JP2000076062A - System scale estimation supporting device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To perform high-reliable estimation in a short time through simple operation while excluding artificial factors as much as possible and utilizing the electronic data of specifications or design drawing prepared in the upstream process of development. SOLUTION: A processor 10 inputs an existent specification 30 and extracts a data function and a transaction function through an analytic part 110 according to rules held in an analytic rule DB 111. The information on the extracted data function and transaction function is held in an analytic DB 112. Based on the information held in the analytic DB 112, a measuring part 113 calculates a function point and outputs it to an input/output device 20 according to the measuring rules of function points.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to a system scale estimation support apparatus for supporting estimation of a system scale of a software system.

[0002]

2. Description of the Related Art In developing a software system, a development plan is made by estimating a development man-hour, a development scale, and the like. Usually, in estimating the development man-hour and the development scale, first, a method of estimating the scale of software and estimating the development man-hour and the development period based on this is adopted.

As a technique for estimating the scale of software, a technique called a function point method for measuring and quantifying the function of software from data used or generated inside the software is known. The function point method has various variations. For example, an IFPUG (International Function
Based on the “Function Point Calculation Manual” Release 4.0 created by the Point Users Group, function points are calculated as follows (IFPUG method).

First, as a first step, the types of function points to be calculated are determined based on the function points indicating the size of the application software, the function points used to know the scale of the new development project, and the function points for improving the functions. Select from three types of function points used to know the scale of the existing application change project.

In the next step, a range (measurement boundary) for measuring a function point is set.

In the third step, a group of logical data recognizable by the user is extracted as a data function and classified into two types, an internal logical file and an external interface file. Then, the complexity is measured according to the complexity determination table prepared for each type.

In a fourth step, a process involving data entry / exit with respect to the application is extracted as a transaction function, and an external input, which is a function for inputting data to the system beyond the measurement boundary determined in the second step, It is classified into three function types: external output, which is a function of outputting data to the system beyond the measurement boundary, and external inquiry, which is a function of referring to data within the measurement boundary. Then, similarly to the case of the data function, the complexity is measured according to the complexity determination table.

In a fifth step, based on the results of steps 3 and 4, the number is counted for each type and weight, each is weighted and added to obtain an unadjusted function point.

In a sixth step, the system characteristics divided into 14 items are evaluated in six steps, and the total of all the evaluation values is determined as the degree of influence. Then, the adjustment count is calculated from the adjustment count = 0.65 + (degree of influence / 100).

Finally, a final function point is calculated using the unadjusted function points and the adjusted count.

[0011]

In the current project, it is necessary to perform accurate and accurate estimation in a short time and to concentrate on system development. However, at present, specialists calculate function points while reading huge design documents and the like, and estimate the system scale. Therefore, there is a problem that much time is required for estimating the scale of the software system.

Further, since the estimation of the scale of the software system depends on the experience of the project manager, there is a problem that even if the measurement is performed using the same function point method, the value differs depending on the manager. .

Further, in order to develop a system more quickly, it is necessary to estimate the scale of the software system at an early stage and make a system development plan.

An object of the present invention is to eliminate an artificial factor as much as possible and to use electronic data of specifications and design documents created in the course of development in a simple operation in a short time. It is an object of the present invention to provide a system-scale estimation support method and apparatus capable of performing highly reliable estimation.

[0015]

In order to achieve the above object, a system scale estimation support device according to the present invention is a specification relating to a system for estimating a scale,
Means for inputting a specification file having information representing a data set and a data flow; means for extracting a data function and a transaction function from the specification file according to a given analysis rule; It has means for calculating function points according to a predetermined rule using the data function and transaction function extracted by the extracting means, and output means for outputting the calculated function points.

[0016]

FIG. 1 is a configuration diagram of a system scale estimation support apparatus according to an embodiment of the present invention. In addition,
In the present embodiment, a description will be given of a system scale estimation support to which the IFPUG method is applied.

The system size estimation support support device has a processing device 10 and an input / output device 20. Processing device 10
Is an analysis unit 110, an analysis rule database (analysis rule DB) 111, an analysis database (analysis DB) 11
2, measurement unit 113, measurement database (measurement DB) 11
4, an interface unit 115, and a correction rule database (correction rule DB) 116. In the present embodiment, the processing device 10 is realized by, for example, a computer such as a personal computer and a workstation, and the input / output device 20 can be realized as an input / output device such as a display, a printer, and a keyboard attached thereto. The analysis unit 110, the measurement unit 113, and the interface unit 115 are achieved by a program that can realize processing described later in software.

The analysis unit 110 uses the specification 30 as input information and extracts information necessary for calculating function points from the input required specification 30. Analysis rule DB
Reference numeral 111 stores rules necessary for the analysis unit 110 to extract information. The analysis DB 112 is a storage unit for storing information extracted by the analysis unit 110.
The measurement unit 114 calculates a function point using the information held in the analysis DB 112. Measurement unit 1
The function points calculated by 13 are stored in the measurement DB 114. The measurement results stored in the measurement DB 114 are output to the input / output device 20 by the interface unit 115. The user can correct this output using the input / output device 20.

The specification 30 is information indicating a data set (also referred to as an entity or an object) and a data flow (also referred to as a relation or a message) for a software system whose scale is to be measured. Here, it is assumed that the required specification for the software system to be developed uses a specification defined by the concepts of story, scenario, scene, and character. Such a specification is created by a technique described in, for example, Japanese Patent Application Laid-Open No. 9-81611. According to the technique described in Japanese Patent Application Laid-Open No. 9-81611, a character which is an element constituting a target business by a software system is defined, and real-world business is performed using data and procedures provided to the character in a scenario called a scene. The required specifications are defined by inputting as fragmentary concrete examples.

FIG. 2 is a conceptual configuration diagram for explaining an example of the specification 30. The story 200 is a set of fragmentary examples of the required specifications. A fragmentary example of a requirement in a story 200 is represented as a plurality of scenarios 210. The scenario 210 is composed of a character representing “person” or “thing” and a flow of “behavior” (action / processing).
Having. One scene 220, 221 represents a flow of one behavior of the character, and represents a state of involvement of the character and a change in data or attribute of the character.

In the figure, 220, 221, 222 and 22
3 represents a character appearing in the scene 220.
Each of the characters 220, 221, 222, and 223 has its name, display graphic information representing the image, retained internal data information, and internal procedure information. The internal data information held by the character is called an attribute, and the internal procedure information held by the character is called a message. The internal procedure means a “behavior” of a character, such as an operation or a process of performing an access such as reference or update between characters, such as accessing a database from a computer. In the figure, the solid line 240 is
The behavior is shown, and the broken line 241 shows the state of involvement between the characters.

FIG. 3 is a flowchart of a function point measurement process performed by using the processing device 10.

In the measurement process, first, the specification 30 is input (step 300). When the specification 30 is input, a measurement boundary is set. Here, the measurement boundary is set to the above-mentioned story unit, the story file is specified by the user, and the specified file is set as the measurement boundary (step 302).

The analysis unit 110 extracts a data function from the specification held in the designated file according to the analysis rule held in the analysis rule DB 111,
The number of element records and the number of data items that determine the complexity of the data function are extracted, and the information is analyzed.
B112. If such information cannot be extracted due to the analysis rules, an inquiry is made to the user.

The analysis rules stored in the analysis rule DB 111 in connection with the extraction of the data function include:
For example, there are rules such as "use a character represented by a database bitmap as a data function" and "use a user-defined character as a data function". These rules are for extracting a group of data such as a database in the development system from the specification. In addition, there is a rule regarding the type of the data function, such that a file whose data is updated is defined as an internal file, and a data that is not updated is defined as an external interface file. On the other hand, regarding the extraction of the data item, a rule such as “use the attribute of the data function as the data item of the data function” is held (step 304).

Next, the analysis unit 110 extracts a transaction function from the specification according to the analysis rules held in the analysis rule DB 111, extracts data items that determine the complexity of the transaction function, and analyzes these information. It is stored in the DB 112. If there is not enough information on the number of files and the number of data items to be changed, the user inputs and specifies.

Regarding the extraction of a transaction function, the analysis rule DB 111 holds an analysis rule such as “extract from all data flows related to a data unit to be a data function”. In addition, in order to determine the type of the transaction function, there is a rule based on whether the data function is updated and a comparison between the output data items. As for the data item, a rule such as “a data item whose data of a related data function has been changed by a transaction function is set as a data item” is held (step 306).

The measuring unit 113 counts the number of data items of the data function and the transaction function based on the information stored in the analysis DB 112.
Then, the complexity is determined for each of the data function and the transaction function according to a complexity determination table in which the complexity is defined according to the number of data items. Further, an unadjusted function point is calculated from the complexity.

The measuring section 113 further receives an input of the degree of influence of the system characteristic given by the user via the interface section 115, and calculates an adjustment coefficient using this degree of influence. Then, a function point is calculated from the unadjusted function point and the adjustment coefficient, and the measurement DB
To store the result. The interface unit 115 extracts the result from the measurement DB 114, and
(Step 308).

In step 310, the calculated function points are corrected according to a correction rule that is conscious of the system development stage. Specifically, the function points calculated at each stage of the system development are accumulated, and the modification values at each stage of the system development are held as modification rules in the modification rule DB 116 based on the accumulated function points. Correction rule DB 116
For example, a rule such as "correct the estimated function points by plus 10% at the development stage of the required specifications" is held. Such a modification can improve the accuracy of the function point.

FIG. 4 is an explanatory diagram showing an example of the output of information relating to the data function output based on the information obtained as a result of step 308.

Reference numeral 401 denotes a data function (in the figure,
DF). Reference numeral 202 denotes a type defined in the function point method of the extracted data function. In the figure, “IFL” represents an internal logical file according to the function point method, and “EIF” represents an external interface file according to the function point method. 403 is the calculated number of records. 404 is the calculated number of data items. 40
5 shows the complexity of a unit of data defined as a data function. By outputting such a list of data functions, the appropriateness of the determined data function can be easily verified. The user can make a correction to the inappropriate part by using the input / output device 20, and this correction is reflected in the measurement DB 114.

FIG. 5 is an explanatory diagram showing an example of the output of information relating to the transaction function output based on the information obtained as a result of step 308.

Reference numeral 501 denotes a transaction function (abbreviated as TF in the figure), which is set with, for example, the name of the sender of the message (from) and the name of the receiver of the message (to). Reference numeral 502 denotes the type of the extracted transaction function in the function point method. “EI” indicates that the transaction function is an external input, “EO” indicates an external output, and “EQ” indicates an external reference. 503 is the calculated number of related files. 504 is the number of data items changed by the transaction function. 505 is
Indicates the complexity of the transaction function. By outputting such a list as in the case of the data function, the appropriateness of the determined transaction function can be easily verified. The user can make a correction to the inappropriate part by using the input / output device 20, and this correction is
This is reflected in the measurement DB 114.

FIG. 6 shows an example of the corrected measurement result output in step 310.

In 601, a project name is set. In 602, information indicating to which development stage the input specification belongs is set. In 603,
An unadjusted function point (unadjusted FP) calculated according to the function point method is set. A function point 604 after adjustment according to the function point method (adjusted F
P) is set. In a step 605, a correction degree indicating the degree of correction performed in step 310 is set. 606 includes an adjusted function point 604 and a correction degree 60;
A final function point (final FP), which is the final measurement result obtained from 5, is set.

For example, in the figure, it can be seen that the first line shows the measurement result at the “required specification” stage of the “out-of-stock processing system”. In this example, the unadjusted function point is “20”, the adjusted function point is “18”, and the degree of correction is “+ 10%”. And it is shown that the final function point is 19.8.

As described above, according to the system scale estimation support apparatus of the present embodiment, the system scale of a software system can be obtained in a short time while eliminating artificial factors as much as possible.

Further, as input information, information such as specifications and basic design documents created upstream of the development process can be used, and estimation can be performed at an early stage of system development.

Further, by displaying the count contents of the function points in a list, it is possible to know the basis of the calculated function point value and correct the function point value.

[0041]

According to the present invention, it is possible to eliminate a human factor as much as possible and to perform a highly reliable estimation with a simple operation in a short time.

[Brief description of the drawings]

FIG. 1 is a configuration diagram of a system scale estimation support device according to an embodiment of the present invention.

FIG. 2 is a conceptual configuration diagram for explaining an example of a specification sheet 30.

FIG. 3 is a flowchart of a function point measurement process.

FIG. 4 is an explanatory diagram illustrating an example of output of information regarding a data function.

FIG. 5 is an explanatory diagram illustrating an example of output of information regarding a transaction function.

FIG. 6 is an explanatory diagram illustrating an example of an output of a measurement result.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 10 ... Processing device, 20 ... Input / output device, 30 ... Specification, 110 ... Analysis part, 111 ... Analysis rule, 112 ... Analysis DB, 113 ... Measurement part, 114: measurement DB 115: interface unit

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Katsuhiko Yuura, Inventor 2-2-2 Kagahara, Tsuzuki-ku, Yokohama-shi, Kanagawa Prefecture F-term in the System Development Division, Hitachi, Ltd. 5B076 DF01

Claims (5)

[Claims] 1. A specification relating to a system for estimating a scale, comprising: means for inputting a specification file having information indicating a data collection and data flow; and Means for extracting a data function and a transaction function from the specification file; and a data function extracted by the extracting means;
A system scale estimation support device, comprising: means for calculating a function point according to a predetermined rule using a transaction function; and output means for outputting the calculated function point. 2. The system scale estimation support apparatus according to claim 1, wherein said extracting means extracts information recognized as a data unit from a division included in said specification. 3. The system scale estimation support apparatus according to claim 2, wherein said extraction means extracts a function related to a set of data extracted as a data function as a transaction function. 4. The predetermined rule includes a rule for determining complexity from the number of data items of each of the extracted data function and transaction function, and a rule for determining an unadjusted function point from the complexity. Wherein the calculating means comprises:
A data function extracted by the extraction means,
For each of the transaction functions,
4. The system scale estimation support apparatus according to claim 1, wherein a complexity according to the predetermined rule is determined, and an unadjusted function point is obtained based on the complexity. 5. The system scale estimation support device according to claim 4, wherein said output means displays a list of the extracted data functions or transaction functions together with the number of counted data items and the complexity.