SDD
SDD is an acronym with multiple meanings in various fields. == Computing == == Business and Finance == == Science and Medicine ==Computing
Software Design Description
The Software Design Description (SDD) is a standardized data item description (DID) in software engineering, specifically DI-IPSC-81435 under MIL-STD-498, used to detail the design of a Computer Software Configuration Item (CSCI). It provides a comprehensive representation of the software's architecture, components, and implementation rationale, serving as a bridge between requirements and code.[1] The SDD ensures that design decisions are documented systematically, enabling developers, acquirers, and maintainers to understand the system's structure without ambiguity.[2] Key elements of the SDD include the software architecture, which outlines the high-level components (software units) and their static and dynamic relationships, along with resource utilization and execution concepts. Data design covers database structures, data files, and local data elements, ensuring consistency across the CSCI. Interface design specifies interactions among software units, hardware, users, and external systems, detailing data elements, formats, and communication protocols. Detailed design decisions address individual software units, including processing logic, algorithms, and programming language choices, often with pseudocode or flowcharts for clarity.[1] These elements are organized into sections such as CSCI-wide design decisions (e.g., safety, security, and flexibility), architectural design, detailed design, and requirements traceability to link elements back to specified needs.[3] Historically, the SDD emerged as part of MIL-STD-498, a U.S. Department of Defense standard released in 1994 to harmonize software development and documentation practices, superseding earlier DIDs like DI-MCCR-80012A.[4] This standard referenced IEEE Std 1016 as a guide for SDD content. Following the cancellation of MIL-STD-498 in 1998, the SDD evolved through IEEE 1016-2009, which formalized the information content and organization for SDDs across commercial, scientific, and military applications, emphasizing stakeholder communication without mandating specific tools or languages.[5][6] The purpose of the SDD is to facilitate verification and validation by providing a verifiable basis for testing, support maintenance through clear design rationale, and enable acquirer oversight during development.[1] It relates to the broader Software Design Document as a similar but more standardized format focused on CSCI-level details in engineering contexts.[5]Software Design Document
A Software Design Document (SDD) is a comprehensive artifact in the software development lifecycle that serves as a blueprint for how a software system will meet user requirements, detailing the architecture, modules, algorithms, interfaces, and data flows necessary for implementation.[7] It bridges the gap between high-level requirements and detailed coding by providing a structured representation of the design decisions, ensuring traceability, maintainability, and communication among stakeholders such as developers, testers, and project managers.[8] In formal engineering contexts, the SDD overlaps with the Software Design Description, particularly under standards like IEEE 1016, but emphasizes broader applicability across methodologies.[7] Standard components of an SDD typically include an introduction outlining the purpose, scope, and references; a system overview describing the overall architecture and context; design concepts explaining high-level approaches and trade-offs; detailed module descriptions covering specific components, interfaces, algorithms, and data structures; and appendices with supporting diagrams, such as entity-relationship models or flowcharts, to visualize the design.[8] These elements ensure the document addresses stakeholder concerns through multiple design views (e.g., logical, interface, and interaction views) and includes rationale for key decisions to support future maintenance and evolution.[7] Industry standards like ISO/IEC/IEEE 12207 reference such structures in their software detailed design process, recommending the use of IEEE 1016 for organizing content to achieve verifiable designs aligned with requirements.[9] Best practices for creating an SDD emphasize completeness, consistency, and traceability, with the use of standardized design languages and viewpoints to avoid conflicts across views and ensure all requirements are addressed.[8] In waterfall methodologies, the SDD is developed upfront as a comprehensive deliverable during the design phase to guide sequential implementation, whereas in agile methodologies, it is maintained iteratively as a living document, focusing on just-in-time detailing for sprints to balance documentation with rapid delivery.[10] ISO/IEC/IEEE 12207 supports these adaptations by providing a flexible framework for design processes that can be tailored to sequential or iterative life cycles, promoting evaluation of design feasibility and integration with implementation activities.[11]Syntax-Directed Definition
A syntax-directed definition (SDD) is a context-free grammar extended with attributes attached to its symbols and semantic rules associated with its productions, enabling the specification of program semantics through computations along the parse tree. This formalism supports syntax-directed translation, where attributes capture semantic information derived from the syntactic structure during parsing. Introduced as part of attribute grammars, SDDs allow for modular description of translation tasks in compilers without prescribing a specific evaluation order.[12] Central to SDDs are two types of attributes: synthesized and inherited. Synthesized attributes are computed bottom-up, depending on the attributes of a production's right-hand-side symbols and flowing upward to the left-hand-side symbol in the parse tree; for instance, the value of an expression node can be derived from its operands. Inherited attributes, in contrast, are passed top-down from a parent or sibling nodes to the right-hand-side symbols, facilitating context-dependent computations such as scope resolution or type propagation. These attributes collectively form an attribute grammar, where rules ensure dependencies are resolved correctly to avoid circularity.[13] A representative example involves type checking in a simple arithmetic expression parser. Consider the grammar productions for expressions E (expression), T (term), and F (factor), with attributes like .type for the inferred type (e.g., int or float). For E → E₁ + T, the rule E.type ← if E₁.type = float or T.type = float then float else int synthesizes the type bottom-up, ensuring compatibility; if mismatched, an error is flagged. Similarly, for T → F, T.type ← F.type propagates the type, while inherited attributes might pass expected types downward in more complex declarations. This setup computes types across the parse tree, detecting incompatibilities like adding an integer to a string.[13] SDDs find primary application in compiler phases beyond parsing, particularly code generation and error detection. In code generation, semantic rules attached to productions produce intermediate representations, such as three-address code for expressions via synthesized attributes like .code (e.g., E.code ← E₁.code || T.code || 'temp = E₁.place + T.place'). For error detection, attribute computations enforce semantic rules, such as type consistency or variable declaration checks, halting compilation on violations and providing diagnostic feedback. These uses leverage the parse tree's structure for efficient, declarative specification of compiler actions.[14]Sentential Decision Diagram
A Sentential Decision Diagram (SDD) is a directed acyclic graph (DAG) that provides a canonical and tractable representation of Boolean functions, generalizing the structure of binary decision diagrams (BDDs) to handle sentential logic through recursive decompositions.[15] Unlike BDDs, which are limited to variable decisions, SDDs incorporate logical operators and partitions, enabling a broader class of representations while preserving efficiency in operations like conjunction and disjunction.[15] This structure is defined with respect to a variable tree (vtree), which partitions variables into contiguous subsets, ensuring decomposability.[16] In terms of construction, SDD nodes consist of decision nodes (typically depicted as circles) that select a variable from the current vtree node, paired with elements comprising prime and sub sub-diagrams in rectangular boxes.[15] Edges connect these elements, representing true/false evaluations that recursively traverse to child vtree nodes, with terminal nodes holding constants (true/false) or literals.[16] The diagram is built via (X, Y)-decompositions, where X and Y are disjoint variable sets from the vtree, and elements form partitions that are both exhaustive and mutually exclusive.[15] Compared to truth tables, which enumerate all 2^n assignments for n variables and thus scale exponentially in space, SDDs offer substantial savings by exploiting functional structure and sharing sub-diagrams across the DAG.[17] For instance, complex formulas like the n-bit inner product require only O(n^2) nodes in an SDD, versus exponential size in truth tables or even some BDD variants.[17] This succinctness is achieved through compression rules that normalize redundant elements and trimming to eliminate false sub-diagrams.[16] Algorithms for building SDDs include top-down compilation from conjunctive normal form (CNF) using SAT solver techniques like unit propagation and clause learning, with caching to reuse components across recursions.[15] Bottom-up construction applies conjunction or disjunction operations to terminal SDDs, respecting the vtree for decomposability.[16] Querying employs the Apply algorithm, which performs Boolean operations in time proportional to the product of input sizes, leveraging unique decomposition rules to ensure disjoint primes and distinct subs for canonicity.[15] These rules—requiring partitions to cover all possibilities without overlap—underpin the efficiency and uniqueness of SDDs.[16] SDDs find application in automated reasoning tools for tasks like probabilistic inference.[15]Solution Deployment Descriptor
The Solution Deployment Descriptor (SDD) is an XML-based standard developed by the OASIS Solution Deployment Descriptor Technical Committee for describing and managing the deployment of composable software solutions in enterprise environments, including application servers like IBM WebSphere.[18] In the context of IBM WebSphere, the SDD specifies deployment targets, resources, and bindings for J2EE applications, enabling the definition of installable units (IUs) such as enterprise applications, modules, and supporting artifacts like databases.[19] This allows administrators to model complex, multi-component solutions that can be deployed across heterogeneous platforms, ensuring consistency in configuration and lifecycle management. The structure of an SDD document follows a standardized XML schema that organizes information into key elements for precise automation. The<deployments> element defines the hierarchy of IUs, including attributes for module types (e.g., EAR files for J2EE apps) and server targets within WebSphere cells or nodes. The <resources> element details software artifacts, dependencies, and content requirements, such as JNDI resources or connection factories needed for application runtime.[18] Complementing these, the <bindings> element specifies mappings and configurations, including attributes for resolving references to external services or servers, like binding a J2EE resource reference to a specific WebSphere resource provider. This schema-based approach ensures interoperability and extensibility, with namespaces for custom extensions in enterprise-specific profiles.
In deployment processes, SDD files are parsed by tools such as WebSphere's administrative console or scripting utilities (e.g., wsadmin) to automate installation, configuration, and updates of J2EE applications across clusters.[20] For instance, a deployment tool reads the SDD to map bindings to actual server resources, install modules to targeted nodes, and validate dependencies before activation, reducing manual errors in large-scale environments.[19] This parsing supports scripted or GUI-driven workflows, integrating with provisioning systems for repeatable deployments.
The SDD evolved from earlier J2EE descriptors like application.xml, which focused on basic module packaging under the Java EE specification, by extending to a broader, platform-agnostic model for composite solutions. Approved as an OASIS Standard in 2008, version 1.0 introduced comprehensive lifecycle support, building on submissions from vendors including IBM to address gaps in deploying integrated enterprise stacks.[18]