A conditional compilation and dynamic feature management system
By using conditional compilation and dynamic feature management system, the problems of bloated output size, performance loss and security risks in traditional software building and deployment are solved. It achieves streamlined build output, improved runtime flexibility and startup performance, and ensures security and configuration correctness.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HANGZHOU AMTD YINGANG DIGITAL TECH CO LTD
- Filing Date
- 2026-04-05
- Publication Date
- 2026-06-30
Smart Images
Figure CN122308842A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the fields of software engineering and program optimization technology, and in particular to a conditional compilation and runtime feature dynamic management system based on build-time flags, which is applicable to large command-line tools, configurable applications, and software systems that require both build-time optimization and runtime flexibility. Background Technology
[0002] Traditional software construction and deployment face the following technical challenges.
[0003] 1. Increased output size: Traditional static compilation methods package all functional modules into the final executable file. Even if the functions actually called by the user only account for a small part of the whole, the unused modules still occupy storage space and memory resources.
[0004] 2. Runtime performance loss: Feature availability checks are performed during program execution, introducing unnecessary branching and conditional jumps, increasing CPU cycle consumption.
[0005] 3. Accumulated startup delay: The initialization logic of a large number of unused modules is executed when the program starts, which significantly prolongs the cold start time and affects the user experience.
[0006] 4. Expanded security attack surface: The code logic of disabled functions still exists in the binary file, which may be maliciously used as an attack vector, increasing the system security risk.
[0007] 5. High configuration management complexity: Runtime configuration is deeply coupled with business code, lacking a clear separation of concerns mechanism, making configuration changes difficult and prone to introducing errors.
[0008] Existing technical solutions such as C language preprocessors and Webpack's DefinePlugin provide basic conditional compilation capabilities, but they have the following limitations: for example, they lack organic integration with runtime feature dynamic control mechanisms, cannot effectively manage dependencies and conflicts between features, lack automated dead code elimination and verification methods, and do not provide automatic generation and synchronization mechanisms for feature configurations. Summary of the Invention
[0009] This invention provides a conditional compilation and dynamic feature management system, which achieves collaborative work between compile-time code optimization and runtime behavior control through a layered architecture of build-time conditional import and runtime feature checking.
[0010] This invention balances streamlined build artifacts with runtime flexibility, effectively solving problems such as bloated build artifacts, insufficient runtime flexibility, and chaotic feature dependencies in existing software systems. It can be widely applied to feature management and build optimization of large-scale software systems.
[0011] I. Conditional Import Mechanism During Build (a) Importing modules during construction The core of this invention lies in the design and implementation of a build-time conditional import module. This module is configured to selectively import modules using a conditional expression pattern. The conditional expression is evaluated during the build phase, and the module bundling tool completely removes module dependencies corresponding to inactive code branches during the build process. The build-time conditional import module uses conditional compilation interface functions provided by the module bundling tool. This design leverages the conditional compilation capabilities of modern module bundling tools (such as webpack, Rollup, esbuild, etc.) to achieve selective bundling of module dependencies by statically evaluating the conditional expression during the build phase.
[0012] (ii) Conditional import mode Build-time conditional imports support three main modes: conditional import statements, conditional export statements, and conditional require calls. Conditional import statements are the basic mode of build-time conditional imports, allowing the use of conditional expressions within module import statements. When the conditional expression evaluates to true, the corresponding module is imported normally; when the conditional expression evaluates to false, the import statement is completely removed, and the module is not packaged into the build artifact. Typical forms of conditional import statements include conditional imports using the ternary operator (selectively importing different modules or null values based on a condition), conditional imports using the logical AND operator (importing modules only when the condition is met), and imports using conditional block statements (importing modules within an if statement block). Conditional export statements allow modules to selectively export functionality based on conditional expressions. When the conditional expression evaluates to true, the corresponding functionality is exported; when the conditional expression evaluates to false, the export statement is removed, and external modules cannot access the functionality. Application scenarios for conditional export statements include exporting different API interfaces based on feature flags, exporting different versions of implementations in different environments, and conditionally exposing debugging tools or internal interfaces. Conditional require calls support conditional module loading in the CommonJS module system. The require call is wrapped in a conditional expression, and the build tools identify and process these conditional calls during the static analysis phase. Features include support for dynamically calculating module paths, compatibility with the CommonJS module system, and the ability to be used for progressive migration of large legacy codebases.
[0013] (III) Sources of evaluation of conditional expressions Conditional expressions support three evaluation sources: Boolean constants, environment variable references, and attribute flag references. Boolean constants are the simplest source, directly using the literals `true` or `false`. They are suitable for fixed conditional judgments and are typically used for temporary controls or permanent function switches during development and debugging. Typical applications include isolating development environment-specific code, conditional inclusion of debugging tools, and permanently disabling experimental features. Environment variable references allow conditional expressions to obtain values from variables in the build environment. This supports using different attribute configurations in different build environments (e.g., development, testing, production) to achieve environment-aware build optimization. Features include support for reading from environment variable objects such as `process.env`, variable substitution during build without retaining environment variable references, and support for default value settings and type conversions. Attribute flag references are the core source of conditional expressions, allowing the definition of attribute flags to be referenced in the code. The value of the attribute flag is determined by the build configuration and is replaced with the actual Boolean value during the build phase. Advantages include centralized management of all attribute switches, support for type safety of attribute flags, and ease of tracking and auditing attribute configurations.
[0014] (iv) Code branch elimination strategy The code branch elimination in the build artifact employs a two-phase strategy combining static replacement and dead code elimination to ensure complete elimination of code branches. In the static replacement phase, the build tool replaces conditional expressions with their evaluated results (true or false). After replacement, the original conditional judgments become constant judgments, creating conditions for subsequent dead code elimination. The specific operations of static replacement include identifying conditional expressions in the code, calculating the expression value according to the build configuration, replacing the expression with the calculated result, and preserving the replaced code structure. In the dead code elimination phase, the build tool analyzes the replaced code, identifies and removes code branches that will never be executed. For cases where conditional judgments become constants (true or false), executing branches are preserved, and non-executable branches are removed. The specific operations of dead code elimination include identifying constant conditions in if statements, removing branch code with false conditions, inlining branch code with true conditions, cleaning up module dependencies that are no longer referenced, and removing empty statement blocks and invalid code. This two-phase strategy ensures the complete elimination of code branches, removing not only the conditional judgments themselves but also all related dead code, minimizing the size of the build artifact.
[0015] II. Layered Characteristic Control Mechanism (a) Layered characteristic control module This invention includes a hierarchical feature control module configured to distinguish between build-time feature control and runtime feature control. The hierarchical design is one of the core innovations of this invention. By distinguishing between the two levels of feature control, a balance between build optimization and runtime flexibility is achieved.
[0016] (ii) Construction-time characteristic control Build-time feature control is implemented through build-phase conditional expressions, completely eliminating inactive code from the build artifacts. Its core features include static decision-making, complete elimination, zero runtime overhead, and streamlined build artifacts. Static decision-making means the feature state is determined during the build phase, retaining no runtime judgment logic; the code in the build artifacts is already in its final form, eliminating the need for runtime conditional checks. Complete elimination means removing the entire module tree from the build artifacts when a feature is inactive, including not only individual files but also all dependent modules referenced by those files, resulting in complete dependency tree elimination. Zero runtime overhead means that since related code has been completely removed, there is no runtime overhead for conditional checks or feature checks, achieving execution efficiency equivalent to code without feature control. Streamlined build artifacts mean that unused functionality will not appear in the build artifacts, significantly reducing artifact size and lowering loading and execution resource consumption. Build-time feature control is suitable for scenarios such as features that are determined not to be used in certain environments, stable version releases of experimental features, differentiated builds for customer-customized versions, and dedicated code isolation for different platforms.
[0017] (III) Runtime Feature Control Runtime feature control is implemented through runtime state query callbacks. The code exists in the build artifacts, but its execution path is controlled by the runtime state. Its core features include dynamic decision-making, code preservation, flexible adjustment, and remote control. Dynamic decision-making means that the feature state is determined at runtime and can be dynamically adjusted based on configuration services, user settings, or system state. The state query callbacks re-evaluate the decision each time a command is retrieved, ensuring real-time decision-making. Code preservation means that the relevant code exists in the build artifacts, but the execution path is controlled by the runtime state. All functional branches are packaged, and the runtime selects the execution path based on the state. Flexible adjustment means that feature states can be adjusted without redeployment, suitable for scenarios requiring rapid response to business changes. Remote control means that it can be integrated with remote configuration services to achieve centralized feature management, supporting advanced scenarios such as canary releases and A / B testing. Runtime feature control is suitable for features requiring dynamic runtime adjustment, feature switches integrated with remote configuration services, user-configurable feature options, and canary release features requiring rapid rollback.
[0018] (iv) Runtime characteristic check module This invention also includes a runtime feature checking module, configured to query the real-time status of feature flags through a remote configuration service during program execution, and dynamically control the execution path of compiled code. Its core functions include remote configuration service integration, real-time status query, execution path control, and status change notification. Regarding remote configuration service integration, the runtime feature checking module establishes a connection with the remote configuration service, supporting various configuration service types, including feature switch management platforms (such as LaunchDarkly, Split, Optimizely), self-built configuration center services, and distributed configuration storage systems. For real-time status query, the module provides real-time query capabilities for feature flag status, supporting both synchronous and asynchronous query modes. Query results include feature status, variant values, evaluation reasons, and other information, and support caching and refresh strategies for query results. Regarding execution path control, it dynamically controls the code execution path based on the query results, including dynamic selection of conditional branches, dynamic enabling / disabling of function entry points, and dynamic switching of behavior modes. Regarding status change notification, it supports subscribing to feature flag status change notifications, triggering a callback function when the feature status changes, supporting batch change notifications, and providing a comparison of the status before and after the change.
[0019] III. On-demand loading mechanism (a) Loading modules on demand This invention includes an on-demand loading module configured to delay the initialization of heavy subsystems using a dynamic module loading mechanism, performing loading and initialization only on the first access. Its core idea is to postpone the loading of heavy subsystems from program startup to the first use. This strategy significantly improves program startup performance, especially in large software systems.
[0020] (ii) Lazy loading strategy The lazy loading workflow consists of five phases: placeholder creation, access interception, dynamic loading, initialization execution, and reference replacement. In the placeholder creation phase, the program initialization phase creates lightweight placeholder objects for the lazy-loaded subsystem. These placeholder objects contain only necessary metadata and do not load the actual implementation code. In the access interception phase, when the program first accesses the functionality of the lazy-loaded subsystem, the placeholder object intercepts the access request. In the dynamic loading phase, after the access is intercepted, the dynamic module loading mechanism is triggered, loading the corresponding module code from the build artifacts. In the initialization execution phase, after the module is loaded, the subsystem's initialization logic is executed, creating a complete functional instance. In the reference replacement phase, the placeholder object is replaced with the actual subsystem instance, and subsequent accesses directly use the initialized instance.
[0021] (iii) Subsystem types with lazy loading Heavyweight subsystems that use lazy loading for on-demand modules include observability monitoring frameworks, remote procedure call (RPC) frameworks, data analytics frameworks, and feature management services. Observability monitoring frameworks are a crucial component of large software systems, responsible for collecting and reporting runtime metrics, logs, and tracing data. These frameworks typically include metric collectors, log processors, distributed tracing clients, and monitoring data exporters. The advantages of lazy loading observability frameworks include reduced dependency initialization overhead at startup, avoiding loading related code in scenarios where monitoring is unnecessary, and supporting on-demand enabling of monitoring functions. Remote procedure call (RPC) frameworks support cross-service communication calls and involve complex network protocol implementations and serialization logic. They typically include service discovery clients, load balancers, serialization / deserialization engines, and network connection pool managers. The advantages of lazy loading RPC frameworks include reduced pre-establishment overhead for network connections, avoiding loading remote call-related code in local execution scenarios, and supporting on-demand connection establishment and management. Data analytics frameworks provide data processing and analysis capabilities, typically containing a large amount of computational logic and data processing tools, including data collectors, data transformation engines, statistical analysis tools, and report generators. The advantages of lazy loading of data analytics frameworks include reducing the pre-occupancy of computing resources, avoiding loading related code in non-analysis scenarios, and supporting on-demand execution of analysis tasks. Feature management services are a core component of the system, responsible for the management and evaluation of feature flags, including feature flag storage, evaluation engine, configuration synchronization service, and audit log service. The advantages of lazy loading of feature management services include avoiding the overhead of feature state initialization at startup, supporting the expansion of the feature management service's own capabilities, and reducing the dependency complexity of the core startup path.
[0022] IV. Code Elimination Verification Mechanism (a) Code Elimination Verification Module This invention includes a code elimination verification module, configured to verify whether the corresponding code of inactive features has been completely eliminated from the final build artifact, and to detect residual code and generate a verification report through runtime reflection or static analysis.
[0023] (ii) The necessity of verification In complex software systems, ensuring the complete removal of inactive feature code is crucial, primarily in four areas: security, performance optimization, intellectual property protection, and maintenance clarity. Regarding security, inactive features may contain sensitive logic or security-related code; if left in the build artifacts, they could be maliciously exploited. For performance optimization, residual dead code increases the size of the build artifacts, impacting loading and execution performance. Regarding intellectual property protection, unreleased feature code may involve trade secrets, requiring assurance against accidental disclosure. Regarding maintenance clarity, verifying code removal helps developers understand the actual content of the build artifacts, facilitating problem diagnosis and optimization.
[0024] (III) Verification Methods The code elimination verification module supports two verification methods: runtime reflection verification and static analysis verification. Runtime reflection verification checks the code structure at runtime using reflection, including module existence checks (checking if a specific module exists in the runtime environment), function reference checks (checking if a specific function or method can be referenced), object attribute checks (checking if a specific object contains attributes or methods related to inactive functions), and dynamic import tests (attempting to dynamically import modules that should be eliminated). Its features include verification results reflecting the actual runtime state, integration and execution in the test environment, and support for continuous monitoring and automated testing. Static analysis verification analyzes the build artifacts after the build is complete, including source code mapping analysis (analyzing the correspondence between the build artifacts and source code through source code mapping files), AST analysis (parsing the abstract syntax tree of the build artifacts), symbol table analysis (analyzing symbol definitions and references in the build artifacts), and volume difference comparison (comparing the volume differences of build artifacts under different feature configurations). Its features include verification without running the program, detection of problems difficult to find at runtime, and support for detailed code-level reports.
[0025] (iv) Generation of verification report The code elimination verification module generates a detailed verification report, including four parts: a verification result summary, detailed check item results, residual code details, and improvement suggestions. The verification result summary includes the overall verification status (pass / fail), the total number of checks and the number of pass / fail items, and an overview of key findings. The detailed check item results include the elimination verification results for each feature flag, the elimination status for each module, and the elimination status for each function / method. The residual code details include the location information of the residual code (file, line number), the content fragments of the residual code, and an analysis of the reasons for its remnant status. The improvement suggestions include remedial suggestions for failed verification items, optimization suggestions for the code elimination strategy, and build configuration adjustment suggestions.
[0026] V. Feature Dependency Management Mechanism (a) Feature Dependency Management Module This invention includes a feature dependency management module, configured to manage the dependency and mutual exclusion relationships between feature flags, including pre-dependency checks and conflict detection, and verifying the legality of the configuration and reporting violations during the build phase.
[0027] (ii) Types of Dependency Relationships The feature dependency management module manages two types of relationships: dependency and mutual exclusion. A dependency indicates that the normal operation of one feature depends on the activation state of another feature. This includes prerequisite dependencies (feature A requires feature B to be activated first), transitive dependencies (feature A depends on feature B, feature B depends on feature C, then feature A is transitively dependent on feature C), and optional dependencies (feature A can utilize the functionality of feature B, but the absence of feature B does not affect the basic functionality of feature A). A mutual exclusion indicates that two or more features cannot be activated simultaneously. This includes complete mutual exclusion (features A and B cannot be activated simultaneously; one must be selected or neither must be selected), conditional mutual exclusion (features A and B cannot be activated simultaneously under specific conditions), and intra-group mutual exclusion (at most one feature in a group can be activated, forming a single-selection relationship).
[0028] (iii) Pre-dependency check The feature dependency management module performs pre-dependency checks to ensure the legality of feature configurations. Its check process includes five steps: dependency graph construction, dependency chain analysis, reachability verification, circular dependency detection, and violation reporting. In the dependency graph construction phase, a dependency graph is built based on feature flag definitions, where nodes represent feature flags and edges represent dependencies. In the dependency chain analysis phase, the complete dependency chain for each active feature flag is analyzed, identifying all direct and indirect dependencies. In the reachability verification phase, it verifies whether all feature flags on the dependency chain are active; if any inactive dependencies exist, they are marked as dependency violations. In the circular dependency detection phase, it checks for circular dependencies in the dependency graph, as circular dependencies can prevent the determination of the correct activation order. In the violation reporting phase, a detailed error report is generated for any discovered dependency violations, explaining the violating feature flag and the missing dependency.
[0029] (iv) Conflict detection The feature dependency management module performs conflict detection to prevent mutually exclusive features from activating simultaneously. Its detection process includes four steps: mutual exclusion rule parsing, activation status checking, condition evaluation, and conflict reporting. In the mutual exclusion rule parsing phase, the mutual exclusion rules in the feature flag definitions are parsed, and a mutual exclusion relationship matrix is constructed. In the activation status checking phase, it checks whether there are mutual exclusion conflicts among currently active feature flag combinations. In the condition evaluation phase, it evaluates whether the current condition triggers the mutual exclusion constraint for mutually exclusive conditions. In the conflict reporting phase, a detailed error report is generated for any detected conflicts, explaining the conflicting feature flags and the reason for the mutual exclusion.
[0030] (v) Validation and blocking during construction The feature dependency management module verifies configuration validity and reports violations during the build phase, verifies feature flag dependencies and conflicts, reports errors during the build process, and prevents unauthorized configurations from entering the build process. The advantages of build-time verification include early problem detection (identifying issues during the build phase to avoid unpredictable runtime behavior), rapid feedback (developers receive immediate feedback on configuration errors without waiting for deployment and testing), prevention of unauthorized artifacts (unauthorized configurations are prevented from entering the build process, ensuring the correctness of build artifacts), and integration with CI / CD (build-time verification can be integrated into continuous integration processes to automatically detect configuration problems).
[0031] VI. Feature Documentation Generation Mechanism (a) Feature document generation module This invention includes a feature document generation module, configured to automatically generate feature configuration documents based on the definition metadata of feature flags. The documents include feature descriptions, current status, dependencies, and information on the impact of code size.
[0032] (II) Document Generation Principles The feature documentation generation module uses the metadata defining feature tags to automatically extract and organize feature-related information, generating structured configuration documents. This approach avoids the tediousness and error-proneness of manual document maintenance, ensuring consistency between the documentation and the actual configuration. Metadata sources include feature tag definition files, build configuration files, environment variable configurations, dependency definitions, and historical change records.
[0033] (III) Document Content The automatically generated feature configuration document contains information in four aspects: feature description, current status, dependencies, and code size impact. The feature description provides basic information about the feature flag, including the feature name and unique identifier, functional description and usage, version and change history, and the responsible person and maintenance team. The current status displays the feature flag's configuration, including the default status at build time, the configuration status in various environments, the current runtime status (if applicable), and the status change history. Dependencies show the relationship between the feature flag and other features, including a list of prerequisite dependencies, a list of dependent features, a list of mutually exclusive features, and a dependency diagram. Code size impact shows the effect of the feature flag on the build artifacts, including the increased code size when enabled, a list of related modules and files, the size contribution of dependent packages, and optimization suggestions.
[0034] (iv) Document Format and Output The feature documentation generation module supports multiple output formats, including Markdown (suitable for use in code repositories and documentation sites), HTML (suitable for display in web interfaces), JSON (suitable for programmatic processing and integration), and PDF (suitable for formal documents and reports).
[0035] VII. Characteristic Flag Definition and Configuration Mechanism (a) Characteristic Flag Definition Module This invention includes a feature flag definition module, configured to centrally define all feature flags, ensuring type safety and configuration consistency. The feature flag definition module manages all feature flags through centralized definition, offering advantages such as a single data source (all feature flag definitions are centralized in one location, avoiding maintenance difficulties caused by scattered definitions), type safety (the definition and use of feature flags are constrained by a type system, detecting type errors during the compilation phase), configuration consistency (ensuring that build configurations, runtime checks, and documentation use the same feature flag definitions, avoiding inconsistencies), and ease of auditing (centralized definition facilitates auditing the completeness and correctness of feature flags).
[0036] (ii) Characteristic Marker Types This invention supports twelve feature types: distributed collaboration mode, intelligent assistant mode, automated triggering mechanism, remote connection capability, voice interaction capability, external system integration mode, workflow script support, context compression optimization, proactive service mode, system monitoring capability, background service mode, and direct connection mode. Distributed collaboration mode supports multi-user collaborative editing and synchronization, including real-time collaboration, conflict resolution, and version synchronization. Intelligent assistant mode provides AI-assisted functions, including intelligent code completion, code suggestions, and problem diagnosis. Automated triggering mechanism supports event- or condition-based automated operations, including file monitoring, scheduled tasks, and conditional triggering. Remote connection capability supports remote server connection and operation, including SSH connection, remote execution, and file transfer. Voice interaction capability supports voice input and output functions, including speech recognition, speech synthesis, and voice commands. External system integration mode supports integration with third-party systems, including API integration, data synchronization, and message notification. Workflow script support supports custom workflows and script execution, including script engines, task orchestration, and flow control. Context compression optimization supports intelligent compression of context information, reducing memory usage and network transmission volume. The proactive service mode supports proactive push and reminder functions, including message push, status reminders, and suggestion prompts. System monitoring capabilities support monitoring and reporting of system operation status, including performance monitoring, error tracing, and resource statistics. The background service mode supports background operation and daemon process functions, including background tasks, scheduled services, and daemon processes. The direct connection mode supports point-to-point direct connection communication, bypassing intermediate layers to achieve efficient data transmission.
[0037] (III) Building the configuration module This invention also includes a build configuration module configured to set feature flag states based on environment variables and pass them to the module packaging tool. The configuration process includes environment variable reading (reading the configuration values of feature flags from variables in the build environment), default value application (applying predefined default values for unconfigured feature flags), type conversion (converting environment variable values to the type required for the feature flags, typically Boolean values), configuration validation (verifying the legality and consistency of the configuration values), and passing the configuration to the build tool (passing the final configuration to the module packaging tool for evaluating conditional expressions). Configuration values are determined according to the following priority (from highest to lowest): build command-line arguments, environment variables, configuration files, and default values in feature flag definitions.
[0038] 8. Computer-readable storage media The present invention also provides a computer-readable storage medium storing a computer program thereon, wherein the program, when executed by a processor, implements the functions of the conditional compilation and dynamic feature management system as described in any one of claims 1 to 9. The computer-readable storage medium may include, but is not limited to, random access memory (RAM, for storing runtime programs and data), read-only memory (ROM, for storing fixed program code), programmable read-only memory (PROM, a storage medium that supports one-time programming), erasable programmable read-only memory (EPROM, a programmable storage medium that supports ultraviolet erasure), electrically erasable programmable read-only memory (EEPROM, a programmable storage medium that supports electrical erasure), flash memory (such as solid-state drives (SSDs), USB flash drives, SD cards, etc.), magnetic storage media (such as hard disk drives (HDDs), magnetic tapes, etc.), and optical storage media (such as CD-ROMs, DVDs, Blu-ray discs, etc.). Beneficial effects
[0039] Compared with existing technologies, this invention has the following beneficial effects: In terms of streamlined build artifacts, the conditional import mechanism during build completely eliminates inactive code branches, significantly reducing the size of the build artifacts and lowering resource consumption for loading and execution. Regarding runtime flexibility, the layered feature control mechanism supports dynamic adjustment of feature states at runtime while ensuring build optimization, meeting the needs of rapidly changing business requirements. In terms of startup performance optimization, the on-demand loading mechanism delays the initialization of heavy subsystems, significantly improving program startup performance and enhancing user experience. Regarding security, the code elimination verification mechanism ensures that inactive feature code is completely eliminated, preventing sensitive code leakage and potential security risks. Regarding configuration correctness, the feature dependency management module verifies the legality of feature configurations during the build phase, preventing runtime errors caused by dependency violations and conflicts. Regarding documentation consistency, the feature documentation generation module automatically generates documentation consistent with the actual configuration, reducing documentation maintenance costs and improving documentation accuracy. Regarding type safety, the feature flag definition module centrally manages feature flags, utilizing a type system to ensure the type safety of the configuration and detect errors during the compilation phase. Regarding improvements in development efficiency, the feature configuration process is simplified by building a configuration module. Developers can easily control feature status through environment variables, thereby improving development and testing efficiency. In summary, this invention provides a complete solution for conditional compilation and dynamic feature management, achieving collaborative work between compile-time code optimization and runtime behavior control. It balances streamlined build artifacts with runtime flexibility and can be widely applied to feature management and build optimization of large-scale software systems, including but not limited to command-line tools, desktop applications, web applications, and microservice architectures. Attached Figure Description
[0040] Figure 1 This is a layered architecture diagram of the system, showing the two-layer architecture of conditional import during construction and feature checking at runtime. It annotates the evaluation process of conditional expressions during the construction phase, shows the real-time status query process of the remote configuration service, and specifically marks the collaborative relationship between the two control mechanisms.
[0041] Figure 2 The flowchart for conditional import during build time details the processing flow of the module packaging tool, including key steps such as conditional expression parsing, module dependency analysis, and elimination of inactive code. It also provides an example of the on-demand loading mechanism for heavy subsystems.
[0042] Figure 3 The runtime feature check sequence diagram shows the status query process of feature flags, including remote configuration service calls, multi-level cache checks, and dynamic control of execution paths, while also marking the trigger points of status query callbacks.
[0043] Figure 4This diagram illustrates the code elimination verification process, showcasing the optimization effect by comparing the differences in code structure before and after the build. It also marks the detection points of the static analysis tool and provides examples of the generation logic and content format of the verification report.
[0044] Figure 5 It is a feature dependency graph that graphically displays the complex dependency network between feature tags, clearly marks key prerequisite dependencies and conflict relationships, and includes decision points for legality checks on feature combinations during the build process.
[0045] Figure 6 Automatically generate flowcharts for documents, fully demonstrating the transformation process from metadata to the final document, including key steps such as feature description extraction, state collection, dependency analysis, and impact assessment, and highlighting the implementation details of the automatic filling mechanism for document templates.
[0046] Figure 7 To provide a timing diagram for on-demand loading, this document details the delayed initialization process of heavy-duty subsystems, including the initial access triggering conditions, dynamic loading implementation, initialization execution flow, and other aspects, with special annotations of the critical paths that have the greatest impact on system performance.
[0047] Figure 8 The system component interaction diagram comprehensively displays the data flow relationships between various functional modules, including the feature flag definition module, build configuration module, dependency management module, and documentation generation module, clearly marking the core control flow and interaction sequence during system operation. Detailed Implementation
[0048] Specific Implementation Example 1: Conditional Compilation and Feature Management System of Enterprise-level AI Code Assistant Platform.
[0049] This embodiment uses the "DevStudio Enterprise" enterprise-level AI code assistant platform developed by the applicant as an example to illustrate in detail the application scenarios and technical implementation details of the present invention in actual products. DevStudio Enterprise is an intelligent programming assistant for enterprise development teams, supporting multiple functions such as code completion, intelligent question answering, automated refactoring, and team collaboration. It requires building differentiated product versions according to different customers' license levels, security policies, and functional requirements, while ensuring that the build artifacts of each version are streamlined, have excellent startup performance, and controllable runtime behavior.
[0050] I. System Architecture and Feature Design DevStudio Enterprise employs the layered feature control architecture of this invention, dividing feature flags into two main categories: build-time feature flags and runtime feature flags. Each category of flags assumes different control responsibilities and adopts different technical implementation methods. Build-time feature flags include distributed collaboration mode (DISTRIBUTED_MODE), intelligent assistant mode (ASSISTANT_MODE), automated triggering mechanisms (AUTO_TRIGGER and REMOTE_TRIGGER), remote connectivity capability (REMOTE_ACCESS), voice interaction capability (VOICE_INTERACTION), external system integration mode (EXTERNAL_INTEGRATION), workflow script support (WORKFLOW_SUPPORT), context compression optimization (CONTEXT_COMPRESSION), proactive service mode (PROACTIVE_SERVICE), system monitoring capability (SYSTEM_MONITOR), background service mode (BACKGROUND_SERVICE), and direct connection mode (DIRECT_CONNECTION). The activation status of these features is determined by conditional expressions during the build phase, and the code corresponding to inactive features will be completely eliminated. Runtime feature flags include new model suggestions, enhanced context, smart compaction, and experimental features. These features are dynamically controlled at runtime through a remote configuration service, allowing the feature state to be adjusted without rebuilding.
[0051] The definition of attribute flags is constrained by the TypeScript type system to ensure type safety and compile-time error detection. Below is a pseudocode example of attribute flag definition: ```typescript / / Pseudocode: Attribute Flag Type Definition export const FLAGS = { / / Build-time attribute flags DISTRIBUTED_MODE: 'DISTRIBUTED_MODE', ASSISTANT_MODE: 'ASSISTANT_MODE', / / ... other build-time flags / / Runtime feature flags NEW_MODEL_SUGGESTIONS: 'new_model_suggestions', ENHANCED_CONTEXT: 'enhanced_context', / / ... other runtime flags } as const; / / Type constraints ensure type safety export type BuildTimeFlag = 'DISTRIBUTED_MODE' | 'ASSISTANT_MODE' |...; export type RuntimeFlag = 'new_model_suggestions' | 'enhanced_context' | ...; ``` II. Characteristic Dependencies and Conflict Management DevStudio Enterprise defines complex feature dependencies and uses a feature dependency management module to automatically validate configurations during the build phase, preventing runtime errors caused by dependency violations or feature conflicts. Feature dependencies include three types: prerequisite dependencies, mutual exclusion, and implicit enablement. Prerequisite dependencies mean that one feature requires another feature to be activated before it can function properly. For example, the remote trigger feature (REMOTE_TRIGGER) requires both the automatic triggering mechanism (AUTO_TRIGGER) and remote connectivity capability (REMOTE_ACCESS) to be activated simultaneously. Mutual exclusion means that two features cannot be activated at the same time. For example, the distributed collaboration mode (DISTRIBUTED_MODE) and the intelligent assistant mode (ASSISTANT_MODE) are mutually exclusive because they use different architectural design philosophies. Implicit enablement means that activating one feature automatically activates related features. For example, the distributed collaboration mode implicitly enables the external system integration mode because the collaboration function depends on the communication capabilities of external systems.
[0052] The following is a pseudocode implementation of feature dependency verification: ```typescript / / Pseudocode: Feature Dependency Verification Logic const flagDependencies = [ { flag: 'REMOTE_TRIGGER', requires: ['AUTO_TRIGGER', 'REMOTE_ACCESS'], conflicts: [], }, { flag: 'DISTRIBUTED_MODE', requires: ['AUTO_TRIGGER', 'REMOTE_ACCESS'], conflicts: ['ASSISTANT_MODE'], implies: ['EXTERNAL_INTEGRATION'], }, / / ... Other dependency definitions ; function validateFlagDependencies(enabledFlags: Set <string>) { const errors: string[] = []; for (const dep of flagDependencies) { if (enabledFlags.has(dep.flag)) { / / Check if the prerequisite dependencies are satisfied for (const required of dep.requires) { if (!enabledFlags.has(required)) { errors.push(`Missing feature dependency: ${dep.flag} requires ${required}`); } } / / Check if the mutual exclusion property is conflicting for (const conflict of dep.conflicts) { if (enabledFlags.has(conflict)) { errors.push(`Attribute conflict: ${dep.flag} and ${conflict} are mutually exclusive`); } } } } return { valid: errors.length === 0, errors}; } ``` Before executing the build task, the build system first calls the dependency verification module. If the verification fails, the build process is terminated immediately and detailed error information is output to ensure that illegal configurations cannot enter the build artifacts.
[0053] III. Implementation of Conditional Import During Construction DevStudio Enterprise uses the conditional compilation interface provided by the module packaging tool to implement build-time conditional imports. The core principle is to statically evaluate conditional expressions during the build phase and then remove inactive code branches through dead code elimination technology. The build configuration module reads feature flag states from environment variables, converts them into constant definitions that the module packaging tool can recognize, and then passes them to the build process.
[0054] The specific implementation of the build process is as follows: First, the build configuration module parses the feature flag settings in environment variables or configuration files and builds a feature status dictionary; second, the verification module checks feature dependencies and conflicts to ensure the configuration is valid; then, the feature status is converted into constant definitions (for example, replacing `FLAGS.DISTRIBUTED_MODE` with `true` or `false` literals); next, the module packaging tool performs code packaging, and performs constant folding on conditional expressions during the packaging process; finally, the dead code elimination plugin identifies and removes code branches that will never be executed and their dependent modules.
[0055] Here is a pseudocode example of the configuration build: ```typescript / / Pseudocode: Build Configuration Process async function buildCodeAssist(config) { / / Verify feature dependencies const validation = validateFlagDependencies(config.flags); if (!validation.valid) { console.error('Attribute dependency validation failed:', validation.errors); process.exit(1); } / / Generate constant definitions to replace attribute flag references in the code. const defineFlags = {}; for (const [flag, enabled] of Object.entries(config.flags)) { defineFlags[`process.env.${flag}`] = enabled ? 'true' : 'false'; } / / Perform build await build({ entryPoints: ['. / src / main.ts'], define: defineFlags, / / Constant replacement plugins: [deadCodeEliminationPlugin()], }); } ``` IV. Conditional Imports in Application Code Application code uses conditional import statements to reference modules with specific attributes. These statements are statically analyzed and processed during the build phase. Conditional imports take the form of ternary operators or logical AND operators. The module packaging tool recognizes these patterns and processes them accordingly: when the condition is true, the module reference is retained; when the condition is false, the module reference and its dependency tree are removed.
[0056] Here is a pseudocode example of conditional imports in the application code: ```typescript / / Pseudocode: Conditional import example / / Distributed collaboration module (approx. 850KB), included only when DISTRIBUTED_MODE is enabled const distributedModule = conditionalCompile('DISTRIBUTED_MODE') ? require('. / distributed / collaboration-manager') null; / / AI Assistant Core Module (approximately 1.2MB), included only when ASSISTANT_MODE is enabled. const assistantModule = conditionalCompile('ASSISTANT_MODE') ? require('. / assistant / core-engine') null; / / Voice interaction module (approximately 2.1MB, including a speech recognition library) const voiceModule = conditionalCompile('VOICE_INTERACTION') ? require('. / voice / speech-handler') null; / / During application initialization, whether to execute initialization logic depends on whether the module exists. async function initializeApp() { if (distributedModule) { await distributedModule.initialize({ signalingServer: '...'}); } if (assistantModule) { await assistantModule.initialize({ modelEndpoint: '...'}); } } ``` The conditional compilation helper function `conditionalCompile` is replaced with a constant value during the build phase. Therefore, the entire conditional expression becomes either `true ? require(...) : null` or `false ? require(...) : null` after the build. The former preserves the module reference, while the latter is completely removed during the dead code elimination phase.
[0057] V. Runtime Feature Check and Remote Configuration Runtime feature flags are controlled through a remote configuration service. At runtime, the system queries the configuration service for feature status and dynamically adjusts the code execution path based on the query results. The runtime feature manager is responsible for communicating with the remote configuration service, caching feature status, and notifying subscribers of status changes.
[0058] The implementation of runtime feature management includes the following key components: a remote configuration client responsible for establishing a connection with the configuration service and subscribing to feature state changes; a feature state cache used to store queried feature states, reducing the number of network requests; and a list of state change listeners to support multiple modules subscribing to the same feature's state change notifications. When a feature state changes in the remote configuration service, the remote configuration client receives the change notification, updates its local cache, and triggers all registered listener callback functions.
[0059] The following is a pseudocode example of runtime feature management: ```typescript / / Pseudocode: Runtime Feature Manager class RuntimeFeatureManager { private client: RemoteConfigClient; private flagCache: Map<string, boolean> = new Map(); async initialize() { await this.client.waitForInitialization(); / / Subscribe to runtime feature state changes for (const flag of ['new_model_suggestions', 'enhanced_context',...]) { this.client.on(`update:${flag}`, (value) => { this.flagCache.set(flag, value); this.notifyListeners(flag, value); }); } } isEnabled(flag: RuntimeFlag): boolean { / / Prioritize using the cache; if the cache is not found, query the remote service. if (this.flagCache.has(flag)) { return this.flagCache.get(flag); } const value = this.client.variation(flag, false); this.flagCache.set(flag, value); return value; } } ``` The application code uses both build-time and runtime checks to achieve complete functional control: build-time checks ensure that the relevant code exists, while runtime checks determine whether the function is enabled. For example, the implementation of the model recommendation function first checks whether the AI assistant module exists (build-time check), then checks whether the new model suggestion feature is enabled (runtime check), and only executes the recommendation logic if both conditions are met.
[0060] VI. Hierarchical Control of Command Registration The command system is the core interaction mechanism of DevStudio Enterprise, and it needs to support both build-time and runtime feature control. The command registration module divides commands into three categories: core commands are always present and available; build-time conditional commands are included depending on the build configuration; and runtime conditional commands are always present in the build artifacts, but their availability is determined by the runtime state.
[0061] The implementation logic for command registration is as follows: First, core commands (such as help, clear, cost, etc.) are collected. These commands do not depend on any feature flags. Then, feature-related commands are conditionally added based on the feature flags during the build process. For example, voice commands are only included when the VOICE_INTERACTION feature is enabled. Finally, runtime conditional commands are added. These commands carry the isEnabled callback function and are dynamically filtered based on the runtime state when the command list is displayed.
[0062] Here is a pseudocode example for command registration: ```typescript / / Pseudocode: Command Registration and Filtering function getAvailableCommands() { const commands = [ / / Core commands always exist { name: 'help', handler: showHelp}, { name: 'clear', handler: clearHistory}, / / Build-time conditional commands (become a static list after build) ...(conditionalCompile('VOICE_INTERACTION') ? voiceCommands :[]), ...(conditionalCompile('WORKFLOW_SUPPORT') ? workflowCommands :[]), / / Runtime conditional commands { name: 'experimental:ai-debug', handler: experimentalDebug, isEnabled: () => featureManager.isEnabled('experimental_features'), }, ]; / / Filter commands that are not available at runtime return commands.filter(cmd => !cmd.isEnabled || cmd.isEnabled()); } ``` VII. Load heavy-duty subsystems as needed To optimize startup performance, DevStudio Enterprise employs a dynamic module loading mechanism to delay the initialization of heavyweight subsystems, performing loading and initialization only on the first access. These delayed-loaded subsystems include an observability monitoring framework (approximately 15MB, including the OpenTelemetry SDK), a remote procedure call framework (approximately 8MB, including the gRPC client), a data analysis framework (approximately 12MB, including the data processing engine), and a feature management service (approximately 5MB, including the configuration synchronization client).
[0063] The on-demand loading implementation uses a lazy initialization pattern: a dynamic import statement is triggered when a subsystem is accessed for the first time. After loading is complete, initialization logic is executed and the instance is cached. Subsequent accesses directly use the already initialized instance. Dynamic import statements are converted into code split points during the build process, and related modules are packaged into independent chunk files, which are loaded only when needed via the network or file system.
[0064] The following is a pseudocode example of on-demand loading of observability services: ```typescript / / Pseudocode: On-demand loading of observability services let traceProvider = null; async function initObservability() { if (traceProvider) return; / / If already initialized, return directly. / / Dynamically load heavy dependencies (approximately 15MB) const [{ NodeTracerProvider}, { OTLPTraceExporter}] = awaitPromise.all([ import('@opentelemetry / sdk-trace-node'), import('@opentelemetry / exporter-trace-otlp-http'), ]); traceProvider = new NodeTracerProvider({ exporter: new OTLPTraceExporter({ url: process.env.OTEL_ENDPOINT}), }); traceProvider.register(); } async function traceOperation(name, operation) { if (!traceProvider) { await initObservability(); / / Initialize as needed } return traceProvider.getTracer('app').startActiveSpan(name,operation); } ``` 8. Code Elimination Verification The code elimination verification module ensures that code with inactive features has been completely removed from the build artifacts, preventing sensitive code leaks or security risks. Verification employs two methods: static analysis scans the build artifacts after completion to detect any code patterns that should be eliminated but are actually present; runtime reflection dynamically checks the existence of modules and functions in the test environment.
[0065] The static analysis is implemented as follows: for each build-time feature flag, a set of code patterns that should be eliminated (such as module paths, function names, class names, etc.) are defined, and then these patterns are searched in the build artifacts. If a feature is disabled but its code pattern still exists in the build artifacts, a verification failure is reported and detailed residual code information is output.
[0066] Here is a pseudocode example of code elimination verification: ```typescript / / Pseudocode: Code Elimination Verification function verifyCodeElimination(flags) { const binaryContent = readFileSync('. / dist / main.js', 'utf-8'); const errors = []; / / Define the code patterns that should be eliminated const moduleChecks = [ { flag: 'VOICE_INTERACTION', patterns: [ / voice\ / speech-handler / , / SpeechRecognition / ], }, { flag: 'DISTRIBUTED_MODE', patterns: [ / distributed\ / collaboration / , / RTCPeerConnection / ], }, ]; for (const check of moduleChecks) { const isEnabled = flags[check.flag]; for (const pattern of check.patterns) { const found = pattern.test(binaryContent); if (!isEnabled && found) { errors.push(`The feature ${check.flag} is disabled but the code still exists`); } } } return { valid: errors.length === 0, errors}; } ``` The verification results generate a detailed report, including the size of the build artifacts, the status of each feature flag, a list of eliminated modules, a list of residual modules, and error details, making it easier for developers to quickly locate problems.
[0067] IX. Automatic Generation of Feature Documentation The feature documentation generation module automatically generates configuration documentation based on the definition metadata of feature tags, ensuring that the documentation is consistent with the actual configuration. The documentation content includes feature descriptions, current status, dependencies, conflict relationships, code size impact, and version information.
[0068] The documentation generation workflow is as follows: First, metadata is extracted from the feature flag definition file and build configuration. Then, it is categorized and organized according to feature type (build-time or runtime). Finally, Markdown or HTML format documents are generated according to predefined templates. The generated documents include feature status tables, dependency diagrams, and build artifact information summaries, providing a reference for team collaboration and operations management.
[0069] 10. Build Examples for Different Versions DevStudio Enterprise offers differentiated versions for various customer scenarios, each enabling different combinations of feature flags. The Community Edition only enables basic AI assistant functionality and external integration capabilities, with a build footprint of approximately 8.5MB; the Professional Edition adds advanced features such as voice interaction, workflow support, and system monitoring, with a build footprint of approximately 14.2MB; and the Enterprise Edition enables distributed collaboration mode and all advanced features, with a build footprint of approximately 18.7MB. The startup times for each version are 120ms, 180ms, and 250ms, respectively, with memory usage of 35MB, 58MB, and 85MB, respectively, catering to the diverse performance and functional needs of different customers.
[0070] Specific Implementation Example 2: Conditional Compilation and Feature Management System of Multi-Cloud Management Platform CLI.
[0071] This embodiment uses another example developed by the applicant, the "CloudCLI Pro" multi-cloud management platform command-line tool, to illustrate in detail the application of this invention in the field of DevOps tools. CloudCLI Pro is a multi-cloud resource management tool for enterprise operations and maintenance teams, supporting mainstream cloud platforms such as AWS, Azure, GCP, Alibaba Cloud, and Tencent Cloud. It requires the construction of lightweight, customized versions based on the cloud environment, compliance requirements, and functional needs of different enterprises, while ensuring that the startup speed of the CLI tool meets the real-time requirements of the operations and maintenance scenario.
[0072] I. System Requirements and Characteristic Design The core challenges faced by CloudCLI Pro include: enterprise customers may only use some cloud platforms and do not need to include SDKs for all cloud platforms; support for offline environments such as private clouds or air-gap networks is required, as configuration cannot be obtained by relying on runtime networks; different customers have different compliance requirements, and some customers prohibit automatic deletion operations or batch operations; CLI tools require extremely fast startup speeds, with a target startup time of less than 300 milliseconds; and support for dynamic function switches is required to disable certain commands with security risks in an emergency.
[0073] Based on the architecture of this invention, CloudCLI Pro designs three sets of feature flags: cloud platform support flags (AWS_SUPPORT, AZURE_SUPPORT, GCP_SUPPORT, ALIYUN_SUPPORT, TENCENT_SUPPORT) control whether each cloud platform SDK is included; resource type support flags (COMPUTE_SUPPORT, STORAGE_SUPPORT, NETWORK_SUPPORT, DATABASE_SUPPORT, KUBERNETES_SUPPORT, SERVERLESS_SUPPORT) control whether each resource type management module is included; functional feature flags (AUTO_SYNC, COST_ANALYSIS, SECURITY_SCAN, BACKUP_MANAGEMENT, MONITORING_INTEGRATION) control the enabling status of advanced functions; and dangerous operation flags (DELETE_OPERATIONS, BULK_OPERATIONS, FORCE_OPERATIONS) control whether high-risk operations are included, meeting the compliance requirements of different customers.
[0074] II. Conditional Import of Cloud Platform Modules The core design philosophy of CloudCLI Pro is that each cloud platform is treated as an independent module, and is only included in the build artifact when the corresponding feature flag is enabled. The cloud platform SDKs are relatively large (AWS SDK approximately 45MB, Azure SDK approximately 38MB, GCP SDK approximately 32MB, Alibaba Cloud SDK approximately 18MB, Tencent Cloud SDK approximately 15MB), and the conditional import mechanism can significantly reduce the size of the build artifact.
[0075] The conditional import of cloud platform modules employs a combination of build-time constant replacement and dynamic require: First, a conditional compilation helper function determines the status of feature flags; then, based on the result, it decides whether to execute a require statement to load the corresponding module; finally, the successfully loaded module is registered in the cloud platform registry for subsequent calls. During the build phase, conditional branches that disable the cloud platform are completely eliminated, and the corresponding require statements and their dependent SDK modules are not packaged.
[0076] The following is a pseudocode example of conditional import of cloud platform modules: ```typescript / / Pseudocode: Conditional import of cloud platform modules const awsModule = conditionalCompile('AWS_SUPPORT') require('. / providers / aws') null; const azureModule = conditionalCompile('AZURE_SUPPORT') ? require('. / providers / azure') null; / / ... Other cloud platform modules / / Build a cloud platform registry that only includes enabled platforms. export const cloudProviders = { ...(awsModule && { aws: awsModule}), ...(azureModule && { azure: azureModule}), / / ... Other platforms }; function getSupportedProviders() { return Object.keys(cloudProviders); } ``` III. Conditional Import of Resource Type Module In addition to the cloud platform, the resource type management module also adopts a conditional compilation mechanism, allowing customers to select the included resource types according to their actual needs. The resource type module includes compute resource management (EC2 / VM / ECS), storage resource management (S3 / Blob / GCS), network resource management (VPC / Subnet / Security Group), database resource management (RDS / CloudSQL), Kubernetes cluster management (EKS / AKS / GKE), and serverless resource management (Lambda / Functions), etc.
[0077] The conditional import mechanism in the resource type module is similar to that in the cloud platform module, but it adds a layer of control logic for dangerous operations. When the DELETE_OPERATIONS feature flag is disabled, deletion commands (such as terminate and delete) in the resource management module will be excluded from the command list, ensuring that compliance-sensitive customers cannot perform deletion operations.
[0078] The following is a pseudocode example of resource type command aggregation: ```typescript / / Pseudocode: Resource type command aggregation function getResourceCommands() { const commands = []; if (computeModule) { commands.push( { name: 'compute list', handler: computeModule.listInstances}, { name: 'compute start', handler: computeModule.startInstance}, / / The delete command is only included when DELETE_OPERATIONS is enabled. ...(conditionalCompile('DELETE_OPERATIONS') ? [ { name: 'compute terminate', handler:computeModule.terminateInstance}, ] : []), ); } / / ... Other resource types return commands; } ``` IV. Configuration and Product Optimization CloudCLI Pro's build system predefines multiple build variants for different customer scenarios, each corresponding to a set of feature flag configurations. The main build variants include: the aws-only variant, which enables only AWS platform support, with a build artifact of approximately 11.8MB and a startup time of approximately 180ms, suitable for enterprise customers in pure AWS environments; the china-clouds variant, which enables support for Alibaba Cloud and Tencent Cloud, with a build artifact of approximately 7.9MB and a startup time of approximately 150ms, suitable for domestic cloud environments and disables delete operations to meet compliance requirements; the readonly variant, which enables AWS, Azure, and GCP (the three major international cloud platforms) but disables all write operations, with a build artifact of approximately 14.5MB and a startup time of approximately 220ms, suitable for auditing scenarios; and the full variant, which enables all cloud platforms and all functions, with a build artifact of approximately 46.2MB and a startup time of approximately 380ms, suitable for management scenarios requiring full functionality.
[0079] The build configuration implementation process is as follows: First, load the corresponding feature flag configuration according to the build variant name, then verify the legality of the configuration, then generate constant definitions and pass them to the module packaging tool, and finally execute the build and output the artifact size statistics.
[0080] V. Runtime Feature Control CloudCLI Pro's runtime feature controls are primarily used to implement dynamic security policies, including the default dry-run mode, audit logging, rate limiting, and command timeout control. Runtime configurations are obtained from a remote configuration service, allowing adjustments to security policies without redeploying the tool.
[0081] The runtime feature manager initializes when the CLI starts, pulling the current configuration from the remote configuration service and caching it locally, while also subscribing to configuration change notifications. The command execution wrapper checks the runtime configuration before executing each command, determining whether to enable dry-run mode, log audits, apply rate limits, etc., based on the configuration. When the remote configuration service is unavailable, the runtime feature manager uses the locally cached configuration or the default configuration to ensure the CLI functions correctly in offline environments.
[0082] The following is a pseudocode example of a runtime command execution wrapper: ```typescript / / Pseudocode: Runtime command execution wrapper async function executeCommand(commandName, operation) { / / Check if dry-run mode is enabled by default if (runtimeConfig.isDryRunDefault && !commandName.startsWith('list')) { console.log(`[DRY-RUN] command will be executed in dry-run mode, and actual changes will be skipped`); return { dryRun: true}; } / / Record audit logs if (runtimeConfig.isAuditLoggingEnabled) { await logAuditEvent({ command: commandName, timestamp: new Date().toISOString(), user: process.env.USER, }); } / / Execute command (with timeout control) const timeout = runtimeConfig.commandTimeout; return Promise.race([ operation(), new Promise((_, reject) => setTimeout(() => reject(new Error('Command timeout')), timeout) ), ]); } ```.
[0083] VI. Code Elimination Verification Report CloudCLI Pro implements a detailed code removal verification mechanism to ensure that disabled cloud platform SDKs and related code are completely removed from the build artifacts. The verification process defines a set of characteristic code patterns for each cloud platform, including SDK package names, core class names, API client names, etc., and then searches for these patterns in the build artifacts to determine if there is any code that should be removed but is actually left behind.
[0084] The verification report includes the artifact size for each build variant, a list of enabled cloud platforms, a list of disabled cloud platforms, a list of eliminated SDK modes, a list of residual SDK modes, and details of verification errors. Through the verification report, developers can quickly identify issues with incomplete code elimination, and operations personnel can confirm that the build artifacts meet the expected configuration.
[0085] VII. Actual Performance The performance of CloudCLI Pro in a real-world production environment validates the effectiveness of the architecture of this invention. Through conditional compilation, the AWS-only variant reduces the artifact size by 74% (11.8MB vs 46.2MB), startup time by 53% (180ms vs 380ms), and memory usage by 65% (45MB vs 128MB) compared to the full variant. The China-Clouds variant, while meeting compliance requirements (disabling deletion operations), achieves the smallest artifact size (7.9MB) and the fastest startup speed (150ms), satisfying the dual needs of domestic enterprise customers for lightweight design and compliance.
[0086] Through the hierarchical feature control architecture of this invention, CloudCLI Pro successfully solves the technical challenges faced by multi-cloud management tools, such as large SDK size, slow startup speed, diverse compliance requirements, and offline environment support, providing customized, high-performance, compliant and secure CLI tool versions for different types of customers.< / string>
Claims
1. A conditional compilation and dynamic feature management system, characterized in that, It includes a build-time conditional import module, configured to selectively import modules using a conditional expression pattern. The conditional expression is evaluated during the build phase, and the module packaging tool completely removes module dependencies corresponding to inactive code branches during the build process. The build-time conditional import module uses the conditional compilation interface functions provided by the module packaging tool.
2. The system according to claim 1, characterized in that, It also includes a runtime feature checking module and a hierarchical feature control module. The hierarchical feature control module is configured to distinguish between build-time feature control and runtime feature control. Build-time feature control is implemented through build-stage conditional expressions, where inactive code is completely removed from the build artifacts, and the entire module tree is removed from the build artifacts when a feature is inactive. Runtime feature control is implemented through runtime status query callbacks. The code exists in the build artifacts, but its execution path is controlled by the runtime status, and it is re-evaluated each time a command is retrieved through the status query callbacks. The runtime feature checking module is configured to query the real-time status of feature flags through a remote configuration service during the program execution phase, and dynamically control the execution path of the compiled code.
3. The system according to claim 1, characterized in that, It also includes an on-demand loading module, configured to use a dynamic module loading mechanism to delay the initialization of heavy subsystems, performing loading and initialization only on the first access; the on-demand loading module delays the loading of the observability monitoring framework, remote procedure call framework, data analysis framework, and feature management service.
4. The system according to claim 1, characterized in that, It also includes a code elimination verification module, configured to verify whether the corresponding code of inactive features has been completely eliminated from the final build artifact, and to detect residual code and generate a verification report through runtime reflection or static analysis.
5. The system according to claim 1, characterized in that, It also includes a feature dependency management module, configured to manage the dependencies and mutual exclusions between feature flags, including pre-dependency checks and conflict detection, verifying the legality of configurations and reporting violations during the build phase; the feature dependency management module verifies the dependencies and conflicts of feature flags, reports errors during the build process, and prevents illegal configurations from entering the build process.
6. The system according to claim 1, characterized in that, It also includes a feature document generation module, which is configured to automatically generate feature configuration documents based on the definition metadata of feature flags. The documents contain feature descriptions, current status, dependencies, and information on the impact of code size.
7. The system according to claim 1, characterized in that, It also includes a feature flag definition module and a build configuration module; the feature flag definition module is configured to centrally define all feature flags to ensure type safety and configuration consistency; the build configuration module is configured to set the feature flag status according to environment variables and pass it to the module packaging tool.
8. The system according to claim 1, characterized in that, The features include: distributed collaboration mode, intelligent assistant mode, automated triggering mechanism, remote connection capability, voice interaction capability, external system integration mode, workflow script support, context compression optimization, proactive service mode, system monitoring capability, background service mode, and direct connection mode.
9. The system according to claim 1, characterized in that, The build-time conditional import module supports three modes: conditional import statements, conditional export statements, and conditional require calls; the conditional expressions support three evaluation sources: Boolean constants, environment variable references, and attribute flag references; the code branch elimination in the build artifact adopts a two-stage strategy combining static replacement and dead code elimination.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the functions of the conditional compilation and dynamic feature management system as described in any one of claims 1 to 9.