An embedded database programming method

Abstract

The present application relates to the field of computer software development and database technology, in particular to a kind of embedded database programming method, including intent model construction step: scanning source code identifies embedded syntax block, constructs abstract syntax tree and peels off bottom drive, generates drive independent intent model;Logic sequence synthesis step: inject dialect parameter and resource strategy, synthesis execution logic sequence and generate target code;Fingerprint checking step: intercept request in runtime, calculate structure fingerprint and carry out consistency check with benchmark fingerprint;Binding execution step: execute request after checking, establish weak reference life cycle binding of resource object and host variable.The present application eliminates the risk of resource leakage, and enhances the robustness of system under long time running.

Description

Technical Field

[0001] This invention relates to the fields of computer software development and database technology, specifically to an embedded database programming method. Background Technology

[0002] In the daily development and operation of database application systems, the host program needs to frequently interact with the underlying database to achieve persistent data storage and retrieval. The efficiency and security of the application largely depend on the parsing method of the data manipulation statements embedded in the source code and the lifecycle management mechanism of the database connection resources.

[0003] In the traditional approach, data manipulation usually relies on direct calls to specific database drivers or constructing execution commands through string concatenation. This approach is highly coupled with the underlying driver. When faced with heterogeneous database switching or complex runtime attacks, it is not only prone to security vulnerabilities caused by structural tampering, but also often causes resource leaks due to the asynchronous lifecycles of resource objects and host variables, resulting in low system robustness. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides an embedded database programming method. Specifically, the technical solution of this invention includes:

[0005] The input source code stream is scanned to identify embedded data manipulation syntax blocks contained therein;

[0006] Syntax parsing is performed on embedded data operation syntax blocks to construct an abstract syntax tree. Based on the abstract syntax tree, the underlying driver code is stripped away to generate a data operation intent model that is independent of the driver.

[0007] The preset database dialect parameters and resource management strategies are injected into the data operation intent model to synthesize an execution logic sequence containing complete execution logic.

[0008] The embedded data manipulation syntax blocks in the source code stream are replaced with standard function calls pointing to the execution logic sequence to generate the target executable code;

[0009] During the execution of the target code, the current data operation request is intercepted, and the runtime structure fingerprint of the data operation request is calculated;

[0010] The runtime structure fingerprint is compared with the baseline fingerprint generated based on the data operation intent model to verify structural consistency.

[0011] If the structural consistency check passes, execute the data operation request and establish a weak reference lifecycle binding between the generated database resource object and the host variable.

[0012] Preferably, based on the abstract syntax tree, the underlying driver code is stripped away to generate a data manipulation intent model independent of the driver, including:

[0013] Traverse the abstract syntax tree to extract logical nodes that represent the intent of data manipulation and parameter nodes that represent bound variables;

[0014] Remove resource management nodes from the abstract syntax tree that involve database connection establishment, cursor creation, and resource closure; based on the retained logical nodes and parameter nodes, reconstruct and generate a data operation intent model.

[0015] Preferably, preset database dialect parameters and resource management strategies are injected into the data operation intent model to synthesize an execution logic sequence containing complete execution logic, including:

[0016] Based on the database dialect parameters, the general logical nodes in the data operation intent model are converted into dialect grammatical structures specific to the database type.

[0017] Based on the resource management strategy, exception handling logic and connection pool acquisition logic are embedded in the dialect syntax structure to generate the execution logic sequence.

[0018] Preferably, the structural consistency verification between the runtime structural fingerprint and the baseline fingerprint generated based on the data operation intent model includes:

[0019] If the runtime structural fingerprint completely matches the baseline fingerprint, the data operation request is determined to be a legitimate request, and the structural consistency check is confirmed to have passed.

[0020] If the runtime structural fingerprint does not match the baseline fingerprint, the data operation request is deemed to contain the risk of injection attack, and the structural consistency verification is determined to have failed.

[0021] Preferably, in the event that the structural consistency check fails, the data operation request is intercepted and the subsequent execution of the execution logic sequence is terminated.

[0022] Preferably, a weak reference lifecycle binding is established between the generated database resource object and the host variable, including:

[0023] By leveraging the weak reference mechanism of programming languages, weak reference proxies pointing to database resource objects can be created.

[0024] Register weak reference proxies to the destructor callback interface of the host variable to ensure that the lifecycle of the database resource object strictly follows the scope of the host variable.

[0025] Preferably, the memory reference count status of the host variable is monitored in real time; when the host variable is detected to have been garbage collected, the destructor callback interface is triggered.

[0026] Weak reference proxies are used to force the closing of database resource objects and the return of database connections.

[0027] Preferably, during the construction of the abstract syntax tree, the location of dynamic variables in the embedded data manipulation syntax block is identified;

[0028] Mark all dynamic variable positions as parameterized placeholders to prevent string concatenation operations in the execution logic sequence.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. This invention achieves complete decoupling between business logic and specific database implementation by stripping the underlying driver code based on an abstract syntax tree and constructing a data operation intent model independent of the driver; it achieves the effect of adapting to heterogeneous databases simply by injecting different dialect parameters; compared with the programming methods in the prior art that are highly dependent on specific driver interfaces, it can automatically synthesize a sequence containing complete execution logic according to a preset strategy, solving the problem that traditional methods require large-scale code reconstruction when migrating or switching databases, and significantly improving code portability and maintenance efficiency;

[0031] 2. This invention achieves robust security protection for data operation requests through a structural consistency verification mechanism between runtime structural fingerprints and baseline fingerprints; it achieves the effect of real-time identification and interception of structural tampering or injection attacks during operation; compared with traditional defense methods that rely solely on parameterized queries, it adopts a normalized calculation logic that separates structure and data and a virtual bracket injection algorithm, which can anchor the syntactic skeleton of the code, effectively preventing logical anomalies caused by malicious splicing, and solving deep security risks in complex runtime environments;

[0032] 3. This invention achieves automated and precise management of database connection resources by establishing a weak reference lifecycle binding between database resource objects and host variables; it achieves the effect that the lifecycle of resource objects strictly follows the scope of host variables and forces the release of underlying resources when host variables are garbage collected; compared with the shortcomings of existing technologies that rely on developers to manually close connections, which are prone to omissions, the asynchronous cleanup mechanism of virtual reference proxy and reference queue eliminates the risk of resource leakage and enhances the robustness of the system under long-term operation.

[0033] 4. This invention achieves passive security compliance at the code level by implementing context-aware forced parameterization during the construction of the abstract syntax tree and prohibiting string concatenation operations in the execution sequence; it achieves the effect of forcibly converting dynamic variables into standard parameter binding nodes and eliminating the hidden dangers of insecure concatenation; and it differs from existing technologies that lack dynamic... Compared to the strict constraints of the build process, by identifying valid semantic context and performing expression flattening, it ensures that all data interactions comply with security specifications and solves the security vulnerability problem caused by developer negligence. Attached Figure Description

[0034] The present invention will be further explained below with reference to the accompanying drawings and embodiments:

[0035] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0037] Example 1

[0038] Please see Figure 1 An embedded database programming method, comprising:

[0039] The input source code stream is scanned to identify embedded data manipulation syntax blocks contained therein;

[0040] Syntax parsing is performed on embedded data operation syntax blocks to construct an abstract syntax tree. Based on the abstract syntax tree, the underlying driver code is stripped away to generate a data operation intent model that is independent of the driver.

[0041] The preset database dialect parameters and resource management strategies are injected into the data operation intent model to synthesize an execution logic sequence containing complete execution logic.

[0042] The embedded data manipulation syntax blocks in the source code stream are replaced with standard function calls pointing to the execution logic sequence to generate the target executable code;

[0043] During the execution of the target's code, the current data operation request is intercepted, and the runtime structure fingerprint of the data operation request is calculated.

[0044] The runtime structure fingerprint is compared with the baseline fingerprint generated based on the data operation intent model to verify structural consistency.

[0045] If the structural consistency check passes, execute the data operation request and establish a weak reference lifecycle binding between the generated database resource object and the host variable.

[0046] This embodiment elaborates on the core execution logic of the embedded database programming method, which introduces a compile-time intermediate layer and treats database operations in the source code as intent declarations.

[0047] The system scans the input source code stream, which originates from a raw text file containing a mixture of host language and database operation statements with specific tags. During this process, the system identifies embedded data manipulation syntax blocks within the source code. This syntax block is used to encapsulate data interaction logic;

[0048] The system performs syntax parsing on the embedded data operation syntax blocks to construct an abstract syntax tree, and then strips the underlying driver code based on the abstract syntax tree to generate a data operation intent model that is independent of the driver.

[0049] This model is a logical structure that purely describes business intent. It identifies and removes all initialization, connection configuration, and cursor allocation nodes that involve specific database drivers by traversing the abstract syntax tree, and retains only the core nodes that represent the data topology, thereby achieving logical decoupling.

[0050] The system injects preset database dialect parameters and resource management strategies into the data operation intent model, and synthesizes an execution logic sequence containing complete execution logic.

[0051] Among them, the database dialect parameter comes from the unique syntax rule configuration of the target database, and the resource management strategy comes from the predefined connection pool acquisition rules and exception capture level. The system weaves the above parameters and strategies into the intent model to generate a complete code block that is tightly sealed.

[0052] Based on this, the system replaces the embedded data manipulation syntax blocks in the source code stream with standard function calls pointing to the execution logic sequence, generating the target execution code, which internally contains automatically generated robust code.

[0053] During the execution of the target code, the system intercepts the current data operation request and calculates the runtime structure fingerprint of the data operation request. To ensure the reproducibility of the fingerprint calculation, this step adopts specific structure-data separation calculation logic:

[0054] The system calls the lightweight lexical analyzer to Text stream decomposition into Sequence; perform structure normalization processing, traverse. The sequence replaces all string literals, numeric constants, and dynamic variables with predefined placeholders of a uniform type, such as... At the same time, strictly retain , The original topological order of keywords, parentheses, and operators;

[0055] Normalized Sequence input hashing algorithms, such as Generate a unique representation of this A 64-bit integer fingerprint of the logical skeleton; this method effectively shields the fingerprint from the influence of specific query parameter values, anchoring only the syntax structure of the code;

[0056] The system will perform a structural consistency check between the runtime structural fingerprint and the baseline fingerprint generated based on the data operation intent model;

[0057] In response to the successful structural consistency check, the system executes the data operation request and establishes a weak reference lifecycle binding between the generated database resource object and the host variable.

[0058] This embodiment eliminates the two major security risks of structural tampering and resource leakage at the source by performing dual verification at compile time and runtime, and verifies the robustness of this technical solution in complex heterogeneous database environments.

[0059] Example 2

[0060] Based on the abstract syntax tree, the underlying driver code is extracted to generate a data manipulation intent model that is independent of the driver, including:

[0061] Traverse the abstract syntax tree to extract logical nodes that represent the intent of data manipulation and parameter nodes that represent bound variables;

[0062] Remove resource management nodes from the abstract syntax tree that involve database connection establishment, cursor creation, and resource closure;

[0063] Based on the retained logical nodes and parameter nodes, the data operation intent model is reconstructed.

[0064] This embodiment further specifies the steps for generating the data manipulation intent model, and its reconstruction process follows the principle of minimum information entropy.

[0065] The system traverses the abstract syntax tree to extract logical nodes representing the intent of data manipulation and parameter nodes representing bound variables; this process typically employs a depth-first traversal algorithm, where logical nodes refer to... The core semantics, the parameter node refers to The variable placeholder in the middle is used as an input condition;

[0066] The system removes resource management nodes from the abstract syntax tree that involve database connection establishment, cursor creation, and resource closure. These nodes are marked as noise nodes by the system because they belong to implementation details rather than business intent, and are therefore completely removed from the tree structure.

[0067] Based on the retained logical nodes and parameter nodes, the system reconstructs and generates a data operation intent model, and relinks the remaining clean nodes to form a graph structure independent of specific drivers; this reconstruction process specifically executes a topology repair algorithm:

[0068] When a resource management node is removed At that time, the system obtains its parent node. and the set of all child nodes ;

[0069] System check exist Type constraints of the slot; if the slot supports a list of nodes, such as... of The system performs a list flattening operation, transforming the list into a flattened list. All nodes are inserted in their original time sequence. child node list The original index position is used to maintain the linear continuity of the execution flow;

[0070] If the slot only supports a single node, such as of Slot, the system creates a composite block section ,Will The components are encapsulated in this synthesizer, and then the synthesizer is mounted to... The corresponding slot;

[0071] Through this container adaptation mechanism, the system fills the structural gaps caused by the removal of nodes, and maintains the semantic integrity and type safety of the syntax tree while strictly maintaining the relative execution order between child nodes.

[0072] This embodiment achieves an idealized result by removing the resource management node. The model makes business intent no longer limited by a specific database driver version or type, greatly improving code portability.

[0073] Example 3

[0074] Preset database dialect parameters and resource management strategies are injected into the data operation intent model to synthesize an execution logic sequence containing complete execution logic, including:

[0075] Based on the database dialect parameters, the general logical nodes in the data operation intent model are converted into dialect grammatical structures specific to the database type.

[0076] Based on the resource management strategy, exception handling logic and connection pool acquisition logic are embedded into the dialect syntax structure to generate an execution logic sequence.

[0077] This embodiment is a further specification of the execution logic sequence synthesis step, which is implemented through a knowledge-driven template injection mechanism;

[0078] The system converts the general logical nodes in the data operation intent model into dialect grammatical structures specific to the database type based on the database dialect parameters.

[0079] During this process, the system maintains a detailed dialect mapping library, which stores common dialects in key-value pairs. Node types, such as pagination query nodes, Nodes, and specific databases, such as , of Syntax template;

[0080] The conversion engine uses the visitor pattern to traverse the intent model, retrieves the dialect template corresponding to each node, and populates the node attribute values ​​into the template variable slots;

[0081] For complex dialect nodes involving changes in query structure, such as The paginated query transformation is not limited to text template filling, but rather performs... Subtree rewrite operation:

[0082] The system executes a three-level nested rewrite algorithm: the system constructs the inner query node. Retain the original sorting logic;

[0083] Building mid-level query nodes ,Will As a data source, and added to the projection area Alternate names, and add them to the filter area. <=( + Condition nodes;

[0084] Construct outer query node ,by As the data source, add it to the filter area. > Conditional nodes enable the topological transformation from a general model to a specific dialect at the logical structure level, generating specific statement structures that conform to the target database syntax.

[0085] Based on resource management strategies, the system embeds exception handling logic and connection pool acquisition logic into the dialect grammar structure to generate an execution logic sequence; this step is not a simple text concatenation, but rather the construction of a structured command chain object;

[0086] This object is physically implemented using a doubly linked list structure in the command pattern, where each node in the list implements... The interface, which explicitly defines The method is used to execute business logic in the forward direction, and The method is used for Perform a rollback operation within the block;

[0087] The system instantiates a Container; according to the connection pooling strategy, insert at the container header Instruction node;

[0088] Create The composite control flow node encapsulates the dialect syntax structure obtained from the aforementioned transformation into... Instruction Injection In the logic block;

[0089] According to the preset exception handling level, in Injection in logic block and Instructions; in Injection in logic blocks The resulting execution logic sequence is a memory object model containing a complete control flow topology and resource lifecycle management, providing a strict logical framework for the subsequent generation of robust target code.

[0090] Example 4

[0091] Perform structural consistency verification between the runtime structural fingerprint and the baseline fingerprint generated based on the data operation intent model, including:

[0092] If the runtime structural fingerprint completely matches the baseline fingerprint, the data operation request is determined to be a legitimate request, and the structural consistency check is confirmed to have passed.

[0093] If the runtime structural fingerprint does not match the baseline fingerprint, it is determined that the data operation request contains the risk of injection attack, and the structural consistency verification fails.

[0094] It also includes: intercepting data operation requests and terminating the subsequent execution of the execution logic sequence in the event of a structural consistency check failure.

[0095] This embodiment further specifies the structural consistency verification and defense response steps, introducing a collision-resistant structural fingerprint hash model for quantification. Statement structure security;

[0096] The system defines the calculation logic for the runtime structural fingerprint and the baseline fingerprint. To ensure the uniqueness and computability of fingerprint values ​​within the finite computer word length, the following improved modulo-weighted hash formula is adopted:

[0097] ;

[0098] in, This represents the summation operation performed on each item in the sequence; The final calculated structural fingerprint value is characterized by a range strictly limited by the modulus. ,Right now ; The total length of the structured token sequence involved in the computation, i.e., the number of tokens; The first character in the structure token sequence that participates in the computation Unit; Representation of state-aware structure extraction function Acting on tokens The output is a string identifier containing depth-encoded information; Characterizes the standard hash function, used to... The output identifier is mapped to a numerical value; The bitwise XOR operator is used to perform operations on hash values. With disturbance constant Perform bit-level obfuscation operations; The disturbance constant is derived from a random integer generated when the system starts up; The position weighting factor is set to the prime number 131 in this embodiment; The size of the cyclic window is used to construct a periodic weight distribution to provide location sensitivity; The modulus is set to a large prime number. ; The representation of the state-aware structure extraction function maintains a depth counter that is updated as the sequence is traversed. Initially 0;

[0099] To ensure fingerprint comparability between the compile-time model and the runtime string, the system performs strict sequence alignment: when calculating the baseline fingerprint... Derived from a deterministic serialization traversal of the data manipulation intent model, the system calls the virtual token generator to... Nodes are mapped to standardized SQL keywords, and virtual structure brackets are explicitly inserted at subtree entry and exit points, generating a structure consistent with the physical... Syntactically isomorphic token streams;

[0100] When calculating runtime fingerprints, Originating from intercepted Real-time streaming parsing of statements;

[0101] In order to eliminate physical To address structural differences caused by the omission of parentheses, the system executes a virtual parenthesis injection algorithm at this stage: the system maintains an operator stack and context priority state;

[0102] The parser employs a bidirectional scanning strategy; when an operator is detected... When, if its priority If the root operator has a lower precedence than the root operator of its left adjacent subexpression, the system immediately inserts it at the beginning of that subexpression in the output stream. Virtual token;

[0103] Similarly, if If the priority is lower than that of the adjacent subexpression on the right, then insert at the end of the right subexpression. ;

[0104] In its implementation, the system utilizes a recursive descent simulator, and for each non-leaf node, outputs before entering the node. Output after exiting the node This forces the runtime-generated token sequence to be topologically identical to the compile-time sequence. The traversal sequence is strictly isomorphic.

[0105] when When a left parenthesis is present, or a virtual parenthesis is present. Incrementing, when it is a right parenthesis Self-decrease;

[0106] The function performs the following transformation: If for Keywords, convert to uppercase;

[0107] like If it is a literal or variable, replace it with a type identifier; the final output identifier will be the depth value. Encoding included, for example or This solidifies the nested hierarchy information within the hash value, preventing logical tampering attacks by changing the bracket hierarchy; in specific implementation, The function uses the following deterministic mapping table:

[0108] for Keywords, such as , :

[0109] ;

[0110] For literal values, such as abc, 123:

[0111] ;

[0112] For identifiers, such as table names and column names:

[0113] ;

[0114] This mapping ensures that even the same keyword can appear at different nesting depths. At the same time, completely different string identifiers will be generated, after... A cascading effect occurs after function hashing;

[0115] perturbation constant The random 32-bit integer is generated by a cryptographically secure pseudo-random number generator during system startup; in specific implementation, in Read in environment / / Equipment, or Call in environment Obtain a high-entropy seed to generate unpredictable random values ​​to prevent reverse engineering attacks based on pre-computed rainbow tables.

[0116] Location weight factor The value is set to a prime number 131; this value was chosen based on a large sample size. Analysis of statement hash distribution characteristics; Experimental data shows that when processing names containing a large number of underscores, such as... and mixed case During sequence, The hash collision rate in 64-bit space is extremely low, and its bit avalanche effect index is close to the ideal value of 0.5, ensuring that a small change in the input can cause a drastic change in the output fingerprint, and the computational cost is better than that of larger prime numbers.

[0117] Loop window size Set to 16; this parameter value is based on Local features, span statistics of the abstract syntax tree (AST);

[0118] Analysis shows that, Substructures within a statement that have strong logical connections, such as (...) clauses, multiple tables average of conditions The length usually falls within a specific range, setting the window size. It can fully cover most local syntactic features, preventing feature loss due to window truncation;

[0119] In addition, 16 was chosen as a power of 2. This allows the use of bitwise AND operation `i&15` to replace the modulo operation `i%16` in low-level calculations, optimizing computational performance; here, the subexpression... As a weighting factor The exponent term specifically means constructing a cyclic positional encoding mechanism;

[0120] Specifically, the mechanism indexes a linearly growing sequence of tokens. Mapping to a finite interval This causes the weighting factors to exhibit periodic changes. ;

[0121] In fingerprint calculation, the role of this exponential term is:

[0122] On the one hand, it provides local position sensitivity, ensuring that the length is Within the sliding window, each token has a unique position weight, which makes the exchange of adjacent or near-neighbor tokens produce significant hash differences, preventing structural fine-tuning attacks.

[0123] On the other hand, it achieves computational performance optimization compared to directly using As an index, used The order of exponentiation is limited, allowing the system to pre-compute and cache the results. to The constant table avoids large number modulo operations with high powers on long sequences, and also prevents the potential risk of numerical overflow due to excessively large exponents.

[0124] Modulus Set as a large prime number The choice of this value is based on number theory properties and hash uniformity verification. It is less than The largest prime number; the fingerprint distribution generated using this modulus has excellent discrete properties, minimizing the probability of hash collisions.

[0125] It should be noted that, in order to ensure the computability of the above formula and avoid integer overflow under a 64-bit computing architecture, the system adopts a step-by-step modulo operation strategy in its implementation:

[0126] That is, the modulo operation is executed immediately after each addition and multiplication operation. Operation; due to near The intermediate product result, i.e. It is extremely easy to break the 64-bit limit; therefore, the specific underlying operation logic of the system is as follows:

[0127] ;

[0128] Among them, the multiplication part Use a 128-bit unsigned integer type, such as in C++. or The result of u128 is temporarily stored, and then a modulo operation is performed to reduce it to... The range is then calculated, and finally, an addition operation is performed with the accumulator, followed by another modulo operation to ensure the final fingerprint. The precision and uniqueness;

[0129] In addition, regarding the formula parameters The output is 32 bits and the final fingerprint In the 64-bit case, this embodiment clarifies the bit width expansion logic: before performing the weighted summation operation of the above formula, the system will... Output 32-bit hash value and perturbation constant Perform zero-extend or type coercion to a 64-bit or 128-bit unsigned integer;

[0130] This conversion ensures that subsequent weighting factors are followed. Multiplication and accumulation operations can overcome the limitations of the 32-bit address space, enabling the generation of fingerprints. It can effectively fill the high-bit space of a 64-bit integer, thereby significantly reducing the probability of hash collisions and achieving a smooth mapping from local 32-bit features to global 64-bit fingerprints;

[0131] Regarding the above-mentioned disturbance constant Due to the dynamic generation characteristics, this embodiment clarifies the generation timing of the baseline fingerprint to ensure logical closure: the normalized token sequence or its compressed representation of the data operation intent model is compiled and embedded into the read-only data segment of the target execution code;

[0132] During the initialization phase of the target code startup, the system generates a random number for this runtime cycle. It then immediately iterates through the embedded token sequence and uses the above formula to calculate all embedded tokens. Reference fingerprint of operation And it resides in a protected memory area;

[0133] This delay calculation mechanism ensures that the baseline fingerprint and the runtime fingerprint use the exact same random perturbation factor, thus preventing static rainbow table attacks while guaranteeing the feasibility of the verification algorithm.

[0134] Based on this, the system executes fingerprint comparison logic; during runtime, the system intercepts requests and extracts the fingerprint data. Statements are tokenized, and runtime fingerprints are calculated. The verification process uses a constant-time comparison algorithm for comparison. and ;

[0135] If both are completely equal, the data operation request is determined to be a valid request, and the structural consistency check is confirmed to have passed.

[0136] Conversely, if the two do not match, the system determines that the data operation request contains the risk of injection attack and determines that the structural consistency check has failed.

[0137] In response to the failure of the structural consistency check, the system intercepts the data operation request and immediately throws an exception. An exception occurs, and the execution of the subsequent logical sequence is terminated.

[0138] Example 5

[0139] Establish a weak reference lifecycle binding between the generated database resource object and the host variable, including:

[0140] By leveraging the weak reference mechanism of programming languages, weak reference proxies pointing to database resource objects can be created.

[0141] Register the weak reference proxy to the destructor callback interface of the host variable so that the lifecycle of the database resource object strictly follows the scope of the host variable;

[0142] The method also includes: real-time monitoring of the memory reference count status of host variables; and triggering the destructor callback interface when the host variable is detected to have been garbage collected.

[0143] Weak reference proxies are used to force the closing of database resource objects and the return of database connections.

[0144] This embodiment further specifies the weak reference lifecycle binding and automatic garbage collection mechanism, through phantom references. The technology enables the entanglement of the lifecycles of physical resources and logical variables;

[0145] The system utilizes the weak reference mechanism of programming languages ​​to create weak reference proxies pointing to database resource objects;

[0146] Specifically, the proxy is a custom reference container class. It is inherited from language standards This class; during its construction, the container treats the host variables as weakly reachable targets. The data is passed along, and a private, strongly referenced member variable is defined inside the container to store the database resource object, such as... Handle;

[0147] The system registers weak reference proxies to the destructor callback interface of the host variable; here, the destructor callback interface does not refer to a traditional C++ destructor, but rather to a destructor based on a reference queue. Asynchronous cleanup notification mechanism;

[0148] At the same time, in order to prevent The monitoring fails because the object itself is garbage collected before the host variable. The system maintains a global static variable. Sets, such as When creating a proxy, it is stored in this collection to establish a strong reference anchor, ensuring that the lifetime of the proxy object is longer than that of the host variable;

[0149] The system monitors the memory reference count status of host variables in real time; given that modern managed language runtimes, such as , Garbage collection generally uses reachability analysis rather than reference counting. In practice, monitoring the reference counting status in this step refers to monitoring the reachability status or memory lifecycle status of the object.

[0150] The system no longer relies on changes in the physical reference count; instead, it determines garbage collection timing by capturing jumps in object reachability levels. This is achieved through a background daemon thread that does not directly poll memory values ​​but instead listens to... The enqueue event signifies that the host variable has lost all strong references and entered a phantom reachable state awaiting garbage collection. Therefore, logically equivalent to the end of the life cycle;

[0151] When it is detected that the host variable has been reclaimed by the garbage collection mechanism, that is... If an object is determined to be unreachable, its associated proxy reference is added to a queue, and the daemon thread executes the operation. The operation wakes up from the block and retrieves the popped item. object;

[0152] At this point, although the host variable has been garbage collected, the handle to the private database resource object inside the container remains valid;

[0153] Trigger the destructor callback interface; the daemon thread reads the private resource handle through a weak reference proxy, forcibly executing the database resource object. Operations and database connection return operations; after the operations are completed, the daemon thread removes the proxy object from... Remove from the collection to complete the final memory decoupling.

[0154] This embodiment ensures that database resources are only released after the host variable is completely destroyed by encapsulating the resource handle in a virtual reference container that tracks the host variable and combining it with global anchoring technology.

[0155] Example 6

[0156] During the construction of the abstract syntax tree, the location of dynamic variables in the embedded data manipulation syntax block is identified;

[0157] Mark all dynamic variable positions as parameterized placeholders to prevent string concatenation operations in the execution logic sequence.

[0158] This embodiment is a supplement to the abstract syntax tree construction process, involving parameterization to enhance security;

[0159] When parsing embedded data manipulation syntax blocks, the system identifies the location of dynamic variables contained therein, i.e., embedded host language variables;

[0160] During the construction of the abstract syntax tree, the system enforces parameterization rules; specifically, the parser executes a context-aware expression flattening algorithm.

[0161] When traversing to a binary operator node of type string concatenation, the system recursively checks its left and right child nodes; if one side is... The string literal is on one side and the host variable reference is on the other side. The parser performs an upward backtracking context lookup step: starting from the current host variable reference node, it traverses upward along the parent node pointer. As long as the parent node type is still a string concatenation or grouping brackets, it continues to backtrack upward until the first ancestor node that is not a string concatenation type is found. This ancestor node is defined as a valid semantic context node.

[0162] The system verifies whether the valid semantic context node is in a preset whitelist set; this whitelist set includes:

[0163] ;

[0164] The variable is determined to be in a value node position only if the validation passes. ;

[0165] If so, the parser will delete the binary operator node and merge the string literal into the nearest one. In the text block, the host variable reference node is replaced in place with the parameter binding node. And mark it as a parameterized placeholder;

[0166] If the valid semantic context node belongs to a table name, column name definition, or other structural syntax node (i.e., an identifier location), the parser will abort construction and throw an unsafe dynamic exception. A compilation error has been reported, forcing developers to use static table names.

[0167] This structured transformation eliminates the possibility of concatenation operations at the syntax tree level, thus prohibiting the generation of any form of string concatenation code in the execution logic sequence; based on this, all legal variable values ​​will be enforced according to the database-driven standard. The interface is used for transmission.

[0168] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An embedded database programming method, characterized in that, The method includes: The input source code stream is scanned to identify embedded data manipulation syntax blocks contained therein; The embedded data operation syntax block is parsed to construct an abstract syntax tree, and the underlying driver code is stripped off based on the abstract syntax tree to generate a data operation intent model that is independent of the driver. The preset database dialect parameters and resource management strategies are injected into the data operation intent model to synthesize an execution logic sequence containing complete execution logic. The embedded data manipulation syntax block in the source code stream is replaced with a standard function call pointing to the execution logic sequence to generate the target executable code; During the execution of the target code, the current data operation request is intercepted, and the runtime structure fingerprint of the data operation request is calculated; Perform a structural consistency check between the runtime structure fingerprint and the benchmark fingerprint generated based on the data operation intent model; If the structural consistency check passes, the data operation request is executed, and a weak reference lifecycle binding is established between the generated database resource object and the host variable. The step of stripping the underlying driver code based on the abstract syntax tree to generate a driver-independent data manipulation intent model includes: Traverse the abstract syntax tree to extract logical nodes that represent the intent of data manipulation and parameter nodes that represent bound variables; Remove resource management nodes from the abstract syntax tree that involve database connection establishment, cursor creation, and resource closure; Based on the retained logical nodes and parameter nodes, the data operation intent model is reconstructed and generated; The step of injecting preset database dialect parameters and resource management strategies into the data operation intent model to synthesize an execution logic sequence containing complete execution logic includes: Based on the database dialect parameters, the general logical nodes in the data operation intent model are converted into dialect grammatical structures for a specific database type. According to the resource management strategy, exception handling logic and connection pool acquisition logic are embedded in the dialect syntax structure to generate the execution logic sequence.

2. The embedded database programming method according to claim 1, characterized in that, The step of performing structural consistency verification between the runtime structural fingerprint and the benchmark fingerprint generated based on the data operation intent model includes: If the runtime structure fingerprint completely matches the baseline fingerprint, the data operation request is determined to be a legitimate request, and the structure consistency check is confirmed to have passed. If the runtime structure fingerprint does not match the baseline fingerprint, the data operation request is determined to contain the risk of injection attack, and the structure consistency verification is determined to have failed.

3. The embedded database programming method according to claim 2, characterized in that, The method further includes: If the structural consistency check fails, the data operation request is intercepted, and the subsequent execution of the execution logic sequence is terminated.

4. The embedded database programming method according to claim 1, characterized in that, The weak reference lifecycle binding established between the generated database resource object and the host variable includes: By utilizing the weak reference mechanism of programming languages, a weak reference proxy pointing to the database resource object is created; Register the weak reference proxy to the destructor callback interface of the host variable so that the lifecycle of the database resource object strictly follows the scope of the host variable.

5. An embedded database programming method according to claim 4, characterized in that, The method further includes: Real-time monitoring of the memory reference count status of the host variables; If the host variable is detected to have been garbage collected, the destructor callback interface is triggered. The weak reference proxy forces the closing operation of the database resource object and the return operation of the database connection.

6. The embedded database programming method according to claim 1, characterized in that, The method further includes: During the construction of the abstract syntax tree, the positions of dynamic variables in the embedded data manipulation syntax blocks are identified; Mark all the positions of the dynamic variables as parameterized placeholders to prevent string concatenation operations in the execution logic sequence.

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