A function node semantic adaptation method and system based on formal verification

Abstract

The application provides a function node semantic adaptation method and system based on formal verification, and relates to the technical field of visual low-code development technology. The method comprises the following steps: obtaining abstract syntax tree metadata from a constraint mapping table based on a node unique identifier, and generating a local post constraint object and a local pre constraint object; extracting a source post constraint condition and a target pre constraint condition; based on the source post constraint condition, the target pre constraint condition and a connection line conversion mapping relationship, constructing a joint violation proof proposition, and converting the joint violation proof proposition into a theoretical formula string; passing the theoretical formula string to a theorem solving engine to output a binary state flag; in the case where the joint violation proof proposition is established, extracting a variable assignment model, and projecting a violation data traceability view based on the variable assignment model. Through the application, the problem of unstable compilation is solved, and the effect of improving the stability of compilation is achieved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of visual low-code development technology, and more specifically, to a method and system for semantic adaptation of function nodes based on formal verification. Background Technology

[0002] Traditional visual logic orchestration systems rely heavily on static type checks or runtime verification when handling module connections. This lagging debugging paradigm leads to deep-seated hidden logic overflows and business semantic conflicts buried in the runtime environment, which can easily cause production accidents.

[0003] Existing protocol identification technologies only cover format adaptation at the network communication layer, and cannot guarantee the boundary security and physical dimension compatibility of data streams in the system state space from the bottom layer, thus affecting system stability. Summary of the Invention

[0004] This invention provides a method and system for semantic adaptation of function nodes based on formal verification, which at least solves the problem of insufficient compilation stability in related technologies.

[0005] According to an embodiment of the present invention, a method for semantic adaptation of function nodes based on formal verification is provided, comprising: Obtain component drag events, retrieve abstract syntax tree metadata based on node unique identifiers, and generate local post-constraint objects and local pre-constraint objects. The abstract syntax tree metadata corresponds to the function node being operated on. Extract the source post-constraints from the source node cache and the target pre-constraints from the target node cache; Based on the source post-constraints, the target pre-constraints, and the connection transformation mapping relationship, a joint violation proof proposition is constructed, and the joint violation proof proposition is converted into a theoretical formula string; The modular theory formula string is passed to the theorem solving engine, which performs the first compilation to output the binary state flag. If the joint violation proof proposition is true, extract the variable assignment model, block the rendering of the document object model connection, and project the violation data source view based on the variable assignment model.

[0006] In an exemplary embodiment, based on the source post-constraint, the target pre-constraint, and the connection transformation mapping relationship, the joint violation proof proposition is constructed as follows: The root node of the target abstract syntax tree corresponding to the target pre-constraint is encapsulated with a logical NOT operator; The target abstract syntax tree encapsulating the logical NOT operator is merged with the source abstract syntax tree corresponding to the source post-constraint using the logical AND operator; Calculate the semantic distance between the source service tag corresponding to the source node and the target service tag corresponding to the target node; If the semantic distance is greater than a preset compatibility threshold, business conflict logic constants are injected into the merged abstract syntax tree to generate a complete joint violation proof proposition abstract syntax tree.

[0007] In an exemplary embodiment, calculating the semantic distance between the source service label corresponding to the source node and the target service label corresponding to the target node includes: In a pre-constructed directed acyclic graph of physical dimensions, the source service label and the target service label are mapped to source graph nodes and target graph nodes, respectively. Calculate the number of undirected shortest path edges from the source graph node to the target graph node; The number of edges in the undirected shortest path is used as the semantic distance.

[0008] In one exemplary embodiment, projecting a violation data tracing view based on the variable assignment model includes: Obtain the exception data packet returned by the theorem solving engine, wherein the exception data packet contains an abstract feature vector; By reverse querying the operation status dictionary, the abstract feature vector is mapped back to the original business field names visible to the user interface and the extreme value data that caused the crash. The screen tensor relative coordinates of the target node input stake are obtained using the coordinate system transformation operator; At the offset position determined based on the screen tensor relative coordinates, a floating alarm window containing the original business field name and the extreme value data is rendered.

[0009] In one exemplary embodiment, the method further includes: The source post-constraint is characterized as a range of values ​​including a lower bound and an upper bound of a real number. Perform a forward operation along the abstract syntax tree structure on the value range to obtain the mapped output range; Determine whether there is an intersection between the mapped output interval and the legal interval formed by the target pre-constraint conditions, and control the rendering of the connection based on the intersection determination result.

[0010] In one exemplary embodiment, blocking document object model connection rendering includes: Mount the graphical user interface override pipeline in the main rendering thread; Destroy the pre-instantiated connection object associated with the connection attempt event; Calculate the Bézier curve path from the starting point to the ending point along the mouse drag trajectory; The canvas rendering interface is invoked along the Bézier curve path to draw a dashed pixel pattern with a specific warning color and a vibration animation frame.

[0011] According to another embodiment of the present invention, a function node semantic adaptation system based on formal verification is provided, comprising: The constraint extraction module is used to obtain component drag events, obtain abstract syntax tree metadata based on the node's unique identifier, and generate local post-constraint objects and local pre-constraint objects. The abstract syntax tree metadata corresponds to the node of the function being operated on. The logic transformation module is used to extract the source post-constraints cached in the source node and the target pre-constraints cached in the target node; and based on the source post-constraints, the target pre-constraints, and the connection transformation mapping relationship, construct a joint violation proof proposition and convert the joint violation proof proposition into a theoretical formula string; The theorem solving engine module is used to pass the modular theory formula string to the theorem solving engine, and the theorem solving engine performs the first compilation to output the binary state flag; The counterexample projection module is used to extract the variable assignment model and block the rendering of the document object model connection when the joint violation proof proposition is true, and to project a violation data source view based on the variable assignment model.

[0012] In an exemplary embodiment, based on the source post-constraint, the target pre-constraint, and the connection transformation mapping relationship, the joint violation proof proposition is constructed as follows: The root node of the target abstract syntax tree corresponding to the target pre-constraint is encapsulated with a logical NOT operator; The target abstract syntax tree encapsulating the logical NOT operator is merged with the source abstract syntax tree corresponding to the source post-constraint using the logical AND operator; Calculate the semantic distance between the source service tag corresponding to the source node and the target service tag corresponding to the target node; If the semantic distance is greater than a preset compatibility threshold, business conflict logic constants are injected into the merged abstract syntax tree to generate a complete joint violation proof proposition abstract syntax tree.

[0013] According to yet another embodiment of the present invention, a computer-readable storage medium is also provided, wherein a computer program is stored therein, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed.

[0014] According to yet another embodiment of the present invention, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0015] This invention places previously isolated connection behaviors within a logical constraint framework and performs incremental modular theory deduction within an extremely short interaction window, physically blocking potential implicit truncation, boundary overflow, and cross-domain dimensional conflicts. Therefore, it can solve the problem of insufficient compilation security and achieve the effect of improving compilation security. Attached Figure Description

[0016] Figure 1 This is a flowchart of a function node semantic adaptation method based on formal verification according to an embodiment of the present invention; Figure 2 This is a structural block diagram of a function node semantic adaptation system based on formal verification according to an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0018] In the following description, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0019] Furthermore, in this application, directional terms such as "upper," "lower," "left," and "right" may be defined relative to the orientation of the components shown in the accompanying drawings. It should be understood that these directional terms can be relative concepts, used for relative description and clarification, and may change accordingly depending on the orientation of the components in the accompanying drawings.

[0020] In this application, unless otherwise expressly specified and limited, the term "connection" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral part; it can be a direct connection or an indirect connection through an intermediate medium. Furthermore, the term "coupled" can refer to an electrical connection that enables signal transmission.

[0021] As used herein, “about,” “approximately,” or “approximately” includes the stated value and the average value within an acceptable range of deviation from the given value, wherein the acceptable range of deviation is determined by a person skilled in the art taking into account the measurement under discussion and the error associated with the measurement of the given quantity (i.e., the limitations of the measurement system).

[0022] This embodiment provides a method and system for semantic adaptation of function nodes based on formal verification. The method intercepts connection events at the front end and synthesizes the source node output constraints and target node input constraints into Hall logic joint violation propositions. It uses a theorem solving engine in an independent worker thread to perform incremental satisfiability search and extract specific variable assignment counterexamples that cause crashes. This enables exhaustive proof of the boundary safety and semantic compatibility of data flow during the compilation process. It solves the problem of compilation security caused by the concealment of deep logic crashes and the lag in investigation of existing technologies based on static type checking or runtime capture. It achieves the beneficial effect of physically blocking illegal connections and realizing zero runtime crashes during the visual drag-and-drop stage.

[0023] In the process of constructing joint violation proof propositions and performing modular theory solutions for satisfiability in this method, in the dimension of real number operations, all continuous variables are uniformly mapped to the floating-point representation space of the IEEE 754 standard, with the unit being bits; in the dimension of logical judgment, the truth domain of the proposition only contains the set of Boolean values ​​{True, False}, which are dimensionless parameters; in the dimension of business semantics, a graph theory distance space is constructed, with distance measured by the number of edges.

[0024] Specifically, it includes the following steps: S100, responding to component drag events on the visualization canvas, asynchronously deserializes the abstract syntax tree metadata corresponding to the operated function node from the globally read-only constraint mapping table based on the node's unique identifier, and generates local post-constraint objects and local pre-constraint objects in the front-end session state tree. Specifically: S110: The constraint extraction module listens for the release callback function of elements attached to the document object model to read the metadata payload carrying the dragged entity. The system extracts the unique encoded string of a specific component instance from the memory region and uses it as the index key.

[0025] S120: The constraint extraction module initiates an asynchronous, non-blocking query operation in the system's pre-loaded cache hash table based on the extracted index key. After matching the entry, it extracts the serialized binary syntax configuration package.

[0026] S130, the decoding unit recursively descent-parses the binary syntax configuration package and instantiates a pair of separate logical objects within the browser's heap memory area. These two objects respectively represent the node's acceptance requirements for the incoming data stream and its guarantees of the characteristics of the outgoing data stream.

[0027] For example, the constraint extraction module captures a drag-and-drop operation. The obtained node's unique identifier is [UUID-4f8a-9c2b], which represents a business component for safe square root operations. The system then reads its metadata from the global dictionary based on this identifier. After deserialization, the system mounts two sets of objects in the front-end state tree: Local pre-constraint objects are Furthermore, the variable type is marked as a 32-bit single-precision floating-point number, with its unit being bits; Local post-constraint objects are declared as Furthermore, it exhibits accompanying operational characteristics.

[0028] This preloading behavior avoids time-consuming network requests and full recursive parsing of the node tree at the moment of connection, ensuring a foundation for extremely low latency in subsequent operations.

[0029] In another example, for a node used for HL7 medical information exchange, the node's unique identifier is [PID-Segment-Validator]. The constraint extraction module obtains its metadata, parses it, and generates a local pre-constraint object. This object contains multiple sub-constraints; for example, the patient name field PID.5 must be a string type with a length of less than or equal to 50 characters, and the birth date field PID.7 must conform to the [YYYYMMDD] format. Simultaneously, a local post-constraint object is generated, declaring that the data stream output by this node will strictly adhere to all specifications of the HL7 v2.5.1 standard regarding patient identity information segments. This fine-grained constraint preloading provides a precise set of rules for subsequent validation.

[0030] As another example, for nodes involving financial transaction permissions, their unique identifier is [High-Value-Transaction-Auth]. After parsing by the feedforward extraction module, the generated pre-constraint object contains not only numerical constraints but also a non-numerical permission label constraint. For example, the numerical constraint could be that the transaction amount must be less than or equal to RMB 1,000,000.00, and the permission label constraint could be that the operator role must be a senior trader. The post-constraint object declares that the transaction record processed by this node will be marked as authorized. This ability to pre-extract hybrid constraints allows formal verification to cover security rules at the business logic level.

[0031] S200, in response to a connection attempt event from the source node output stub to the target node input stub, extract the source post-constraints cached in the source node and the target pre-constraints cached in the target node. Specifically: S210, the logic conversion module captures the point-to-point drag intention triggered by the user input device. Its engine records the socket anchor point identifiers corresponding to the starting point coordinates and the ending point coordinates, and backtracks to find the originating entity to which the starting point belongs and the receiving target entity to which the ending point belongs based on the topology relationship.

[0032] S220: The memory manager, based on the entity's context pointer, locks and copies the source entity's state guarantee declaration memory block and the target entity's admission qualification declaration memory block, and encapsulates the data of the two regions into a lightweight data transfer object.

[0033] For example, when the cursor is dragged from the output contact of the external deduction interface of the external account to the input contact of the local bank's inbound interface, the system triggers an interception. Assume the external deduction interface of the external account is the source node, identified as N1, and the local bank's inbound interface is the target node, identified as N2. At this time, the Hall logic conversion module extracts the source post-constraints cached in N1. Simultaneously extract the target pre-constraints from the N2 cache. This phase does not perform any actual code execution operations, but merely performs a static, safe copy transfer of the state description file in memory.

[0034] In another example, the body temperature monitoring sensor node acts as the source node, and its output terminal is connected to the input terminal of the fever alarm logic node, which is the target node. The post-constraint condition of the source node is... (The unit is Celsius). The prerequisite constraints for the target node are: The unit is Celsius. The logic transformation module extracts these two constraints to construct the proof by contradiction in the subsequent steps.

[0035] As another example, the output stub of the medical insurance settlement node, whose post-constraint declares that its output settlement status field value is Completed, is subsequently connected to the input stub of the payment notification generation node. The pre-constraint of the payment notification generation node requires that its input settlement status field must be either Completed or Partial_Payment. The transformation module extracts these two string constraints based on enumeration values, and will subsequently verify whether the single output status of the source node is a subset of the multiple input statuses allowed by the target node.

[0036] During the process of obtaining the abstract syntax tree, when the system encounters nodes with extremely high computational complexity, it will perform a boundary dimensionality reduction stripping operation. Specifically: S201. The feature scanning unit traverses all operational modifiers within the source or target abstract syntax tree using a depth-first search. When a specific feature is matched, it is determined that there is a risk of triggering a state explosion. The feature can be a high-order polynomial integral or a hash encryption function.

[0037] S202. The abstract envelope unit encapsulates a placeholder logic shell without internal structure around the original syntax tree node. This placeholder logic shell discards all arithmetic transformation details in the original function body and only extracts the lower bound of the input theoretical limit and the upper bound of the output theoretical limit statically calibrated in the node configuration table.

[0038] S203. The system will send the simplified node object after envelope to the subsequent proposition synthesis process, and use it as a substitute for the original high-complexity node for formal calculation.

[0039] For example, the source node contains an RSA-encrypted large number modulo algorithm, which internally includes deep loops and bit offsets. Directly converting it into a satisfiability proposition would cause the solver to face more than... The computation time for a 3D Boolean bit vector array will exceed 3600 seconds. At this point, the scan unit matches the RSA_Mod_Op feature. The abstract envelope unit uses an uninterpreted function. Replace this algorithm and force the addition of outer constraints. By outputting a wide but structurally simple range of values, subsequent processes can be completed in a short time. Although this sacrifices fine internal tracking accuracy, it absolutely ensures that the verification link remains unbroken and prevents large-scale data overflow.

[0040] In another example, a node used for medical image analysis contains a complex Fourier transform operator that converts a spatial domain image into a frequency domain spectrogram. This transformation involves performing complex exponential operations on each pixel to convert it to an SMT formula, which leads to a surge in solution complexity. The feature scanning unit identifies the FFT_Operator. At this point, the abstract envelope unit does not model its internal transformation logic but defines a broad output constraint based on the physical range of image grayscale values. For example, for an 8-bit grayscale image, the input pixel values ​​are in the range (0, 255). Regarding the output constraint, it can be declared that the magnitude of the output frequency domain coefficients does not exceed a theoretical upper limit, which can be calculated based on the input dimension and the law of conservation of energy. This avoids formal proof of the Fourier transform itself, instead verifying whether the energy boundaries of its input and output meet the system requirements.

[0041] For another example, consider the segmented tiered rate calculation node in an actuarial model. The calculation logic of this node is a complex piecewise function. For instance, the rate is 0.01 when the input amount x is in [0, 1000), and 0.015 when it's in [1000, 5000). Directly converting this multi-branched if-then-else structure into an SMT formula would generate numerous disjunctive paradigms, reducing solution efficiency. Specifically, when the feature scanning unit identifies `Tiered_Rate_Calculator`, the abstract envelope unit does not expand its internal branches but instead calculates the output range over the entire function's domain. For example, if all rates are between [0.01, 0.05], the node is abstracted as an uninterpreted function with an output value in the range [input amount * 0.01, input amount * 0.05]. This simplifies the problem significantly, as subsequent verification only needs to check whether the expanded output range satisfies the input constraints of the target node.

[0042] S300, based on the source post-constraints, the target pre-constraints, and the connection transformation mapping relationship, constructs a joint violation proof proposition and converts it into a standardized form of satisfiability modular theory formula string. Specifically: S310: The abstract syntax tree mutation engine instantiates a new syntax tree node with the type identifier OP_NOT in memory. Then, it assigns the memory address of the root node of the target abstract syntax tree corresponding to the target pre-constraint to the single subtree pointer field of the OP_NOT node, thereby completing the negation operation of the target input condition at the logical level.

[0043] S320, the abstract syntax tree mutation engine continues to instantiate a binary operation node with the type identifier OP_AND. The system then assigns the memory pointer of the newly created root node containing OP_NOT to the right subtree pointer field of the OP_AND node, and simultaneously assigns the root node pointer of the source abstract syntax tree corresponding to the source post-constraint to the left subtree pointer field of the OP_AND node. Through this relinking and mounting of the underlying memory addresses, the physical merging and splicing of the independent source and target trees into a joint violation proof proposition abstract syntax tree is completed.

[0044] S330. Calculate the semantic distance between the source service label corresponding to the source node and the target service label corresponding to the target node. In a pre-constructed directed acyclic graph with physical dimensions, the source service label and the target service label are mapped to source graph nodes and target graph nodes, respectively. Then, the breadth-first search algorithm is used to calculate the number of undirected shortest path edges from the source graph node to the target graph node, and the number of undirected shortest path edges is defined as the semantic distance. It should be noted that, under the condition that there is no connected path between the source graph node and the target graph node, the semantic distance is assigned a value of positive infinity.

[0045] S340. If the semantic distance is greater than the preset compatibility threshold, instantiate and inject the constant quantum tree of business conflict logic into the merged abstract syntax tree to generate a complete abstract syntax tree of joint violation proof proposition.

[0046] S350. The compiler performs a post-order traversal of the generated joint violation proof proposition abstract syntax tree, extracts all variable declarations, constraint boundaries and logical connectors, and translates them line by line into a plain text encoded string with a deterministic parse structure according to a specific formal grammar.

[0047] Among them, the core form of the joint violation proof question is:

[0048] Instead of exhaustively proving that all valid inputs produce valid outputs, the system searches for "live counterexamples" that "both satisfy the source node's output commitment and violate the target node's input requirements." Constants are used to provide a direct, high-dimensional penalty circuit breaker mechanism at the Boolean logic level for non-mathematical business-dimensional conflicts (such as currency type conflicts).

[0049] in, It is a joint violation proof proposition. If the solution result is [Satisfiable (SAT, i.e., True)], it means that there is an illegal connection that causes the system to crash; if it is [Unsatisfiable (UNSAT, i.e., False)], it means that the connection is mathematically absolutely safe.

[0050] There is a quantifier and a domain. x represents the free probe variable in the solution process, that is, the specific data payload that the source node may output; This represents the global scope supported by the data type output by the source node, such as the entire set of 32-bit floating-point numbers. This part indicates the operation of [finding the existence of at least one specific value of x] performed in the global scope.

[0051] These are source post-constraints, used to represent the attribute guarantees or boundary assertions that the source node can provide for its output variable x. For example, a random number node guarantees that its output x must satisfy... .

[0052] This is the logical AND operator, which requires that the conditions on both its left and right sides must be true simultaneously.

[0053] The NOT operator is used to negate the logical condition that follows it.

[0054] These are pre-existing constraints for the target node, representing the minimum requirements for the target node to safely receive and process input data. For example, a square root node requires its input to be ≥0.

[0055] For connection conversion mapping operators, it represents the implicit type conversion, truncation or bit extension mechanisms that may occur at the underlying level when data is passed from the source to the target through a connection, such as casting a 64-bit long integer to a 16-bit short integer.

[0056] The OR operator is used for logical operations; if either of its left or right sides is true, the entire formula is true.

[0057] This is a business conflict logic constant, which is a non-mathematical dimension exclusion penalty constant calculated based on the business ontology graph (DAG). If the source node and the target node are incompatible in business semantics or physical dimensions, this constant is assigned the value True; otherwise, it is False. For example, linking RMB to USD would be incompatible, and so on.

[0058] This formula is constructed based on the proof by contradiction of Hall logic and Satisfiability Modular Theory (SMT) in formal semantics of programming, and its core is reflected in the following two dimensions: 1. Left side: Data flow boundary falsification mechanism based on proof by contradiction Conventional software validation attempts to prove that all transmitted data is secure, but this forward exhaustive search is impossible when the state space explodes. This formula uses reverse logic: expression The physical meaning is to find an anomalous data x that mathematically satisfies two contradictory conditions simultaneously. That is, this x satisfies the output commitment of the source node—assuming it's data that normal business operations can generate—but after implicit transformation via connections... Then, it just so happened to break the target node's reception threshold. .

[0059] If the SMT solver finds such an x, it means that a live counterexample that can penetrate the security net has been found, directly proving that the connection is illegal; if it cannot find one, it mathematically exhaustively proves that the data stream is absolutely secure.

[0060] 2. Right side: High-dimensional semantic circuit breaker mechanism based on short-circuit logic Purely mathematical proofs cannot comprehend the exclusionary nature of business dimensions; for example, in memory, 100 kilograms and 100 meters are indistinguishable at the binary level.

[0061] This formula is passed This involves incorporating business semantic-level verification into mathematical proofs, utilizing logical OR. Its characteristic: Once the preceding undirected acyclic graph shortest path algorithm determines that the physical dimensions of the source and the target are incompatible, That is, it is assigned the value True. At this point, regardless of whether the mathematical interval calculation on the left exceeds the boundary, the entire proposition... It will instantly short-circuit and collapse to True, thereby directly triggering a semantic conflict alarm at the system level. This achieves a high degree of decoupling and integration of pure mathematical boundary error prevention and business logic error prevention under the same Boolean formula system.

[0062] For example, assume that the source node output variable is of type 32-bit integer, i.e. The target pre-constraint requires that the input value must be greater than 0. This is achieved by instantiating the OP_NOT node. Inverting the result produces a logical equivalent to The subtree structure is then merged and attached to the OP_AND node. At this point, the source business label is USD (US Dollar) and the target business label is CNY (Chinese Yuan). A business-dimensional DAG graph with 150 nodes is maintained in the background, using USD and CNY as the search start and end points. Since currency conversion does not allow hard-wired connections, there are no direct edges or indirect multi-hop paths in the graph. The breadth-first search queue returns a path-not-exhaustive flag after reaching its depth, thus assigning the semantic distance to infinity, with the compatibility threshold preset to 0. Therefore, it is determined that infinity is much greater than 0, and the logical truth constant True is injected into the branch of the root node OP_OR of the proposition tree. Then, the... The final abstract tree format generates a string with the following text structure:

[0063] In another example, the source node is a timestamp generator with post-constraints of: It is a 32-bit unsigned integer Unix timestamp, i.e. The target node is a date formatting component with the following preconditions: It must be a positive number. First, regarding... Generate the inverted subtree. Then merge them to generate the corresponding subtree. The structure is as follows. Both the source and target nodes have the business tag "Time," and their semantic distance is 0. Injecting subtree is set to False. The final generated SMT formula will be:

[0064] As another example, the source node outputs a data packet with post-constraints including a checksum field (checksum) and a payload field (payload), satisfying checksum = CRC32(payload). The target node is a data parser whose pre-constraints require that the input checksum must match its own checksum calculated for the payload. When a connection is established, the illegal tree structure constructed by the system will be equivalent to:

[0065] This proposition is logically always false because CRC32 is a deterministic function. Therefore, the SMT solver will quickly return UNSAT, proving that the connection is secure.

[0066] S400: The standardized form of the satisfiability modular theory formula string is passed across threads to an independently running theorem-solving engine. The theorem-solving engine performs a compile-state satisfiability search (i.e., the first compilation) to output a binary state flag indicating whether the proposition is true or false. Specifically: S410. The standardized form of the satisfiability modulus theory formula string is pushed to the theorem solving engine, which runs on a network assembly binary format, via a lock-free message channel.

[0067] S420: Set a global computation timeout threshold for the theorem solving engine.

[0068] S430. If the computation time of the theorem solving engine exceeds the global computation timeout threshold, the search process is forcibly interrupted, and an abnormal flag indicating an unknown verification status is output to trigger downgrade blocking protection.

[0069] S440, the theorem solving engine performs lexical analysis and internal data structure construction operations on the received formula string.

[0070] Specifically, within the engine, a conflict-driven clause learning algorithm continuously guesses the Boolean values ​​of decision variables and performs propagation deduction. When the reasoning leads to a logical contradiction in the current path, conflict clauses are generated to prune the search space. When a set of variable assignments that makes the final calculation result of the entire logical statement true is found, a SAT flag indicating that the proposition is true is output; if no valid solution is found in the exhaustive solution space, an UNSAT flag is output.

[0071] The global computation timeout threshold is a fixed engineering constant of 150 milliseconds. This value is determined based on the critical point of human sensory response in ergonomic experiments. 150 milliseconds is the lower limit of the time window during which users perceive lag when interacting with the graphical drag-and-drop interface. If background computations exceeding this threshold block the front end, it will lead to a poor and fragmented user experience. By issuing interrupt signals in the hardware-level timer, it is ensured that the engine prioritizes the main thread of the interface to prevent crashing when faced with extremely complex verification formula infinite loops.

[0072] For example, the generated formula text is serialized into a byte stream and passed into a copy of the Z3 engine within a WASM-isolated region. The engine initiates a search, and when it encounters a formula whose left half contains a rejection condition... The bit vector engine determines that its result is always False using arithmetic axioms. However, the disjunction condition on the right side of the formula contains a constant True, therefore the entire expression... The solution ultimately collapses to a global result of True. The solution engine took only 12 milliseconds, far below the global computation timeout threshold of 150 milliseconds, and successfully obtained the solution set. Therefore, the output port of the theorem solution engine releases the binary Boolean characteristic indicating that the proposition is true, signifying a fatal risk in the connection.

[0073] Another example is the formula generated for the second timestamp example in S350. The solver analyzes the conjunction condition. It finds that the variable t must be both greater than or equal to 0 and less than or equal to 0, and the only integer that satisfies this condition is t=0. Then it checks whether t=0 satisfies this condition. The solution is found to be satisfied. Therefore, the solver finds a solution t=0 that makes the entire proposition true. It will return SAT and provide the model {t:0}, which means that when the source node outputs a timestamp of 0, the constraint that the target node input must be a positive number is violated.

[0074] As another example, in a load testing scenario, a formula containing complex circular dependencies and multivariate constraints is received. The solver begins to execute conflict-driven clause learning, but within a 150-millisecond time window, its internal decision hierarchy only progresses to level 5, without finding a solution or proving there is no solution. At this point, the main thread's timer triggers an interrupt signal. The S430 captures this signal, immediately terminates the WASM worker thread, and returns a special status code, UNKNOWN, to the UI layer. Based on this, the UI layer blocks the connection and prompts the user that the connection logic is too complex to complete static security verification within the specified time, requiring simplification of the logic or manual addition of test cases.

[0075] Specifically, when the system's processing resources are severely exhausted or in a specific low-security configuration environment, the energy-intensive theorem solution can be replaced by the following method: S401. The interval parser reads constant assertions from the source abstract syntax tree and represents the source post-constituent conditions as a continuous range of values ​​containing a lower bound and an upper bound of real numbers. .

[0076] S402: The mapping driver performs upward arithmetic operations or affine transformations on the value range along the various unary or binary operators defined in the abstract syntax tree structure, and directly obtains the expanded range of the output extrema after mapping based on the axiom of interval operations.

[0077] S403. The collision detection module calculates whether the output range after mapping intersects with the safe reception range formed by the target's pre-constraint conditions on the number axis. It generates a blocking indication if there is no intersection or if the target exceeds the limit.

[0078] For example, suppose the source node outputs a... The signal fluctuates within a certain range. An amplification mapping operation, multiplied by a constant 2, is performed after the intermediate connection configuration. The interval analyzer captures the initial interval. The mapping driver calculates the new lower bound based on the multiplication interval axiom. The new upper limit is The expanded output range is thus determined to be... The target node's secure reception interval requirement is as follows: The collision detection unit compares the two objects and finds that they do not overlap in the coordinate domain, thus generating an error flag. This mode reduces the computation time compared to exhaustive bit vector enumeration to [time missing]. It operates on a constant time scale, but comes at the cost of potentially higher false positive rates.

[0079] Another example is that the source node outputs a temperature value, in the range of... There is a function node in the middle, whose operation is... Then the mapping driver first maps the input range Apply the square operation. Since the function is monotonically increasing within the input interval, the output interval is... Then, subtract 1300 from this interval, and the final mapped output interval is... If the preconditions of the target node are The collision detection unit will detect the mapped interval. and legal interval When an intersection exists, this alternative mode conservatively allows the connection because it cannot rule out the possibility that all outputs are greater than 0. This demonstrates its limitation of potentially producing false negatives (false negatives, or missed detections). The standard SMT solver, however, can find... A nearby value makes the output less than or equal to 0, thus reporting a counterexample.

[0080] S500, responding to the binary state flag indicating the joint violation proof proposition is true, extracts the variable assignment model that makes the formula true from the memory snapshot of the theorem solving engine, blocks the rendering of the document object model connection corresponding to the connection attempt event, and projects a violation data source view on the visualization canvas based on the variable assignment model. Specifically: S510. Obtain the exception data packet containing abstract feature vectors returned by the theorem solving engine.

[0081] S520: By reversing the query to the operation status dictionary, the abstract feature vector is mapped back to the original business field names visible to the user interface and the extreme value data that caused the crash.

[0082] S530. Use coordinate system transformation operators to obtain the screen tensor relative coordinates of the target node input stake.

[0083] S540. At the offset position determined based on the screen tensor relative coordinates, render a floating alarm window containing the original business field name and the extreme value data.

[0084] S550: Mount the graphical user interface override pipeline in the main rendering thread, and destroy the pre-instantiated connection object associated with the connection attempt event. Calculate the Bézier curve path from the start point to the end point along the mouse drag trajectory, and then call the canvas rendering interface on the Bézier curve path to draw a dashed pixel pattern with a specific warning color and vibration animation frames.

[0085] For example, the theorem solving engine outputs a SAT (Standard Achievement Test) flag, and then the parser extracts the object package containing key-value pairs from the engine's underlying read-only snapshot area. At this point, the detached variable within the system is tagged as _sym_v01 with a value of 50.00. Since this variable is a machine-compiled symbol, the dictionary resided by the feedforward extraction process is queried to backmap "_sym_v01" to the user-friendly field label name Amount. Simultaneously, the accompanying conflict metadata flag, Semantic_Unit_Conflict, is extracted. Then, the absolute two-dimensional offset vector of the target connection stub within the current viewport is captured. Anchor points are generated based on this baseline vector plus a fixed bubble offset distance vector (20, 30). At coordinates (270, 390), the browser rendering pipeline draws the highest-level absolutely positioned block component, with the text: "Connection refused! When the source outputs 50.00USD, the target interface experiences business semantic truncation."

[0086] At the same time, the construction of document object model nodes representing connectivity is prevented. Meanwhile, the calculator generates cubic Bézier smooth trajectory data by fitting the starting coordinates and the current hovering coordinates. The graphics acceleration layer refreshes the red dashed line composed of virtual pixels in the corresponding trajectory layer at a refresh rate of 60 frames per second, and applies a sinusoidal periodic offset of 2 pixels on the Y-axis to create visual tremors. This series of micro actions ensures that dangerous wiring is not solidified by the storage structure.

[0087] Another example is the timestamp counterexample in S400, namely the model {t:0}, which maps the internal variable t to the business field UnixTimestamp. The floating window rendered near the input stub of the target node displays the following message: "Connection refused! The target node's constraint 'input must be positive' is violated when the source output UnixTimestamp is 0 (January 1, 1970 00:00:00UTC)."

[0088] As another example, suppose a source node outputs a 32-bit signed integer, with the following post-constraint: The target node input is a 16-bit signed integer, with the following pre-constraints: The problematic proposition in system construction would be:

[0089] The SMT solver will easily find a counterexample, for example This value is valid within the range of 32-bit integers, but when truncated to a 16-bit integer, it overflows, becoming -32768, which is still within the valid range of 16-bit integers. However, if the solver finds... After truncation, more complex wrapping will occur. The solver will find a specific value that clearly causes the loss of type information or numerical error. The counterexample projected from this would be: "Connection refused! When the source output value is 32768, it will cause implicit truncation to a 16-bit integer, posing a risk of data overflow."

[0090] This embodiment also provides a function node semantic adaptation system based on formal verification, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0091] Figure 2 This is a structural block diagram of a function node semantic adaptation system based on formal verification according to an embodiment of the present invention, such as... Figure 2 As shown, the system includes: The constraint extraction module is a state synchronization server component residing in the front-end browser or client-side background environment. Its hardware execution layer relies on an asynchronous non-blocking thread pool allocated by the central processing unit (CPU) and runs in a background worker (WebWorker) or BFF proxy layer that is detached from the main graphics rendering pipeline. This ensures that the large-scale metadata parsing process does not consume computing resources that would cause interface lag.

[0092] This module comprises a metadata parsing subunit and a hash dictionary management subunit. The metadata parsing subunit deserializes the component configuration specifications retrieved via network sockets into an internally understood range tree using a recursive descent parser. The hash dictionary management subunit listens for node mounting and destruction lifecycle events from the global Document Object Model (DOM) and performs garbage collection and dynamic addition / deletion operations on memory entries accordingly.

[0093] This module maintains a globally unique and thread-safe hash table named GlobalConstraintDict in the heap memory space. The key-value pair structure of this table includes: the Key field is a universally unique identifier string Node_UUID that uniquely identifies the node instance; the Value field is a composite object memory block, which contains two one-dimensional memory address pointers, pointing to the local pre-constraint abstract syntax tree Pre_Formula and the local post-constraint abstract syntax tree Post_Formula allocated in the heap after the node is parsed.

[0094] This module initiates stateless requests to the backend service cluster to fetch metadata via standard asynchronous network interfaces such as FetchAPI or XMLHttpRequest; internally, it provides access to the Hall logic conversion module, which is in the same memory scope, through direct memory address addressing operations, with an access time complexity of O(log n). High-speed data reading channel.

[0095] The logic transformation module is the core routing and transformation gateway that handles the input stream from the user interface and the underlying rigorous computational model. This module runs directly in the main execution context of browser kernels such as the JavaScriptV8 engine, relying on a fast object allocator for high-frequency memory object assembly.

[0096] This module includes a connection event interception subunit and an AST splicing and mutation subunit. The connection event interception subunit is bound to the mouse pointer event hook of the graphics container, specifically intercepting drag operations originating from the starting point and their displacement increments, extracting and exposing the physical handles and logical identifiers of the sockets involving the two connected parties. The AST splicing and mutation subunit uses a depth-first object deep copy algorithm to copy independent source and target trees in memory, then instantiates logical operator nodes such as OP_NOT and OP_AND, and splices them into a complete, giant abstract syntax tree representing the illegal proposition at the physical memory level by reloading child node pointers.

[0097] This module maintains a core state container object defined as HoareTriplet_DTO in its runtime memory's stack area or short-lived heap area. The physical memory structure of this container object includes: Pointing representation The memory address attribute `sourceType` of the root node in the expression graph, and the corresponding pointer. The expression graph root node's memory address pointer, and a single-bit SemanticConflictFlag boolean scalar used to record the physical quantity verification status.

[0098] This module listens for and consumes the onLineDraw and related DOM composition event streams issued by the graphical application programming interface through a registry mode; and after completing the abstract tree assembly, it generates plain text by concatenating string streams in a buffer and pushes formal computational payloads that strictly conform to the SMT-LIBv2 specification to subsequent modules.

[0099] The theorem solving engine module is composed of high-efficiency C / C++ low-level verifier source code, which is cross-compiled into network assembly binary format by a specific compiler, such as WebAssembly or WASM format. This module is forced to reside in a completely independent WebWorker worker thread opened by the browser through system calls, exclusively occupying the pre-allocated linear contiguous RAM space in the motherboard memory, and performing logical resolution and vector bit operations based on the arithmetic logic unit (ALU).

[0100] This module includes a proposition dimensionality reduction subunit and an SAT search state machine unit. The proposition dimensionality reduction subunit utilizes pre-compilation optimization techniques to perform constant folding and dead code elimination, such as automatically identifying and deleting statements containing... This form of synonymous repetition greatly reduces the search depth. The SAT search state machine unit encapsulates the complex conflict-driven clause learning main loop, executes decision variable allocation, Boolean constraint propagation, and historical state backtracking mechanism when conflicts occur.

[0101] This module allocates a large-scale array of consecutive integers in its dedicated linear memory space. These arrays form a matrix of conjunctive normal form clauses generated by the Tseitin transformation algorithm. Each row in the matrix represents a clause constraint, and the values ​​of the matrix elements point to the corresponding feature variable handle indices through a specific positive and negative encoding protocol.

[0102] Communication between this module and the main thread is strictly limited to using the browser's standard, lock-free postMessage channel. To eliminate the performance overhead of deep copying during transmission, the module directly receives string or byte streams from the Hall logic conversion module via ArrayBuffer ownership transfer. After execution, it sends back a payload packet containing the result status code and JSON-formatted deserialized variable name-value pairs.

[0103] The counterexample projection module is responsible for reverse engineering the obscure machine logic proof results into visible graphical user interface elements. It is a presentation system directly scheduled by the main UI rendering thread, and its hardware acceleration relies on the hardware rendering interface provided by the computer graphics processing unit to handle high frame rate interface reconstruction actions.

[0104] This module includes a counterexample translation subunit and a rendering intervention subunit. The counterexample translation subunit traverses the mapping hash table, reads the anonymous symbolic variables allocated internally by the engine, and reverse-lookups the original dictionary to deduce the corresponding original business field names. The rendering intervention subunit directly injects the rendering override pipeline into the browser's display list or scene layer, taking over and replacing the original line drawing shader logic.

[0105] This module maintains a frequently updated ErrorOverlay_StateTree coordinate tree object entity in the context of the frame rendering loop. Its memory distribution includes a triggerCoords floating-point array for storing the real-time screen absolute coordinates of the mouse focus, and a warningText string buffer that binds to the coordinate position and contains the source error information text.

[0106] This module listens for the dedicated VERIFY_FAILED exception subscription message dispatched by the underlying event bus, extracts the message payload containing specific numbers and fields, and then directly initiates a synchronous or asynchronous call to the graphics engine kernel through system-level API instructions to force a redraw, directly flushing the exception dashed pattern and pop-up window into the video memory buffer frame.

[0107] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0108] Embodiments of the present invention also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed.

[0109] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0110] Embodiments of the present invention also provide an electronic device including a memory and a processor, the memory storing a computer program and the processor being configured to run the computer program to perform the steps in any of the above method embodiments.

[0111] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0112] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0113] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0114] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0115] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0116] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, in essence, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0117] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for semantic adaptation of function nodes based on formal verification, characterized in that, include: Obtain component drag events, retrieve abstract syntax tree metadata based on node unique identifiers, and generate local post-constraint objects and local pre-constraint objects. The abstract syntax tree metadata corresponds to the function node being operated on. Extract the source post-constraints from the source node cache and the target pre-constraints from the target node cache; Based on the source post-constraints, the target pre-constraints, and the connection transformation mapping relationship, a joint violation proof proposition is constructed, and the joint violation proof proposition is converted into a theoretical formula string; The modular theory formula string is passed to the theorem solving engine, which performs the first compilation to output the binary state flag. If the joint violation proof proposition is true, extract the variable assignment model, block the rendering of the document object model connection, and project the violation data source view based on the variable assignment model.

2. The method according to claim 1, characterized in that, Based on the source post-constraints, the target pre-constraints, and the connection transformation mapping relationship, the joint violation proof propositions are constructed as follows: The root node of the target abstract syntax tree corresponding to the target pre-constraint is encapsulated with a logical NOT operator; The target abstract syntax tree encapsulating the logical NOT operator is merged with the source abstract syntax tree corresponding to the source post-constraint using the logical AND operator; Calculate the semantic distance between the source service tag corresponding to the source node and the target service tag corresponding to the target node; If the semantic distance is greater than a preset compatibility threshold, business conflict logic constants are injected into the merged abstract syntax tree to generate a complete joint violation proof proposition abstract syntax tree.

3. The method according to claim 2, characterized in that, The calculation of the semantic distance between the source service tag corresponding to the source node and the target service tag corresponding to the target node includes: In a pre-constructed directed acyclic graph of physical dimensions, the source service label and the target service label are mapped to source graph nodes and target graph nodes, respectively. Calculate the number of undirected shortest path edges from the source graph node to the target graph node; The number of edges in the undirected shortest path is used as the semantic distance.

4. The method according to claim 1, characterized in that, The projection of a violation data source view based on the variable assignment model includes: Obtain the exception data packet returned by the theorem solving engine, wherein the exception data packet contains an abstract feature vector; By reverse querying the operation status dictionary, the abstract feature vector is mapped back to the original business field names visible to the user interface and the extreme value data that caused the crash. The screen tensor relative coordinates of the target node input stake are obtained using the coordinate system transformation operator; At the offset position determined based on the screen tensor relative coordinates, a floating alarm window containing the original business field name and the extreme value data is rendered.

5. The method according to claim 1, characterized in that, The method further includes: The source post-constraint is characterized as a range of values ​​including a lower bound and an upper bound of a real number. Perform a forward operation along the abstract syntax tree structure on the value range to obtain the mapped output range; Determine whether there is an intersection between the mapped output interval and the legal interval formed by the target pre-constraint conditions, and control the rendering of the connection based on the intersection determination result.

6. The method according to claim 1, characterized in that, Blocking document object model connection rendering includes: Mount the graphical user interface override pipeline in the main rendering thread; Destroy the pre-instantiated connection object associated with the connection attempt event; Calculate the Bézier curve path from the starting point to the ending point along the mouse drag trajectory; The canvas rendering interface is invoked along the Bézier curve path to draw a dashed pixel pattern with a specific warning color and a vibration animation frame.

7. A function node semantic adaptation system based on formal verification, characterized in that, include: The constraint extraction module is used to obtain component drag events, obtain abstract syntax tree metadata based on the node's unique identifier, and generate local post-constraint objects and local pre-constraint objects. The abstract syntax tree metadata corresponds to the node of the function being operated on. The logic transformation module is used to extract the source post-constraints cached in the source node and the target pre-constraints cached in the target node. Based on the source post-constraints, the target pre-constraints, and the connection transformation mapping relationship, a joint violation proof proposition is constructed, and the joint violation proof proposition is converted into a theoretical formula string; The theorem solving engine module is used to pass the modular theory formula string to the theorem solving engine, and the theorem solving engine performs the first compilation to output the binary state flag; The counterexample projection module is used to extract the variable assignment model and block the rendering of the document object model connection when the joint violation proof proposition is true, and to project a violation data source view based on the variable assignment model.

8. The system according to claim 7, characterized in that, Based on the source post-constraints, the target pre-constraints, and the connection transformation mapping relationship, the joint violation proof propositions are constructed as follows: The root node of the target abstract syntax tree corresponding to the target pre-constraint is encapsulated with a logical NOT operator; The target abstract syntax tree encapsulating the logical NOT operator is merged with the source abstract syntax tree corresponding to the source post-constraint using the logical AND operator; Calculate the semantic distance between the source service tag corresponding to the source node and the target service tag corresponding to the target node; If the semantic distance is greater than a preset compatibility threshold, business conflict logic constants are injected into the merged abstract syntax tree to generate a complete joint violation proof proposition abstract syntax tree.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program is configured to perform the method described in any one of claims 1 to 6 when executed.

10. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to perform the method as described in any one of claims 1 to 6.

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