Software product information management system and method based on big data

Abstract

The present invention relates to the field of computer application technology, specifically to a software product information management system based on big data, comprising: an acquisition module, used to acquire software product status information, the software product status information including software product information, storage path information and storage time information; a conversion module, used to call a string encoding rule in a server, encode the software product information into an information string, encode the storage path information into a path string, and encode the storage time information into a time string. The present invention provides information tracing and tracking for software product information management by setting an acquisition module, a conversion module, a storage module, an identification module, a modification module, and a query module, so as to solve the problem that when the software product is changed in the current software product information management, the source information of the software product status information and each modification information cannot be queried, making it impossible to trace and track the information in the software product information management.

Description

Technical Field

[0001] The present invention relates to the field of computer application technology, and in particular to a software product information management system and method based on big data. Background Art

[0002] Software products refer to computer software provided to users, software embedded in information systems or devices, or computer software provided when providing technical services such as computer information system integration and application services.

[0003] When the software manager changes the product information process, a large number of intermediate processes need to be generated. Among them, manually filling out application forms in various formats is a relatively complex part of the process. In addition, the product status process records are managed through the version control system, and the operator is required to spontaneously query the product status and product historical change process saved in the version control system layer by layer, manually update the local product library status, manually fill out the form and related documents and send them to the configuration administrator by email, and then the configuration administrator manually updates the product status.

[0004] In current software product information management, when a software product is modified, the existing saved software product status information will overwrite the original status information due to the modification, resulting in the inability to query the software product status information source information and each modification information, making it impossible to trace and track information in software product information management. Summary of the invention

[0005] The present invention provides the following technical solutions:

[0006] Software product information management system based on big data, including:

[0007] An acquisition module, used to acquire software product status information, wherein the software product status information includes software product information, storage path information and storage time information;

[0008] A conversion module, used to call the string encoding rule in the server, encode the software product information into an information string, encode the storage path information into a path string, and encode the storage time information into a time string;

[0009] A storage module, used for combining the information character string, the path character string and the time character string into an exclusive software character string, and storing the exclusive software character string in a database;

[0010] An identification module, used to establish a connection relationship with the database according to the exclusive software string, and generate an identification tag according to the connection relationship;

[0011] A modification module, used to modify the software product status information, save it as new software product status information after the modification is completed, save the modification record information, and link the new software product status information, the modification record information and the software product status information;

[0012] The query module is used to query according to the identification tag through the visual interface, match the corresponding database string after executing the query command, and then call the string decoding rule in the server to decode the database string to obtain the corresponding software product status information and the linked new software product status information and the modification record information.

[0013] As a preferred real-time solution of the present invention, the server stores a string encoding rule module and a string decoding rule module, the string encoding rule module includes an ASCII encoding unit and a GB2312 encoding unit, and the string decoding rule includes an ASCII decoding unit and a GB2312 decoding unit.

[0014] As a preferred real-time solution of the present invention, the acquisition module includes a software product information unit, and the software product information unit includes a software full name unit, a software abbreviation unit, a product classification number unit, a product version number unit, a product development completion date unit, a product publication status unit, a product first publication date unit, a product first publication location unit, a product development method unit, a product right acquisition method unit, a product right scope unit, a product hardware environment unit, a product software environment unit, a product programming language unit, and a product program code unit.

[0015] As a preferred real-time solution of the present invention, the query module includes:

[0016] A collection module, used to obtain a query method corresponding to the identification tag;

[0017] A training module, used for obtaining a corresponding preset neural network model according to the query method;

[0018] A construction module, used to input the query mode into the preset neural network model to obtain the user's habitual query mode information corresponding to the query in the visual interface;

[0019] The output module is used to send the customary query mode information to the server for storage.

[0020] The present invention also discloses a software product information management system and method based on big data, which is characterized by specifically comprising the following steps:

[0021] S101, used to obtain software product status information, where the software product status information includes software product information, storage path information, and storage time information;

[0022] S102, calling a string encoding rule in the server, encoding the software product information into an information string, encoding the storage path information into a path string, and encoding the storage time information into a time string;

[0023] S103, combining the information string, the path string and the time string into a dedicated software string, and storing the dedicated software string in a database;

[0024] S104, establishing a connection relationship with the database according to the exclusive software character string, and generating an identification tag according to the connection relationship;

[0025] S105, modifying the software product status information, and after the modification is completed, saving it as new software product status information, and saving the modification record information, and linking the new software product status information, the modification record information and the software product status information;

[0026] S106, querying according to the identification tag through the visual interface, matching the corresponding database string after executing the query command, and then calling the string decoding rule in the server to decode the database string to obtain the corresponding software product status information and the linked new software product status information and the modification record information.

[0027] As a preferred real-time solution of the present invention, the string encoding rule includes ASCII encoding and GB2312 encoding, and the string decoding rule includes ASCII decoding and GB2312 decoding.

[0028] As a preferred real-time solution of the present invention, the software product information includes the full name of the software, the abbreviation of the software, the product classification number, the product version number, the product development completion date, the product publication status, the product first publication date, the product first publication location, the product development method, the product right acquisition method, the product right scope, the product hardware environment, the product software environment, the product programming language, and the product program code.

[0029] As a preferred real-time solution of the present invention, the method for querying according to the identification tag through the visual interface includes:

[0030] S201, obtaining a query method corresponding to the identification tag;

[0031] S202, obtaining a corresponding preset neural network model according to the query method;

[0032] S203, inputting the query mode into the preset neural network model to obtain the user's habitual query mode information corresponding to the query in the visual interface;

[0033] S204, sending the customary query method information to a server for storage.

[0034] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0035] The embodiments of the present application provide information traceability and tracking for software product information management by setting an acquisition module, a conversion module, a storage module, an identification module, a modification module, and a query module, so as to solve the problem that when a software product is changed in the current software product information management, the existing saved software product status information will overwrite the original status information due to the modification, resulting in that the source information of the software product status information and each modification information cannot be queried, making it impossible to trace and track the information in the software product information management.

[0036] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 A structural block diagram of a big data-based software product information management system provided in an embodiment of the present application.

[0039] Figure 2 A flowchart of a software product information management method based on big data provided in an embodiment of the present application.

[0040] Figure 3 This is a structural block diagram of the neural network model module provided in an embodiment of the present application.

[0041] Figure 4 A flowchart of a neural network model method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0043] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0045] In the description of the embodiments of the present invention, it should be noted that if the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside", etc. appear, the orientation or position relationship indicated is based on the orientation or position relationship shown in the drawings, or the orientation or position relationship in which the product of the invention is usually placed when in use. It is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, if the terms "first", "second", "third", etc. appear, they are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0046] In addition, the terms "horizontal", "vertical", "overhanging" and the like do not mean that the components must be absolutely horizontal or overhanging, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0047] In the description of the embodiments of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0048] like Figure 1-4As shown, the present application provides a software product information management system and method based on big data, which provides information traceability and tracking for software product information management by setting an acquisition module, a conversion module, a storage module, an identification module, a modification module, and a query module, and solves the problem that when a software product is changed in the current software product information management, the existing saved software product status information will overwrite the original status information due to the modification, resulting in the inability to query the source information of the software product status information and each modification information, making it impossible to trace and track the information in the software product information management. Specifically, it includes:

[0049] Example 1: Figure 1 As shown, this application provides a software product information management system based on big data, including:

[0050] An acquisition module, used to acquire software product status information, wherein the software product status information includes software product information, storage path information and storage time information;

[0051] A conversion module, used to call the string encoding rule in the server, encode the software product information into an information string, encode the storage path information into a path string, and encode the storage time information into a time string;

[0052] A storage module, used for combining the information character string, the path character string and the time character string into an exclusive software character string, and storing the exclusive software character string in a database;

[0053] An identification module, used to establish a connection relationship with the database according to the exclusive software string, and generate an identification tag according to the connection relationship;

[0054] A modification module, used to modify the software product status information, save it as new software product status information after the modification is completed, save the modification record information, and link the new software product status information, the modification record information and the software product status information;

[0055] The query module is used to query according to the identification tag through the visual interface, match the corresponding database string after executing the query command, and then call the string decoding rule in the server to decode the database string to obtain the corresponding software product status information and the linked new software product status information and the modification record information.

[0056] In this embodiment, the server stores a string encoding rule module and a string decoding rule module, the string encoding rule module includes an ASCII encoding unit and a GB2312 encoding unit, and the string decoding rule includes an ASCII decoding unit and a GB2312 decoding unit.

[0057] Specifically, ASCII codes use specified 7-bit or 8-bit binary number combinations to represent 128 or 256 possible characters. Standard ASCII code, also known as basic ASCII code, uses 7-bit binary numbers (with the remaining 1-bit binary being 0) to represent all uppercase and lowercase letters, numbers 0 to 9, punctuation marks. 0 to 31 and 127 (a total of 33) are control characters or communication-specific characters (the rest are displayable characters), such as control characters: LF (line feed), CR (carriage return), FF (form feed), DEL (delete), BS (backspace), BEL (bell), etc.; communication-specific characters: SOH (start of heading), EOT (end of transmission), ACK (acknowledgment), etc. ASCII values 8, 9, 10, and 13 are converted to backspace, tab, line feed, and carriage return characters respectively. They do not have specific graphical displays, but will have different effects on text display depending on different applications. 32 to 126 (a total of 95) are characters (32 is a space), among which 48 to 57 are the ten Arabic numerals from 0 to 9, 65 to 90 are the 26 uppercase English letters, 97 to 122 are the 26 lowercase English letters, and the rest are some punctuation marks, arithmetic symbols, etc.

[0058] Specifically, GB2312 encoding is the national standard for Chinese character encoding. GB2312 encoding收录6763 Chinese characters in total, including 3755 first-level Chinese characters and 3008 second-level Chinese characters. At the same time, GB2312 encoding收录682 full-width characters including Latin letters, Greek letters, Japanese hiragana and katakana letters, and Russian Cyrillic letters. GB2312 encoding performs a partition processing on the收录 characters, with a total of 94 areas. Each area contains 94 positions, with a total of 8836 code positions. This representation method is also called the area-position code. Areas 01 - 09收录682 characters other than Chinese characters, areas 10 - 15 are blank areas and not used, areas 16 - 55收录3755 first-level Chinese characters, sorted by pinyin, areas 56 - 87收录3008 second-level Chinese characters, sorted by radical / stroke count, and areas 88 - 94 are blank areas and not used. For example, the character '啊' is the first Chinese character in GB2312 encoding. It is located at position 01 in area 16, so its area-position code is 1601.

[0059] In this embodiment, the obtaining module includes a software product information unit, and the software product information unit includes a software full name unit, a software short name unit, a product classification number unit, a product version number unit, a product development completion date unit, a product publication status unit, a product first publication date unit, a product first publication location unit, a product development method unit, a product right acquisition method unit, a product right scope unit, a product hardware environment unit, a product software environment unit, a product programming language unit, and a product program code unit.

[0060] It should be noted that there are some inaccuracies in the original Chinese text for the English translation of "收录". It should be "includes" or "contains" etc. The above translation has been adjusted according to the correct meaning.Specifically, the product publication status unit includes published and unpublished options; the product development method unit includes independent development, cooperative development, commissioned development, and task development options; the product rights acquisition method unit includes original acquisition, inherited acquisition (assignment, assumption, inheritance), whether the software has been registered (original registration number), and whether the registration has been changed or supplemented (change or supplement certificate number) options; the product rights scope unit includes all and part (right of publication, right of authorship, right of modification, right of reproduction, right of distribution, right of rental, right of information network dissemination, right of translation, and other rights that should be enjoyed by the copyright owner) options.

[0061] In this embodiment, if Figure 3 As shown, the query module includes:

[0062] A collection module, used to obtain a query method corresponding to the identification tag;

[0063] A training module, used for obtaining a corresponding preset neural network model according to the query method;

[0064] A construction module, used to input the query mode into the preset neural network model to obtain the user's habitual query mode information corresponding to the query in the visual interface;

[0065] The output module is used to send the customary query mode information to the server for storage.

[0066] Specifically, the preset neural network model is a pre-trained neural network model. Since each user has different query habits, different query methods will be generated. Through training, each user will generate habitual query method information based on the input method when querying in the visual interface, so that the server will generate corresponding associated identification tag information based on each user.

[0067] Neural network is a complex network system formed by a large number of simple processing units widely connected to each other. It reflects many basic characteristics of human brain function and is a highly complex nonlinear dynamic learning system. Neural network has large-scale parallel, distributed storage and processing, self-organization, self-adaptation and self-learning capabilities. It is particularly suitable for processing imprecise and fuzzy information processing problems that need to consider many factors and conditions at the same time. The neural network model is BP neural network, which is a hierarchical neural network composed of input layer, middle layer and output layer. The middle layer can be expanded to multiple layers. The neurons between adjacent layers are fully connected, and there is no connection between neurons in each layer. The network learns in a teacher-teaching manner. When a pair of learning patterns is provided to the network, each neuron obtains the input response of the network to generate connection weights, and then corrects each connection weight from the output layer through each middle layer layer by layer in the direction of reducing the error between the desired output and the actual output, and returns to the input layer. This process is repeated and alternating until the global error of the network tends to a given minimum value, that is, the learning process is completed.

[0068] Example 2: Figure 2 As shown, the present invention also discloses a software product information management system and method based on big data, which is characterized by specifically including the following steps:

[0069] S101, used to obtain software product status information, where the software product status information includes software product information, storage path information, and storage time information;

[0070] S102, calling a string encoding rule in the server, encoding the software product information into an information string, encoding the storage path information into a path string, and encoding the storage time information into a time string;

[0071] S103, combining the information string, the path string and the time string into a dedicated software string, and storing the dedicated software string in a database;

[0072] S104, establishing a connection relationship with the database according to the exclusive software character string, and generating an identification tag according to the connection relationship;

[0073] S105, modifying the software product status information, and after the modification is completed, saving it as new software product status information, and saving the modification record information, and linking the new software product status information, the modification record information and the software product status information;

[0074] S106. Query according to the recognition label through the visualization interface. After executing the query command, match the corresponding database string, and then call the string decoding rule in the server to decode the database string to obtain the corresponding software product status information, the linked new software product status information, and the modification record information.

[0075] In this embodiment, the string encoding rules include ASCII encoding and GB2312 encoding, and the string decoding rules include ASCII decoding and GB2312 decoding.

[0076] Specifically, ASCII codes use a specified combination of 7-bit or 8-bit binary numbers to represent 128 or 256 possible characters. The standard ASCII code is also called the basic ASCII code, which uses 7-bit binary numbers (the remaining 1-bit binary is 0) to represent all uppercase and lowercase letters, numbers 0 to 9, punctuation marks. 0 to 31 and 127 (a total of 33) are control characters or communication-specific characters (the rest are displayable characters), such as control characters: LF (line feed), CR (carriage return), FF (form feed), DEL (delete), BS (backspace), BEL (bell), etc.; communication-specific characters: SOH (start of heading), EOT (end of transmission), ACK (acknowledgment), etc. ASCII values 8, 9, 10, and 13 are converted to backspace, tab, line feed, and carriage return characters respectively. They do not have a specific graphical display, but will have different effects on text display depending on different applications. 32 to 126 (a total of 95) are characters (32 is a space), among which 48 to 57 are the ten Arabic numerals 0 to 9, 65 to 90 are the 26 uppercase English letters, 97 to 122 are the 26 lowercase English letters, and the rest are some punctuation marks, arithmetic symbols, etc.

[0077] Specifically, GB2312 encoding is the national standard for Chinese character encoding. GB2312 encoding includes a total of 6763 Chinese characters, among which there are 3755 first-level Chinese characters and 3008 second-level Chinese characters. At the same time, GB2312 encoding includes 682 full-width characters including Latin letters, Greek letters, Japanese hiragana and katakana letters, and Russian Cyrillic letters. GB2312 encoding divides the included characters into zones. There are a total of 94 zones, each zone contains 94 bits, and a total of 8836 code positions. This representation method is also called the area-position code. Zones 01 - 09 include 682 characters other than Chinese characters. Zones 10 - 15 are blank zones and not used. Zones 16 - 55 include 3755 first-level Chinese characters, sorted by pinyin. Zones 56 - 87 include 3008 second-level Chinese characters, sorted by radical / stroke count. Zones 88 - 94 are blank zones and not used. For example, the character "啊" is the first Chinese character in GB2312 encoding. It is located at the 01st position in the 16th zone, so its area-position code is 1601.

[0078] In this embodiment, the software product information includes the full name of the software, the abbreviation of the software, the product classification number, the product version number, the product development completion date, the product publication status, the product first publication date, the product first publication location, the product development method, the product rights acquisition method, the product rights scope, the product hardware environment, the product software environment, the product programming language, and the product program code.

[0079] Specifically, the product publication status unit includes published and unpublished options; the product development method unit includes independent development, cooperative development, commissioned development, and task development options; the product rights acquisition method unit includes original acquisition, inherited acquisition (assignment, assumption, inheritance), whether the software has been registered (original registration number), and whether the registration has been changed or supplemented (change or supplement certificate number) options; the product rights scope unit includes all and part (right of publication, right of authorship, right of modification, right of reproduction, right of distribution, right of rental, right of information network dissemination, right of translation, and other rights that should be enjoyed by the copyright owner) options.

[0080] In this embodiment, if Figure 4 As shown, the method for querying according to the identification tag through the visual interface includes:

[0081] S201, obtaining a query method corresponding to the identification tag;

[0082] S202, obtaining a corresponding preset neural network model according to the query method;

[0083] S203, inputting the query mode into the preset neural network model to obtain the user's habitual query mode information corresponding to the query in the visual interface;

[0084] S204, sending the customary query method information to a server for storage.

[0085] Specifically, the preset neural network model is a pre-trained neural network model. Since each user has different query habits, different query methods will be generated. Through training, each user will generate habitual query method information based on the input method when querying in the visual interface, so that the server will generate corresponding associated identification tag information based on each user.

[0086] Neural network is a complex network system formed by a large number of simple processing units widely connected to each other. It reflects many basic characteristics of human brain function and is a highly complex nonlinear dynamic learning system. Neural network has large-scale parallel, distributed storage and processing, self-organization, self-adaptation and self-learning capabilities. It is particularly suitable for processing imprecise and fuzzy information processing problems that need to consider many factors and conditions at the same time. The neural network model is BP neural network, which is a hierarchical neural network composed of input layer, middle layer and output layer. The middle layer can be expanded to multiple layers. The neurons between adjacent layers are fully connected, and there is no connection between neurons in each layer. The network learns in a teacher-teaching manner. When a pair of learning patterns is provided to the network, each neuron obtains the input response of the network to generate connection weights, and then corrects each connection weight from the output layer through each middle layer layer by layer in the direction of reducing the error between the desired output and the actual output, and returns to the input layer. This process is repeated and alternating until the global error of the network tends to a given minimum value, that is, the learning process is completed.

[0087] Although the present application has been described in conjunction with specific features and embodiments thereof, it is obvious that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the accompanying drawings are merely exemplary illustrations of the present application and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. Software product information management system based on big data, characterized by: include: An acquisition module, used to acquire software product status information, wherein the software product status information includes software product information, storage path information and storage time information; A conversion module, used to call the string encoding rule in the server, encode the software product information into an information string, encode the storage path information into a path string, and encode the storage time information into a time string; A storage module, used for combining the information character string, the path character string and the time character string into an exclusive software character string, and storing the exclusive software character string in a database; An identification module, used to establish a connection relationship with the database according to the exclusive software string, and generate an identification tag according to the connection relationship; A modification module, used to modify the software product status information, save it as new software product status information after the modification is completed, save the modification record information, and link the new software product status information, the modification record information and the software product status information; The query module is used to obtain the customary query method information according to the identification tag through the visual interface, match the database string corresponding to the query result after executing the query command, and then call the string decoding rule in the server to decode the database string to obtain the corresponding software product status information and the linked new software product status information and the modification record information, wherein the method for obtaining the customary query method information according to the identification tag through the visual interface includes: Obtaining a query method corresponding to the identification tag; Inputting the query mode into a trained neural network model to obtain the user's customary query mode information corresponding to the query in the visualization interface; The customary query mode information is sent to a server for storage.

2. The software product information management system based on big data according to claim 1, characterized in that: The server stores a string encoding rule module and a string decoding rule module, wherein the string encoding rule module includes an ASCII encoding unit and a GB2312 encoding unit, and the string decoding rule includes an ASCII decoding unit and a GB2312 decoding unit.

3. The software product information management system based on big data according to claim 1, characterized in that: The acquisition module includes a software product information unit, and the software product information unit includes a software full name unit, a software abbreviation unit, a product classification number unit, a product version number unit, a product development completion date unit, a product publication status unit, a product first publication date unit, a product first publication location unit, a product development method unit, a product right acquisition method unit, a product right scope unit, a product hardware environment unit, a product software environment unit, a product programming language unit, and a product program code unit.

4. A software product information management method based on big data, characterized in that: The specific steps include: S101, used to obtain software product status information, where the software product status information includes software product information, storage path information, and storage time information; S102, calling a string encoding rule in the server, encoding the software product information into an information string, encoding the storage path information into a path string, and encoding the storage time information into a time string; S103, combining the information string, the path string and the time string into a dedicated software string, and storing the dedicated software string in a database; S104, establishing a connection relationship with the database according to the exclusive software character string, and generating an identification tag according to the connection relationship; S105, modifying the software product status information, and after the modification is completed, saving it as new software product status information, and saving the modification record information, and linking the new software product status information, the modification record information and the software product status information; S106, obtaining the customary query method information according to the identification tag through the visual interface, matching the database string corresponding to the query result after executing the query command, and then calling the string decoding rule in the server to decode the database string to obtain the corresponding software product status information and the linked new software product status information and the modification record information, wherein obtaining the customary query method information according to the identification tag through the visual interface includes: Obtaining a query method corresponding to the identification tag; Inputting the query mode into a trained neural network model to obtain the user's customary query mode information corresponding to the query in the visualization interface; The customary query mode information is sent to a server for storage.

5. The software product information management method based on big data according to claim 4 is characterized in that: The string encoding rules include ASCII encoding and GB2312 encoding, and the string decoding rules include ASCII decoding and GB2312 decoding.

6. The software product information management method based on big data according to claim 5, characterized in that: The software product information includes the full name of the software, the abbreviation of the software, the product classification number, the product version number, the product development completion date, the product publication status, the product first publication date, the product first publication location, the product development method, the product rights acquisition method, the product rights scope, the product hardware environment, the product software environment, the product programming language, and the product program code.

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