A method and terminal for checking software configuration files

Abstract

This invention discloses a method and terminal for checking software configuration files. The method involves dividing the configuration file into all configuration items to obtain a preset number of configuration data segments; creating a data indexing mechanism to index any configuration data segment and any configuration item within that segment; and, in response to a check command, creating a self-checking and correction process for the corresponding configuration item based on the data indexing mechanism, and executing the self-checking and correction process. This invention, by combining segmentation processing and indexing mechanisms, effectively avoids the repeated reading and parsing of large configuration files during checks. By executing the self-checking and correction process, it updates and iterates the original configuration items, improving check efficiency.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method and terminal for checking software configuration files. Background Technology

[0002] Software configuration files must be checked before it is officially released for use, especially game configuration files, which typically contain tens of thousands of configuration items, making manual inspection difficult. Furthermore, existing configuration file checking methods can only check the current version of the configuration file and cannot adapt to frequent changes in configuration formats. Repeatedly reading and parsing large configuration files with tens of thousands of configuration items consumes significant computing resources and time. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method and terminal for checking software configuration files, which can efficiently and flexibly check configuration files with large amounts of data, and reduce the consumption of computing resources and time in the repeated reading and parsing process.

[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A method for checking software configuration files includes the following steps: Divide all configuration items within the configuration file to obtain a preset number of configuration data segments; A data indexing mechanism is created, which is used to index any of the configuration data segments and any of the configuration items in the configuration data segments; In response to the inspection command, a self-check correction process is created based on the data indexing mechanism for the configuration item corresponding to the inspection command, and the self-check correction process is executed.

[0005] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows: A software configuration file inspection terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it performs the following steps: Divide all configuration items within the configuration file to obtain a preset number of configuration data segments; A data indexing mechanism is created, which is used to index any of the configuration data segments and any of the configuration items in the configuration data segments; In response to the inspection command, a self-check correction process is created based on the data indexing mechanism for the configuration item corresponding to the inspection command, and the self-check correction process is executed.

[0006] The beneficial effects of this invention are as follows: It provides a method and terminal for checking software configuration files, dividing all configuration items within the configuration file to obtain a preset number of configuration data segments; it creates a data indexing mechanism, and by combining segmentation processing and the indexing mechanism, it can effectively avoid the situation of repeatedly reading and parsing large configuration files during the check, enabling the system to handle configuration files of any size while flexibly and purposefully performing partial checks to adapt to frequent changes in configuration formats; and, based on the data indexing mechanism, it creates a self-checking and correction process for the configuration items corresponding to the check instructions, and by executing the self-checking and correction process, it completes the update and iteration of the original configuration items, thereby improving the check efficiency. Attached Figure Description

[0007] Figure 1 A flowchart illustrating the steps of a software configuration file inspection method provided in an embodiment of the present invention; Figure 2 A system block diagram of a software configuration file checking terminal provided in an embodiment of the present invention; Figure 3 This is a system block diagram of a processor for a software configuration file checking terminal provided in an embodiment of the present invention.

[0008] 200. A terminal for checking software configuration files; 202. Memory; 204. Processor. Detailed Implementation

[0009] To make the technical problems, technical solutions, and beneficial effects to be solved by this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.

[0010] To facilitate understanding of the content of this invention, the following explanations of the terms used in this invention are provided: Configuration file: A file used to store software system settings, parameters, or options, usually stored in text or structured format.

[0011] Configuration item: The smallest independent unit in a configuration file, usually represented by a key-value pair or a specific syntax structure.

[0012] Configuration data segmentation: Divide the entire configuration file into several logical or physical blocks according to preset rules. The purpose of segmentation is to improve the processing efficiency of large configuration files and facilitate parallel checking or index management.

[0013] Data indexing mechanism: A data structure or algorithm used to quickly locate and access configuration data segments or specific configuration items.

[0014] Lexicon: The basic unit in text processing, which can refer to a word, symbol, number, or specific delimiter. The total number of lexicons is often used to measure the complexity of a configuration file.

[0015] Self-check and correction process: An automated inspection and repair process, including: locating configuration items according to inspection instructions, verifying whether their values ​​conform to rules (such as format, range, and dependencies), and automatically generating a correction script and executing the update if an anomaly is found.

[0016] Please refer to Figure 1 A method for checking software configuration files includes the following steps: Divide all configuration items within the configuration file to obtain a preset number of configuration data segments; A data indexing mechanism is created, which is used to index any of the configuration data segments and any of the configuration items in the configuration data segments; In response to the inspection command, a self-check correction process is created based on the data indexing mechanism for the configuration item corresponding to the inspection command, and the self-check correction process is executed.

[0017] As can be seen from the above description, the beneficial effects of the present invention are as follows: All configuration items within the configuration file are divided to obtain a preset number of configuration data segments; a data indexing mechanism is created, and the combined use of segmentation processing and indexing mechanisms can effectively avoid the repeated reading and parsing of large configuration files during checks, enabling the system to handle configuration files of any size while flexibly and purposefully performing partial checks to adapt to frequent changes in configuration formats; furthermore, based on the data indexing mechanism, a self-checking and correction process is created for the configuration items corresponding to the check instructions. By executing the self-checking and correction process, the original configuration items are updated and iterated, improving check efficiency.

[0018] Also includes: Obtain the maximum number of word inputs, and multiply the maximum number of word inputs by a preset safety coefficient to obtain the warning value of the word inputs. If the total number of tokens in the configuration file exceeds the token input warning value, then the preset number N for dividing the configuration file is set as follows: N = ceil(T_total / T_safe); Where T_total represents the total number of tokens in the configuration file, and T_safe represents the warning value for the number of token inputs; If the total number of tokens in the configuration file is less than or equal to the token input warning value, then the preset number for dividing the configuration file is set to 1.

[0019] As described above, by introducing a dynamic threshold—the lexical input quantity warning value—and using the size of the configuration file as the basis for segmentation decisions, intelligent and adaptive determination of the preset number of segments is achieved. This avoids the problems of insufficient processing of large files and excessive processing of small files that may arise from using a fixed number of segments. It ensures that the segmentation strategy can cope with the performance challenges of large-scale configuration files while maintaining lightweight processing for small-scale configuration files, thus optimizing resource allocation and processing efficiency.

[0020] Furthermore, the data index creation mechanism includes: Create a first indexing mechanism for indexing any of the configuration data segments, wherein the first indexing mechanism is used to set a unique identifier that corresponds one-to-one with the configuration data segments; Create a second indexing mechanism for indexing any of the configuration items from the configuration data segments, the second indexing mechanism comprising: Based on the inspection instructions, determine the keywords, and segment all the configuration data containing the keywords as the target data segments; Extract configuration structure features from the inspection instructions; Based on the configuration structure characteristics, the configuration item pointed to by the inspection instruction is indexed from the target data segment.

[0021] As described above, by explicitly dividing the data indexing mechanism into two levels—a first indexing mechanism and a second indexing mechanism—a unique identifier is assigned to each configuration data segment under the first indexing mechanism. Under the second indexing mechanism, keywords are used for initial filtering within the target segment, quickly narrowing down the range of candidate configuration items. Then, precise matching is performed by combining the configuration structure features extracted from the inspection instructions. This method effectively solves the ambiguity problems that may be encountered by relying solely on keywords, greatly improving the accuracy of the index and the correctness of intent understanding.

[0022] Furthermore, the determination of keywords includes: Based on the software scenario to which the configuration file belongs, the relevance threshold is obtained; A sample set consisting of at least two types of sample words is pre-defined; The relevance of the inspection instruction to each sample word in the sample set is compared, and the sample words whose relevance reaches the relevance threshold are taken as the keywords corresponding to the inspection instruction.

[0023] As described above, by dynamically adjusting the "relevance threshold" according to different software scenarios, the strictness of keyword matching can adapt to the differences and complexities of configuration languages ​​in different scenarios. Furthermore, by pre-setting a sample set containing multiple possible keywords and calculating the relevance between the check command and each sample, the most matching keyword can be intelligently selected, rather than relying on simple string inclusion judgments.

[0024] Furthermore, the self-check correction process for creating the configuration item corresponding to the check instruction includes: Create a script to generate the model; Obtain inspection requirement information from the inspection instructions, and determine the corresponding configuration items based on the inspection requirement information and the data indexing mechanism; Input the inspection requirements information and the configuration items into the script generation model, and output the verification script. The configuration item is verified by the verification script. If the verification result is that the configuration item is abnormal, the abnormal configuration item is input into the script generation model and a correction script is output. The correction script is used to update the configuration item.

[0025] As described above, the self-check and correction process is concretized into a complete automated closed loop. Its core benefit lies in achieving intelligent and highly automated checking and repair. The system can dynamically generate targeted verification scripts based on abstract check requirements, eliminating the need to pre-write all check rules and demonstrating strong adaptability. When anomalies are detected, correction scripts can be automatically generated, achieving automated operation and maintenance capabilities of "solving problems as soon as they are discovered." This significantly reduces the need for manual intervention, improves the efficiency and reliability of configuration management, and lowers the risk of human error.

[0026] Please refer to Figure 2 and Figure 3 A software configuration file inspection terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps: Divide all configuration items within the configuration file to obtain a preset number of configuration data segments; A data indexing mechanism is created, which is used to index any of the configuration data segments and any of the configuration items in the configuration data segments; In response to the inspection command, a self-check correction process is created based on the data indexing mechanism for the configuration item corresponding to the inspection command, and the self-check correction process is executed.

[0027] As can be seen from the above description, the beneficial effects of the present invention are as follows: All configuration items within the configuration file are divided to obtain a preset number of configuration data segments; a data indexing mechanism is created, and the combined use of segmentation processing and indexing mechanisms can effectively avoid the repeated reading and parsing of large configuration files during checks, enabling the system to handle configuration files of any size while flexibly and purposefully performing partial checks to adapt to frequent changes in configuration formats; furthermore, based on the data indexing mechanism, a self-checking and correction process is created for the configuration items corresponding to the check instructions. By executing the self-checking and correction process, the original configuration items are updated and iterated, improving check efficiency.

[0028] Also includes: Obtain the maximum number of word inputs, and multiply the maximum number of word inputs by a preset safety coefficient to obtain the warning value of the word inputs. If the total number of tokens in the configuration file exceeds the token input warning value, then the preset number N for dividing the configuration file is set as follows: N = ceil(T_total / T_safe); Where T_total represents the total number of tokens in the configuration file, and T_safe represents the warning value for the number of token inputs; If the total number of tokens in the configuration file is less than or equal to the token input warning value, then the preset number for dividing the configuration file is set to 1.

[0029] As described above, by introducing a dynamic threshold—the lexical input quantity warning value—and using the size of the configuration file as the basis for segmentation decisions, intelligent and adaptive determination of the preset number of segments is achieved. This avoids the problems of insufficient processing of large files and excessive processing of small files that may arise from using a fixed number of segments. It ensures that the segmentation strategy can cope with the performance challenges of large-scale configuration files while maintaining lightweight processing for small-scale configuration files, thus optimizing resource allocation and processing efficiency.

[0030] Furthermore, the data index creation mechanism includes: Create a first indexing mechanism for indexing any of the configuration data segments, wherein the first indexing mechanism is used to set a unique identifier that corresponds one-to-one with the configuration data segments; Create a second indexing mechanism for indexing any of the configuration items from the configuration data segments, the second indexing mechanism comprising: Based on the inspection instructions, determine the keywords, and segment all the configuration data containing the keywords as the target data segments; Extract configuration structure features from the inspection instructions; Based on the configuration structure characteristics, the configuration item pointed to by the inspection instruction is indexed from the target data segment.

[0031] As described above, by explicitly dividing the data indexing mechanism into two levels—a first indexing mechanism and a second indexing mechanism—a unique identifier is assigned to each configuration data segment under the first indexing mechanism. Under the second indexing mechanism, keywords are used for initial filtering within the target segment, quickly narrowing down the range of candidate configuration items. Then, precise matching is performed by combining the configuration structure features extracted from the inspection instructions. This method effectively solves the ambiguity problems that may be encountered by relying solely on keywords, greatly improving the accuracy of the index and the correctness of intent understanding.

[0032] Furthermore, the determination of keywords includes: Based on the software scenario to which the configuration file belongs, the relevance threshold is obtained; A sample set consisting of at least two types of sample words is pre-defined; The relevance of the inspection instruction to each sample word in the sample set is compared, and the sample words whose relevance reaches the relevance threshold are taken as the keywords corresponding to the inspection instruction.

[0033] As described above, by dynamically adjusting the "relevance threshold" according to different software scenarios, the strictness of keyword matching can adapt to the differences and complexities of configuration languages ​​in different scenarios. Furthermore, by pre-setting a sample set containing multiple possible keywords and calculating the relevance between the check command and each sample, the most matching keyword can be intelligently selected, rather than relying on simple string inclusion judgments.

[0034] Furthermore, the self-check correction process for creating the configuration item corresponding to the check instruction includes: Create a script to generate the model; Obtain inspection requirement information from the inspection instructions, and determine the corresponding configuration items based on the inspection requirement information and the data indexing mechanism; Input the inspection requirements information and the configuration items into the script generation model, and output the verification script. The configuration item is verified by the verification script. If the verification result is that the configuration item is abnormal, the abnormal configuration item is input into the script generation model and a correction script is output. The correction script is used to update the configuration item.

[0035] As described above, the self-check and correction process is concretized into a complete automated closed loop. Its core benefit lies in achieving intelligent and highly automated checking and repair. The system can dynamically generate targeted verification scripts based on abstract check requirements, eliminating the need to pre-write all check rules and demonstrating strong adaptability. When anomalies are detected, correction scripts can be automatically generated, achieving automated operation and maintenance capabilities of "solving problems as soon as they are discovered." This significantly reduces the need for manual intervention, improves the efficiency and reliability of configuration management, and lowers the risk of human error.

[0036] Please refer to Figure 1 Embodiment 1 of the present invention is as follows: A method 100 for checking software configuration files, applicable to configuration file checks in various scenarios such as big data platforms, network tools, and games, includes the following steps 102 to 106: In step 102, all configuration items in the configuration file are divided to obtain a preset number of configuration data segments.

[0037] Especially for game software, the configuration file data is enormous, so segmented processing is adopted. As a preferred segmented processing method, the maximum word input size T_max is obtained; the maximum word input size is multiplied by a preset safety coefficient α to obtain the word input size warning value T_safe, the expression of which is as follows: T_safe = α × T_max.

[0038] It's worth noting that the maximum token input size represents the maximum number of tokens allowed by a large model running check method 100. The token input size warning value is a pre-set threshold for the number of tokens used to evaluate the configuration file size. To avoid program crashes, reduce data pressure, and ensure normal program operation, a preset safety factor is used to allow space for other data inputs and outputs. For example, based on practical experience in large model applications, 20% of the token space is reserved, with system prompts and commands (approximately 5-10%) and model output responses (approximately 10-15%), i.e., a preset safety factor α of 0.8, which is commonly used in best practices by large model vendors such as OpenAI and Anthropic. Furthermore, by comparing the total number of tokens in the configuration file with the token input size warning value, the preset number is obtained based on the comparison results, as follows: When T_total > T_safe, the preset number N_segments is: N_segments = ceil(T_total / T_safe).

[0039] Where T_total represents the total number of tokens in the configuration file.

[0040] The target number of tokens T_segment_target for each segment of configuration data is as follows: T_segment_target = ceil(T_total / N_segments).

[0041] It should be noted that when dividing the configuration data into segments, this embodiment strictly follows the principle of semantic integrity to ensure the integrity of the configuration items and avoid splitting a complete configuration item into different configuration data segments.

[0042] In step 104, a data indexing mechanism is created to index any configuration data segment and any configuration item within the configuration data segment.

[0043] In this embodiment, a first indexing mechanism is created for indexing any configuration data segment; a second indexing mechanism is created for indexing any configuration item from the configuration data segments. The first indexing mechanism is a segment-oriented index, typically assigning a unique identifier to each segment to directly locate the target segment. The second indexing mechanism is an item-level index, used to find specific configuration items within a specified segment. It may achieve precise indexing based on keyword matching, structural features, or contextual information.

[0044] The first indexing mechanism includes: setting a unique identifier that corresponds one-to-one with each configuration data segment. The second indexing mechanism includes: determining keywords based on the inspection instruction, identifying all configuration data segments containing the keywords; extracting configuration structure features from the inspection instruction; and indexing the configuration item pointed to by the inspection instruction from all identified configuration data segments based on the configuration structure features.

[0045] When determining keywords, a relevance threshold θ is obtained based on the software scenario to which the configuration file belongs. The relevance threshold is used to measure the numerical boundary of text similarity. When determining keywords, the similarity between the check instruction and sample keywords is calculated (e.g., cosine similarity, edit distance), and a match is considered only if the similarity reaches this threshold.

[0046] In this embodiment, a sample set consisting of at least two types of keywords is preset. The relevance of the inspection command to each keyword in the sample set is compared, and the keyword corresponding to the inspection command is determined based on the relevance reaching a relevance threshold. Relevance refers to the semantic relevance between the user-submitted inspection command and the configured data segments, used to achieve intelligent retrieval. When a user submits a specific inspection request in the inspection command, such as "check the price of all consumables," instead of blindly processing all configured data segments, the pre-built index is used to calculate the relevance score between the requested keyword, such as "consumables," and the keywords in the sample set.

[0047] The relevance threshold θ serves as a filtering standard. The system only selects keywords when their relevance scores to the sample set reach or exceed 0.6. Based on experience in information retrieval, a balance is struck between recall and precision: θ < 0.4 indicates high recall but high noise; θ > 0.8 indicates high precision but potential for missed detections; and θ = 0.6 has been proven to be optimal in game-based scenarios.

[0048] In step 106, in response to the inspection command, a self-check correction process is created based on the data indexing mechanism for the configuration item corresponding to the inspection command, and the self-check correction process is executed.

[0049] In this embodiment, inspection requirement information is obtained from the inspection instruction; the configuration item corresponding to the inspection instruction is determined through a first indexing mechanism and a second indexing mechanism; and a verification script is created based on the inspection requirement information. The inspection requirement information includes at least the semantic information of the configuration item and the user's natural language requirement, such as "check the attribute balance of all professional roles".

[0050] When creating the script, integrate the following information into a complete "hint word", as follows: User natural language requirements: For example, "Check the attribute balance of all job roles".

[0051] The relevant configuration segment contains specific configuration data for professions such as "warrior" and "mage", obtained through index retrieval.

[0052] Configuration structure features: The extracted structure key, such as `"characters.warrior.attack"`, provides clear guidance for the model to generate parsing code.

[0053] Next, the large model is generated: the above prompts are submitted to the large language model. Based on its understanding of programming, configuration formats, and requirements, the model generates an executable code (such as a Python script), i.e., a validation script. The validation script is an executable code (such as a Python script or a shell command) used to check the validity of configuration items. The script can implement checks based on a rule engine, regular expressions, or business logic.

[0054] In this embodiment, the configuration items corresponding to the verification script are checked. If the check result indicates that the configuration item is abnormal, a correction script is created based on the abnormality. The correction script is an automatically generated repair program used to update the abnormal configuration item to the correct value. This can be achieved through file replacement, API calls, or configuration management tools.

[0055] The correction template for the correction script can be selected in the following forms: The corrected template consists of: prompt text + original requirements + configuration instructions + error script + exception information + execution context.

[0056] Based on this, the captured exception information (including error type, message, stack trace, etc.) is combined with the original requirements, configuration instructions, and the erroneous script code to populate a preset "correction template," generating a detailed "correction prompt." This prompt is then submitted to the large model, which analyzes the cause of the error based on this new contextual information and modifies the original verification script, thereby outputting an optimized new script.

[0057] Regarding the correction process, this embodiment proposes a correction loop control: the maximum number of correction attempts N_retry=3, based on the following engineering considerations: the success rate of the first correction is about 60-70%; the cumulative success rate of the second correction is about 85-90%; the cumulative success rate of the third correction is about 95% or more. More than three corrections usually require manual intervention to avoid infinite loops.

[0058] Embodiment 2 of the present invention is as follows: A method for checking software configuration files, based on the above embodiment one, specifically adopts a keyword frequency weighting calculation process when determining all configuration data segments containing keywords, as detailed below: A method combining TF-IDF and configuration structure analysis is employed: For configuration data segment S_i, keyword weight calculation: weight(t, S_i) = TF(t, S_i) × log(N / DF(t)).

[0059] Where TF(t, S_i) represents the frequency of keyword t in the configuration data segment S_i, N represents the preset number, and DF(t) represents the number of segments containing word t.

[0060] Then, configuration structure features are extracted from the inspection instructions. For example, for JSON format, this embodiment traverses all levels to extract the complete path pointing to the final value (leaf node). For XML format, this embodiment extracts the XPath path containing the actual text content. For key-value pair format, the key name of each line is extracted directly.

[0061] It should be noted that keywords and configuration structure features together constitute the "identity information" describing a configuration data segment, and are stored together in the secondary index to serve subsequent retrieval. Configuration structure features are formal and precise; they describe the "address" of configuration items, primarily used for precise location. Keywords are semantic and fuzzy; they describe the "content features" of configuration items, primarily used for semantic matching and retrieval. Configuration data segments with too low a frequency weight are filtered out. Finally, based on the configuration structure features, the index checks the configuration items pointed to by the instructions from all identified configuration data segments.

[0062] Embodiment 3 of the present invention is as follows: A method for checking software configuration files, based on the above embodiment one or two, integrates the execution records of the self-check and correction process to generate an inspection report.

[0063] In this embodiment, configuration anomalies of configuration items include, but are not limited to, the following: Segment identification information: segment ID, corresponding source file and location.

[0064] Check the execution status: "Success", "Failure", "Terminated due to an exception".

[0065] List of issues found: Each issue should include: Issue type: such as "value out of bounds", "missing configuration item", "incorrect data type". Configuration item location: characteristics of the erroneous configuration structure.

[0066] Detailed description: Expected behavior versus actual behavior.

[0067] Severity level: "High risk", "Medium risk", "Low risk".

[0068] Check the execution metadata: performance metrics such as script execution time, number of configuration items checked, and memory usage.

[0069] When generating inspection reports, the structure of the inspection report can be made more concise by merging duplicate or related issues.

[0070] Please refer to Figure 2 and Figure 3 Embodiment four of the present invention is as follows: A software configuration file checking terminal 200 includes a memory 202, a processor 204, and a computer program stored in the memory 202 and executable on the processor 204. When the processor 204 executes the computer program, it implements a software configuration file checking method according to Embodiment 1, 2, or 3.

[0071] like Figure 3 As shown, processor 204 includes an input module and a processing module.

[0072] The input module, connected to the processing module, is used to obtain configuration files and check instructions; The processing module is used to execute a method for checking a software configuration file according to Embodiment 1, 2, or 3.

[0073] In this embodiment, the processing module is divided into three modules: core processing, execution, and output. Taking the character configuration check of a massively multiplayer online game as an example, when the processing module executes a software configuration file check method, it completes the following: 1. Requirements Input The planner submitted an inspection instruction: "Check the attribute balance of all professional roles to ensure that the differences in basic attributes between different professions are within a reasonable range."

[0074] 2. Configuration processing The system identifies the role configuration file "CharacterSystem.json", which is 2.1MB in size; calculates the number of tokens: T_total=18,500 (assuming T_max=8,000, T_safe=6,400); and processes them in segments: N_segments=ceil(18500 / 6400)=3 segments.

[0075] 3. Index Directory Construction Extract keywords: {"warrior","mage","attack_power","defense","hp_max"}; Extract configuration structure features: {"characters.warrior.base_attack","characters.mage.spell_power"}; Build index: Establish mapping relationships between occupation → segment and attribute → segment.

[0076] 4. Script execution A script is generated to check the attribute balance. Upon execution, it is found that the warrior class's defense value exceeds the reasonable upper limit, and the abnormal value range is detected, triggering the correction mechanism. After correction, the script is successfully executed and a detailed report is generated.

[0077] In summary, the software configuration file inspection method and terminal provided by this invention effectively solves the performance impact of large configuration files on the processing system by dividing the configuration file into semantically complete configuration data segments within a security boundary through an adaptive segmentation mechanism based on large model processing capabilities. Next, by constructing a two-layer index that integrates semantic keywords and precise structural features, the system can quickly and accurately locate target configuration items from massive configurations, overcoming the problems of low accuracy in fuzzy queries and slow location in complex structures found in traditional methods. In the core processing stage, the system dynamically generates executable verification and correction scripts based on the index results and user natural language commands, realizing "on-demand generation" of inspection rules and repair logic without the need for pre-setting massive hard-coded rules, thus possessing strong adaptability and flexibility. Finally, by integrating execution records and anomaly information to generate a structured inspection report and setting a maximum number of attempts for the correction process, an intelligent closed loop of "inspection-location-correction-verification-reporting" is formed, ensuring process controllability and auditability while achieving high-efficiency automation.

[0078] The above are merely embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention's specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for checking software configuration files, characterized in that, Includes the following steps: Divide all configuration items within the configuration file to obtain a preset number of configuration data segments; A data indexing mechanism is created, which is used to index any of the configuration data segments and any of the configuration items in the configuration data segments; In response to the inspection command, a self-check correction process is created based on the data indexing mechanism for the configuration item corresponding to the inspection command, and the self-check correction process is executed.

2. The method for checking software configuration files according to claim 1, characterized in that, Also includes: Obtain the maximum number of word inputs, and multiply the maximum number of word inputs by a preset safety coefficient to obtain the word input warning value; If the total number of tokens in the configuration file exceeds the token input warning value, then the preset number N for dividing the configuration file is set as follows: N = ceil(T_total / T_safe); Where T_total represents the total number of tokens in the configuration file, and T_safe represents the warning value for the number of token inputs; If the total number of tokens in the configuration file is less than or equal to the token input warning value, then the preset number for dividing the configuration file is set to 1.

3. The method for checking software configuration files according to claim 1, characterized in that, The data index creation mechanism includes: Create a first indexing mechanism for indexing any of the configuration data segments, wherein the first indexing mechanism is used to set a unique identifier that corresponds one-to-one with the configuration data segments; Create a second indexing mechanism for indexing any of the configuration items from the configuration data segments, the second indexing mechanism comprising: Based on the inspection instructions, determine the keywords, and segment all the configuration data containing the keywords as the target data segments; Extract configuration structure features from the inspection instructions; Based on the configuration structure characteristics, the configuration item pointed to by the inspection instruction is indexed from the target data segment.

4. The method for checking software configuration files according to claim 3, characterized in that, The keywords to be determined include: Based on the software scenario to which the configuration file belongs, the relevance threshold is obtained; A sample set consisting of at least two types of sample words is pre-defined; The relevance of the inspection instruction to each sample word in the sample set is compared, and the sample words whose relevance reaches the relevance threshold are taken as the keywords corresponding to the inspection instruction.

5. The method for checking software configuration files according to claim 1, characterized in that, The self-check correction process for creating the configuration item corresponding to the check command includes: Create a script to generate the model; Obtain inspection requirement information from the inspection instructions, and determine the corresponding configuration items based on the inspection requirement information and the data indexing mechanism; Input the inspection requirements information and the configuration items into the script generation model, and output the verification script. The configuration item is verified by the verification script. If the verification result is that the configuration item is abnormal, the abnormal configuration item is input into the script generation model and a correction script is output. The correction script is used to update the configuration item.

6. A terminal for checking software configuration files, characterized in that, Includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, performs the following steps: Divide all configuration items within the configuration file to obtain a preset number of configuration data segments; A data indexing mechanism is created, which is used to index any of the configuration data segments and any of the configuration items in the configuration data segments; In response to the inspection command, a self-check correction process is created based on the data indexing mechanism for the configuration item corresponding to the inspection command, and the self-check correction process is executed.

7. A software configuration file inspection terminal according to claim 6, characterized in that, Also includes: Obtain the maximum number of word inputs, and multiply the maximum number of word inputs by a preset safety coefficient to obtain the word input warning value; If the total number of tokens in the configuration file exceeds the token input warning value, then the preset number N for dividing the configuration file is set as follows: N = ceil(T_total / T_safe); Where T_total represents the total number of tokens in the configuration file, and T_safe represents the warning value for the number of token inputs; If the total number of tokens in the configuration file is less than or equal to the token input warning value, then the preset number for dividing the configuration file is set to 1.

8. A software configuration file inspection terminal according to claim 6, characterized in that, The data index creation mechanism includes: Create a first indexing mechanism for indexing any of the configuration data segments, wherein the first indexing mechanism is used to set a unique identifier that corresponds one-to-one with the configuration data segments; Create a second indexing mechanism for indexing any of the configuration items from the configuration data segments, the second indexing mechanism comprising: Based on the inspection instructions, determine the keywords, and segment all the configuration data containing the keywords as the target data segments; Extract configuration structure features from the inspection instructions; Based on the configuration structure characteristics, the configuration item pointed to by the inspection instruction is indexed from the target data segment.

9. A software configuration file inspection terminal according to claim 8, characterized in that, The keywords to be determined include: Based on the software scenario to which the configuration file belongs, the relevance threshold is obtained; A sample set consisting of at least two types of sample words is pre-defined; The relevance of the inspection instruction to each sample word in the sample set is compared, and the sample words whose relevance reaches the relevance threshold are taken as the keywords corresponding to the inspection instruction.

10. A software configuration file inspection terminal according to claim 6, characterized in that, The self-check correction process for creating the configuration item corresponding to the check command includes: Create a script to generate the model; Obtain inspection requirement information from the inspection instructions, and determine the corresponding configuration items based on the inspection requirement information and the data indexing mechanism; Input the inspection requirements information and the configuration items into the script generation model, and output the verification script. The configuration item is verified by the verification script. If the verification result is that the configuration item is abnormal, the abnormal configuration item is input into the script generation model and a correction script is output. The correction script is used to update the configuration item.

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