JP2636266B2 - Automatic generation of programs for multiple models - Google Patents

Description

Description: BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an automatic program generation method using reusable existing program parts,
The present invention relates to a method for automatically generating a program for a plurality of models, in which reusable existing program components are synthesized in accordance with stored product specifications and one program can operate on a plurality of models.

2. Description of the Related Art Generally, in the field of device control, hardware used, particularly relay and sensor control methods are various and complicated, and therefore, almost no systems realize automatic generation of programs.

Also, usually when creating a program for multiple models,
The creator must have the condition that he / she has expert knowledge and skills in the field in particular, and that he / she is familiar with the contents of the existing program. This leads to the insertion of a branch instruction for model identification, which is not good for program development efficiency.

Problems to be Solved by the Invention In order to solve the above-mentioned problems of the prior art, when it is considered that these model branch instructions are automatically inserted, it is necessary to determine all the related models for each part depending on the model. Requires a large number of branch instructions, resulting in an inefficient program.

In view of the above problems, the present invention efficiently generates a program corresponding to a plurality of models efficiently without requiring a creator to have expert knowledge and skill and without having to be familiar with an existing program. The purpose is to provide functions.

Means for Solving the Problems In order to solve the above problems and achieve the object, the automatic program generation method for multiple models of the present invention employs a specification management unit that stores and manages product specifications of each model, and an existing program part. A parts management unit that accumulates and manages, and a specification request means for requesting and acquiring product specifications required for synthesis, and a parts request means for requesting and acquiring program components required for synthesis, and multiple models with differences in product specifications depending on the model Grouping means for grouping, and a component synthesizing unit having a model branch generating means for automatically inserting a model branch instruction, and when the presence or absence of the function specified in the product specification differs depending on the model, A function determination unit that groups a plurality of models according to the presence or absence of a designated function, and a plurality of models when different data values are used depending on the models. Grouping means having at least one means of data discriminating means for grouping according to the value of the data, and table discriminating means for grouping a plurality of models by table when the table to be referred to differs according to the model; And a model branch generation means for automatically inserting a model branch instruction for discriminating a plurality of models into a function realizing location, a data using location, or a table reference location of an existing program component using the model group grouped in the above. It is characterized by having. Hereinafter, description will be made with reference to the drawings.

According to the present invention, in the process, the component synthesizing unit that synthesizes the existing program components according to the product specifications of the corresponding model obtains the existing program components to be synthesized from the component management unit through the component requesting unit. The product specification data required for the part is obtained from the specification management unit through the specification request means.
This procedure is repeated for the designated number of models, and components of a plurality of models are synthesized. Here, using the grouping means, differences between the product specifications of the respective models are found, and the models are divided into groups in order to determine these models. Based on the grouping result, the model branch generation unit inserts a model branch for model determination to automatically generate a program corresponding to a plurality of models.

FIG. 1 is a system configuration diagram showing one embodiment of the present invention.
A component management unit 1 stores and manages reusable program components in a component database 2. A specification management unit 3 stores and manages product specifications of each model in a product specification database 4. Reference numeral 5 denotes a component synthesizing unit that synthesizes a program of a corresponding model in accordance with an instruction from a user interface of ten. At this time, necessary program components are obtained from the component management unit 1 through the component requesting means 6. The required product specification data is obtained from the specification management unit 3 through the specification request means 7 in order to synthesize the program parts for a plurality of models. Here, the product specifications are grouped by the grouping means 8 based on the difference in the specification values, and in order to distinguish each model group from the result, the model branch is automatically generated by the model branch generating means 9 and the program branch is generated. Embed in

FIG. 2 is an internal configuration diagram of the grouping means, wherein 11 function discriminating means for grouping by distinguishing the presence or absence of a function by model, 12 data discriminating means for grouping by discriminating a difference in data value between models, and It is composed of 13 table discriminating means for distinguishing and grouping the table to be referred according to the model.

FIG. 3 is a flow chart showing one embodiment of the present invention. Based on the program components obtained from the component management unit 1 through the 20 component requesting units, the product request from the specification management unit 3 through the 21 specification requesting units. Take in. Next, the type of the obtained product specification is determined by branching the 22 specification models, and the grouping means is selected from any of the function, data, and table. If there is a difference in the function depending on the model, 23 function discriminating means, if the data value differs depending on the model, 24 data discriminating means, if the reference table differs depending on the model,
Execute 25 table determination means. A model branch is automatically generated by 26 model branch generating means from the result of grouping by any of the three means. Finally, 27 specifications request end determination and 28 parts request end determination are performed, and the above processing is repeated until there is no request.

FIG. 4 shows a flow chart of the function determining means 24. First, a branch is made for each model depending on the presence or absence of 30 functions, and at 31 a model name having a function is stored in a temporary memory. Stores the model name without function. At 33, the end of all models is determined. At the end of the process, it is checked whether the group is a group of models that have already been grouped by comparing existing groups at 34. If the set is a new group, it is added and stored.

In FIG. 5, after being grouped by the function determining means 24,
FIG. 10 is a diagram showing a function determination procedure for inserting a model branch, wherein 35 program parts are classified into 36 groups 1 or 37 groups 2 for each model depending on the presence or absence of the function. At this time, the model generation program for 38 is completed by automatically inserting the model branch for determining the group 1.

FIG. 6 shows a flow chart of the data discriminating means 25. For each model, the data values used in the first branch of the 40 data values are compared with 41 data 1 to 42 for each model.
Of data n. n is a natural number less than the number of models. At 43, the end of all models is determined. At the end of the process, it is checked whether or not the group is a group of models that have already been grouped by comparing existing groups at 44. If the group is a new group, it is added and stored.

FIG. 7 shows a data discriminating procedure for inserting a model branch after grouping by the data discriminating means 25. Forty-five program parts are classified into 46 groups 1 to 47 according to the difference in the data value. It is classified into group n. At this time, a model branch for discriminating the group 1 to the group n-1 is automatically inserted to complete the 48 generation program.

FIG. 8 shows a flowchart of the table determining means 26. First, for each model, the values of the tables are compared by 50 reference table branches and classified into 51 tables 1 to 52 n. At 53, the end of all models is determined. At the end of the process, it is checked whether or not it is a set of models that have already been grouped by comparing existing groups at 53. If it is a new group, it is added and stored.

FIG. 9 shows a table discrimination procedure diagram in which a model branch is inserted after being grouped by the appearance means 26, and 55 program parts are changed from 56 groups 1 to 57 by the difference of the reference table.
Are classified into group n. At this time, the generation program of 58 is completed by automatically inserting a model branch for determining group 1 to group n-1 and a process of setting a reference address to a table used in each group.

As described above, by applying any one of the three grouping means to perform grouping, it is possible to effectively generate a model branch and easily and efficiently create a program.

As described above, as is clear from the embodiment, the automatic program generation method for multiple models according to the present invention uses three types of grouping means when synthesizing reusable existing program parts based on product specifications for each model. Even if the user is not familiar with all product specifications across multiple models and the contents of existing program parts by using any of the function discriminating means, Even if there is no knowledge or skill at home, a model branch for model discrimination is efficiently inserted by using the grouping means, and a program corresponding to a plurality of models can be easily generated in a short time. As a result, the program development and installation efficiency is significantly improved and a highly reliable program can be generated as compared with the related art, and an improvement in productivity can be expected.

[Brief description of the drawings]

FIG. 1 is a system configuration diagram showing an embodiment of an automatic program generation method for a plurality of models according to the present invention, FIG. 2 is an internal configuration diagram of grouping means, FIG. 3 is a flow chart of the automatic program generation method in FIG. Is a flowchart showing function discriminating means, FIG. 5 is a function discriminating procedure diagram including model branch generation after function discriminating means is implemented, FIG. 6 is a flowchart showing data discriminating means, and FIG. FIG. 8 is a flow chart showing the table discriminating means, and FIG. 9 is a table discriminating procedure chart including the model branch generation after the table discriminating means is implemented. 1 ... part management section, 2 ... partial database, 3 ... specification management section, 4 ... product specification database, 5 ... part synthesis section, 6 ... part requesting means, 7 ... specification requesting section, 8 ...
... Grouping means, 9 ... Model branch generation means, 10 ...
User interface, 11 function determining means, 12 data determining means, 13 table determining means.

Continuation of front page (56) References JP-A-50-115945 (JP, A) JP-A-62-156736 (JP, A) JP-A-62-197826 (JP, A) JP-A-60-207932 (JP, A) JP-A-61-208539 (JP, A) JP-A-61-67132 (JP, A) JP-A-63-311535 (JP, A)

Claims (1)

(57) [Claims] When a product specification relating to each of a plurality of models is inputted, a plurality of product specifications are provided in accordance with each of the plurality of product specifications.
In a system in which a reusable existing program part is synthesized to automatically generate a program operable for a plurality of models with one program, if a function specified by the product specification differs depending on the model, a plurality of Function determination means for grouping the models according to the presence or absence of the designated function, and data determination means for grouping a plurality of models by the value of the data when the value of data to be used differs depending on the model. Grouping means having at least one means of table discrimination means for grouping a plurality of models by table when different tables are referred to, and functions of existing program parts using model groups grouped by the grouping means. Model to determine model group in realization location, data usage location, or table reference location A plurality of models corresponding program automatic generation system, characterized in that a model branching generation means for inserting 岐命 old automatically.