example, in the business of industrial distribution, there are frequent additions of bases and changes in business partners, and it is required to change the business system accordingly. However, many of the previous business systems had a structure in which programs and data were integrated, and it was impossible to know where the impact would be if the system were to be changed. As a result, it is difficult to modify and cannot be changed frequently. In addition, when attempting to divide a program so as to localize the scope of influence, many dependencies must be examined, resulting in an enormous amount of work time.

The problem with general methods is that when a program is divided into processes, which are service components that execute services, programs that can be placed in each process and programs that should be placed in a single process without duplication. and cannot be determined.

FIG. 2 is a diagram for explaining problems of a general analysis method. FIG. 2(a) shows an application, which is a program resource. In (a) of FIG. 2, an application is composed of a process composed of a plurality of programs and data X, Y, Z such as a database. Here, for the sake of simplification, program 1 is denoted as PG1, etc., the calling relationship between programs is indicated by solid-line arrows, the data update flow is indicated by broken-line arrows, and the data reference flow is indicated by thick-line arrows. show. That is, there is a dependency relationship in which PG2 and PG3 are called from PG1, PG10, and PG20, respectively. Further, there is a relationship of updating data from PG1, PG10, and PG3 to data X, a relationship of data reference from PG1 to data Y, and a relationship of updating data from PG20 to data Z.

In such a state, generally, as shown in FIG. 2(b), a program is always classified into only one process, can be placed in each process to be classified. In other words, classification is performed without duplication of programs, or classification is performed with duplication of programs allowed. However, depending on the structure of the application, the classification may not be performed correctly, causing problems such as deadlocks, and on the contrary, the structure of the application may become difficult to understand.

FIG. 3 is a diagram illustrating an example in which duplication becomes a problem. It is difficult to manage data, such as exclusive management, during execution of data that is updated by various processes. Also, although there is replication in which data is stored in multiple locations, it is easier to manage if the update location is limited. Specifically, in a system that lends and borrows one resource, if each process directly refers to or updates data, data access will be concentrated. In addition, whether or not the data is lent out must be immediately reflected in other processing, so it is difficult to distribute and manage the data by replication or the like.

For example, as shown in FIG. 3, it accepts requests from each process such as service monitoring process, intranet service provision process, and service search process, and executes use and release of pooled IP (Internet Protocol) addresses. Consider an address management program. In this case, since it is sufficient for each process to lend and borrow IP addresses, it is more efficient to manage them in one process rather than arranging the address management program in a plurality of processes so that each process directly lends and borrows IP addresses. be.

FIG. 4 is a diagram illustrating an example in which overlap facilitates classification. The same or similar processing may be performed on different data. In this case, even if the same program is called, it may be possible to simplify the relationship between processes by arranging them for each process.

For example, as shown in FIG. 4, for a request from each of the estimated acquisition date calculation processing for calculating the scheduled date of the estimate and the scheduled delivery date calculation processing for calculating the scheduled delivery date, the specified business day and the calendar Consider a response program that returns a scheduled date from information. In the case of this response program, data is passed as an argument, and data update of DB etc. is not executed. Therefore, if a response program is placed in each process (each process), the independence of each process can be ensured and communication can be reduced.

As mentioned above, depending on the type of processing and data update status, there are cases where it is better to place it in each process to be classified, and there are cases where it is classified as an independent process without being placed in each process to be classified. There are cases where it is better, and it is difficult to judge.

Therefore, the analysis apparatus 100 according to the first embodiment identifies the first program called by another program among the plurality of programs and the plurality of data constituting the program assets. Analysis device 100 identifies a second program, among the first programs, that internally retains any of the plurality of data or updates any of the plurality of data. After that, when classifying the plurality of programs and the plurality of data into service components (processes) that associate the programs and data based on the dependency relationship, the analysis device 100 classifies the second program into independent service components. .

In this way, the analysis apparatus 100 automatically determines whether the programs may be arranged for each process or whether the programs should be arranged in one unit without duplication for each process, and appropriately classifies the programs. By doing so, the structure of the application can be categorized in an easy-to-understand format.

[Explanation of terms]
Here, terms used in the first embodiment will be explained. An application indicates an entire program, and in this embodiment, an application that is a program in which business logic or the like is implemented is targeted. Note that the operating system is not included in the program in this embodiment.

A program is a part of an application, and a function is processing provided by logic implemented in the application. The data are database tables, files, and the like. A service refers to one execution unit of a microservice that implements a plurality of services by combining them, rather than implementing an application as a block. A process is an execution form of a service.

[Function configuration]
FIG. 5 is a functional block diagram showing the functional configuration of the analysis device 100 according to the first embodiment. As shown in FIG. 5, the analysis device 100 has a communication section 101, a storage section 102, and a control section 110. FIG.

The communication unit 101 is a processing unit that controls communication with another device, such as a communication interface. For example, the communication unit 101 receives an instruction to start processing and an input of a program asset to be analyzed from the administrator terminal. Also, the communication unit 101 transmits the analysis result to the administrator terminal or the like.

The storage unit 102 is an example of a storage device that stores programs and data, such as a memory or a hard disk. This storage unit 102 stores a program asset DB 103 , a duplication determination result DB 104 and an analysis result DB 105 .

The program asset DB 13 is a database that stores program assets, which are applications to be analyzed. The program assets stored here are stored by an administrator or the like. FIG. 6 is a diagram showing an example of the entire program stored in the program asset DB 13. As shown in FIG. As shown in FIG. 6, the program assets include program 1, program 10, program 2, program 3, and program 20. FIG. FIG. 6 is an example schematically showing description examples of five programs, and describes only program calling portions and data access.

The overlap determination result DB 104 is a database that stores information specifying whether or not each program permits overlapping placement. For example, the duplication determination result DB 104 stores information indicating whether or not each program can be redundantly arranged in a plurality of processes, a list of programs that can be redundantly arranged, and the like.

The analysis result DB 105 is a database that stores analysis results of program assets by the control unit 20, which will be described later. For example, the analysis result DB 105 associates and stores identifiers indicating program assets, analysis results, analysis dates, and the like.

The control unit 110 is a processing unit that controls the entire analysis apparatus 100, such as a processor. The control unit 110 has an analysis unit 111 , a duplication determination unit 112 , an analysis unit 113 and a presentation unit 114 . Note that the analysis unit 111, the duplication determination unit 112, the analysis unit 113, and the presentation unit 114 are an example of an electronic circuit possessed by a processor, an example of a process executed by the processor, and the like.

The analysis unit 111 is a processing unit that analyzes relationships between programs in program assets. Specifically, the analysis unit 111 receives program assets as an input, and identifies a program serving as a starting point and a program read from another program based on the relationship between program calls and the relationship between programs and data.

For example, using FIG. 6 as an example, the analysis unit 111 identifies program 1, program 10, and program 20 as starting points because they are not called by other programs. On the other hand, since the programs 2 and 3 are called from other programs, the analysis unit 111 identifies them as non-originating programs called from other programs, not originating programs. Then, the analysis unit 111 stores the specified information in the storage unit 102 or outputs it to another processing unit.

The duplication determination unit 112 is a processing unit that determines whether or not it is permissible for each program to be redundantly placed in a plurality of processes. Specifically, the duplication determination unit 112 determines whether the non-originating program (called program) identified by the analysis unit 111 is a program that holds data internally or a program that updates data. Then, the duplication judging unit 112 judges that the program cannot be redundantly arranged when these conditions apply, and judges that the program can be arranged redundantly when it does not correspond to these conditions, and stores the result in the duplication judgment result DB 104. .

For example, referring to FIG. 6, of program 2 and program 3, which are determined to be called by another program, program 3 writes to data Y, so the duplication determination unit 112 determines that duplication is not possible. However, since program 2 does not write data, it is determined that duplication is possible.

Here, an example of judging whether overlap is possible will be specifically described with reference to FIGS. 7 to 11. FIG. FIG. 7 is a diagram for explaining an example in which it is determined that overlap is possible, and FIGS. 8 to 11 are diagrams for explaining examples in which it is determined that overlap is not possible. Here, a program written in COBOL will be described as an example.

In the example of FIG. 7, program 2 is a program that is called from program 1 and that processes and responds using only the input from program 1 that called it. Specifically, program 1 acquires output B when input A is specified when program 2 is called. Program 2 returns 1 as output B if input A is 1, and returns 2 as output B if input A is not 1. That is, program 2 is determined as a duplication-permissible program because it only refers to data.

In the example of FIG. 8, program 3 is a program called from program 1. In the example of FIG. Specifically, the called program 3 updates the data X, which is a database, in addition to the description similar to that of the program 2 described with reference to FIG. That is, program 3 is a program that directly accesses data and updates data, and since the syntax for updating data is described, it is determined to be a non-duplicate program.

In the example of FIG. 9, program 4 is a program called from program 1. In the example of FIG. Specifically, when the input A from the program 1 is 1, the program 4 updates the data X and sets ID=B for the data X. Also, program 4 updates data Y when input A from program 1 is not 1, and sets ID=B for data Y. FIG. In other words, since program 4 is a program that updates one or more databases, it is determined as a non-duplicate program.

In the example of FIG. 10, program 4 is a program called from program 1. In the example of FIG. Specifically, program 4 writes input A from program 1 to file AA, and moves the data in file AA to data item BB in the shared memory area accessible by each program. That is, the program 4 is a program in which a syntax for writing to a file is described, and should be managed together with the file side, so it is determined as a non-overlapping program. Program 4 is also a program in which a syntax for updating the shared memory area is described, and should be managed as an integral part of the shared memory area, and is determined to be a non-overlapping program.

The example of FIG. 11 is an example of a program written in an object-oriented language such as Java (registered trademark). The program in FIG. 11 is a program that refers to and updates a database although there is no explicit description such as an SQL statement. In this way, even programs that do not have update statements, like data objects, that update data shared by multiple processes should be managed together with the data, and will be judged as non-duplicate programs. be.

Returning to FIG. 5, the analysis unit 113 is a processing unit that analyzes and classifies each program and each data in the program assets so that the structure of the application can be easily understood. Specifically, the analysis unit 113 classifies and generates service components using the technique disclosed in Japanese Patent Application Laid-Open No. 2018-181005. At this time, the analysis unit 113 classifies the programs determined by the duplication determination unit 112 to be non-duplicate into independent service components.

For example, the analysis unit 113 traces the calling relationship from the starting program, creates the entire calling structure of the program, and defines it as a "program group". Subsequently, the analysis unit 113 generates service component candidates, which are subsets obtained by grouping program groups and data that are particularly close in relation to each program group and data, based on the relationship between each program group and data. After that, the analysis unit 113 extracts, as common data, data updated from other service component candidates among the data associated with the plurality of service component candidates, and extracts the common data and the plurality of service component candidates that do not include common data. , is generated as a service component of the program assets.

Each process will now be described. FIG. 12 is a diagram for explaining the calling structure and classification of programs. FIG. 12 illustrates an example of generating a program group from the program assets of FIG. In the above example, the analysis unit 113 identifies program 1, program 10, and program 20 as starting points according to the information notified from the analysis unit 111. FIG.

Subsequently, the analysis unit 113 creates a call structure starting from program 1, which is the starting point. Program 1 calls Program 2 and Program 3. From this, it can be determined that the program 1 holds the call structure together with the programs 2 and 3. FIG. Therefore, the analysis unit 113 generates a program group 1 starting from the program 1, and classifies the programs 2 and 3 that can be traced from the program 1 into the program group 1, but it is determined that the duplication of the program 3 is impossible. Therefore, it is excluded from program group 1. It should be noted that program 2 is classified as program group 1 as it is because it has been determined that duplication is possible.

Thus, the analysis unit 113 generates a program group 10 composed of the program 10 and the program 2 and a program group 20 composed of the program 20 and the program 2. FIG. Since it is determined that program 3 cannot overlap, analysis unit 113 generates program group 3 as an independent program group that does not belong to any program group. As a result, the analysis unit 113 can generate program group 1, program group 10, program group 20, and program group 3. FIG.

Subsequently, the analysis unit 113 associates data accessed by each program group with each program group. Specifically, program 1 of program group 1 updates data X and references data Y. As shown in FIG. Therefore, the analysis unit 113 defines a relationship that the program group 1 updates the data X and refers to the data. In this manner, the analysis unit 113 associates data with each of program group 1, program group 10, program group 20, and program group 3. FIG.

These results are shown in FIG. Based on the calling relationship shown in FIG. 12(a), the analysis unit 113 generates, for example, the relationship that the program group 1 updates and refers to the data X as shown in FIG. 12(b), It outputs to the storage unit 12 and other processing units. Specifically, program group 1 updates data X, references data Y, and calls program group 3 . Program group 10 updates data Y and calls program group 3 . Program group 20 updates data Z and calls program group 3 . A program group 3 is called by each of the program groups 1, 10, and 20 and has a relationship of updating data Y. FIG.

Note that the output format is not limited to this, and various formats can be adopted according to the output destination tool. For example, as shown in (c) of FIG. 12, relationships are described by defining relationship formations separated by commas, adding programs, data, and reference relationships in the form of #read, and update relationships in the form of #write. can also For example, the first line in (c) of FIG. 12 describes that program group 1 updates (writes) data X. FIG.

Next, the analysis unit 113 uses a clustering technique such as Japanese Patent Application Laid-Open No. 2013-148987 to group subsets that are particularly close in terms of the relationship between the program group and the data based on the relationship between each program group and the data. to generate a service component candidate. For example, the analysis unit 113 determines that the greater the number of inputs to each piece of data, the stronger the relationship, and generates service component candidates so that programs and data having a strong relationship are grouped together. The generated results are shown in FIG. FIG. 13 is a diagram for explaining the result of generating service component candidates.

As shown in FIG. 13, the analysis unit 113 analyzes a service component candidate (ID=01) including program group 1 and data X, a service component candidate (ID=02) including program group 10, a program group 20 and data Z and a service component candidate (ID=04) containing program group 3 and data Y are generated. In addition, the analysis unit 113 defines "(01, program group 1), (01, data X), (02, program group 10), (03, Program group 10), (03, data Z), (04, program group 3), (04, data Y), etc. are also generated. After that, the analysis unit 113 outputs the generated service component candidates to other processing units.

After that, the analysis unit 113 extracts, as common data, data updated from other service component candidates among the data associated with the plurality of service component candidates, and extracts the common data and the plurality of service component candidates that do not include common data. , is generated as a service component of the program assets. In this embodiment, the case where common data does not exist is exemplified, so the analysis unit 113 stores the information shown in FIG. 13 in the analysis result DB 105 as a result of the classified service components.

Returning to FIG. 5, the presentation unit 114 is a processing unit that outputs the analysis result of the analysis unit 113 to a user or the like. Specifically, the presentation unit 114 obtains the analysis results stored in the analysis result DB 105, and displays the analysis results classified into a plurality of service components. display in a different format than other programs and data.

FIG. 14 is a diagram for explaining analysis results and output examples. As shown in FIG. 14, the presentation unit 114 displays the starting program in a vertically elongated manner, thereby outputting the program in a larger size than the other programs. In addition, the presentation unit 114 displays the programs belonging to each process (each package) in different colors. In addition, the presentation unit 114 changes the color and shape of the program 3 classified as an independent process to update data and the like, thereby outputting the program in a format different from that of other programs. When software map technology or the like is used, the presentation unit 114 can also display the shapes of the originating program and non-overlapping programs by changing the height and color to distinguish them from other programs.

[Process flow]
FIG. 15 is a flowchart showing the overall flow of processing. As shown in FIG. 15, when the analysis apparatus 100 receives an analysis processing start instruction or the like, it analyzes the relationship between the programs in the program assets (S101).

Subsequently, the analysis apparatus 100 executes overlap determination processing for determining whether or not it is permissible for each program to be redundantly placed in a plurality of processes (S102). A program group generation process for tracing and generating a program group is executed (S103).

After that, the analysis device 100 generates service component candidates, which are subsets obtained by grouping programs and data that are particularly close in relation to the data, and performs component extraction processing for extracting service components (S104), and extracts common data. A plurality of service component candidates not included and common data are presented as analysis results generated as program resource service components (S105).

(Duplicate determination process)
FIG. 16 is a flowchart showing the flow of duplication determination processing. Note that this process is a process executed in S102 of FIG.

As shown in FIG. 16, the duplication determination unit 112 acquires a program (S201), refers to the description content of the program, and determines whether or not there is a syntax for updating data or a DB (S202). Here, if there is a syntax for updating data or DB (S202: Yes), the duplication determination unit 112 classifies the program as non-duplicatable (S203).

On the other hand, if there is no syntax for updating data or DB (S202: No) but there is syntax for writing a file (S204: Yes), the duplication determination unit 112 classifies the program as non-duplicate (S203).

If there is no file writing syntax (S204: No) but there is a syntax for updating the shared memory area (S205: Yes), the duplication determination unit 112 classifies the program as non-duplicate (S203).

Then, if there is no syntax for updating the shared memory area (S205: No), the duplication determination unit 112 classifies the program as duplication possible (S206). After that, when there is an undetermined program (S207: No), the duplication determination unit 112 repeats the steps from S201 onward, and when determination is completed for all programs (S207: Yes), the process ends.

(program group generation processing)
FIG. 17 is a flow chart showing the flow of program group generation processing. Note that this process is the process executed in S103 of FIG.

As shown in FIG. 17, the analysis unit 113 acquires a starting program (S301), and acquires a called program called from the starting program (S302).

Next, when the called program is a program that can be duplicated (S303: Yes), the analysis unit 113 includes the called program in the same program group as the source program (S304). On the other hand, when the called program is a non-overlapping program (S303: No), the analysis unit 113 generates a binary relationship between the called program and the originating program group (S305).

If there is a called program that has not been tracked (S307: No), the analysis unit 113 repeats S302 and subsequent steps. On the other hand, the analysis unit 113 completes tracking of all called programs (S307: Yes), and if there is an unprocessed starting point program (S308: No), repeats S301 and subsequent steps to find the unprocessed starting point program. If the program does not exist (S308: Yes), the process ends.

[effect]
As described above, the analysis apparatus 100 can read data from many places (processes) for a program that only reads data. It can be determined that the processing is fast, and it can be determined that duplication is possible. In addition, for a program that writes data, the analysis apparatus 100 prioritizes waiting for other processes if data is written from many places (processes), and determines that duplication is not possible. can be done.

Therefore, the analysis apparatus 100 can clearly indicate what programs can be duplicated and what programs must not be duplicated in order to divide assets, thereby presenting an easy-to-use division plan. As a result, the analysis device 100 can present the structure of the application in an easy-to-understand format.

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 embodiments described above.

[Data, figures, etc.]
The number of programs, processes, service components, data, etc. used in the above embodiments are only examples and can be changed arbitrarily. Also, the order of each process can be changed as appropriate within a consistent range.

[Program analysis]
A known program analysis technique such as a parser can be employed as a method of acquiring the call relation and the read relation to data described in the above embodiment.

[system]
Information including processing procedures, control procedures, specific names, and various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified.

Also, each component of each device illustrated is functionally conceptual, and does not necessarily need to be physically configured as illustrated. That is, the specific forms of distribution and integration of each device are not limited to those shown in the drawings. That is, all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various loads and usage conditions.

Further, each processing function performed by each device may be implemented in whole or in part by a CPU and a program analyzed and executed by the CPU, or implemented as hardware based on wired logic.

[hardware]
FIG. 18 is a diagram illustrating a hardware configuration example. As shown in FIG. 18, the analysis device 10 has a communication device 100a, a HDD (Hard Disk Drive) 100b, a memory 100c, and a processor 100d. 18 are interconnected by a bus or the like.

The communication device 100a is a network interface card or the like, and communicates with other devices. The HDD 100b stores programs and DBs for operating the functions shown in FIG.

The processor 100d reads from the HDD 100b or the like a program for executing the same processing as each processing unit shown in FIG. 5 and develops it in the memory 100c, thereby operating processes for executing each function described with reference to FIG. 5 and the like. For example, this process executes the same function as each processing unit of the analysis device 100 . Specifically, the processor 100d reads a program having functions similar to those of the analysis unit 111, the duplication determination unit 112, the analysis unit 113, the presentation unit 114, and the like, from the HDD 10b and the like. Then, the processor 10d executes processes for executing the same processes as the analysis unit 111, the duplication determination unit 112, the analysis unit 113, the presentation unit 114, and the like.

In this way, the analysis apparatus 100 operates as an information processing apparatus that executes an asset management method by reading and executing a program. Further, the analysis apparatus 100 can read the program from the recording medium by the medium reading device and execute the read program to realize the same functions as the above embodiment. It should be noted that the programs referred to in other embodiments are not limited to being executed by the analyzer 100 . For example, the present invention can be applied in the same way when another computer or server executes the program, or when they cooperate to execute the program.

100 analysis device 101 communication unit 102 storage unit 103 program asset DB
104 Duplication determination result DB
105 Analysis result DB
110 control unit 111 analysis unit 112 duplication determination unit 113 analysis unit 114 presentation unit

Claims (6)

a first identifying unit that identifies a first program called from another program among a plurality of programs and a plurality of data that constitute program assets;
a second identifying unit that identifies a second program of the first program that internally retains any of the plurality of data or updates any of the plurality of data; ,
a classifying unit that classifies the second program into an independent service component when classifying the plurality of programs and the plurality of data into service components that associate the programs and data based on dependency relationships. An asset management device characterized by: The second specifying unit is, among the first program, a program describing a syntax for updating data, a program describing a syntax for writing a file, or a syntax for updating an area of a shared memory. 2. The asset management apparatus according to claim 1, wherein a program corresponding to the program that has been registered is specified as the second program. The classifying unit specifies an originating program that is not called by other programs, and if a called program called by the originating program does not correspond to the second program, the originating program and the called program are identified. are classified into the same service component, and when the called program corresponds to the second program, the originating program and the called program are classified into separate service components. Or the asset management device according to 2. The method further comprises a display control unit that displays the originating program and the second program in a format different from that of other programs and data when displaying the result of classifying the program assets into a plurality of service components. 4. The asset management device according to claim 3. the computer
Identifying a first program called from another program among a plurality of programs and a plurality of data constituting a program asset;
identifying a second program among the first programs that internally retains any of the plurality of data or updates any of the plurality of data;
and classifying the second program into an independent service component when classifying the plurality of programs and the plurality of data into service components that associate the programs and the data based on the dependency relationship. asset management method. to the computer,
identifying a first program called from another program among a plurality of programs and a plurality of data constituting program assets;
identifying a second program among the first programs that internally retains any of the plurality of data or updates any of the plurality of data;
classifying the plurality of programs and the plurality of data into service components that associate the programs and the data based on dependencies, classifying the second program into independent service components. asset management program.

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