Getting the Payoff With MDD. Proven Steps to Get Your Return on Investment

Transcription

1 Getting the Payoff With MDD Proven Steps to Get Your Return on Investment version 1.4 6/18/11 Generate Results: Real Models, Real Code, Real Fast.

2 Welcome Systems development organizations are under increasing pressure to improve business results Develop products in less time With more capabilities and better run-time performance With concept-to-code fidelity and higher product quality In a predictable, repeatable manner Key development practices deliver significant business gains when applied with the right focus Agile Model-Driven Test-Driven This session outlines what it takes to maximize these results. Getting the Payoff With MDD 2

3 Real Gains - outline Why PI-MDD? PI-MDD Methodology Doing it For Real Getting the Payoff With MDD 3

4 Challenges in Systems Development Building complex, high-performance systems is difficult Escalating feature complexity Challenging system execution requirements Reliability, availability Speed, space, environment Aggressive competition Diverse, unique platforms Getting the Payoff With MDD 4

5 Realities of Code-Driven Development Traditional code-focused development approaches Architecture with implementation focus Primary communication through code Waterfall processes All software maintained at implementation-level Single concept space Mix of problem space and implementation detail Hard to effectively decompose Integration and test are hard and expensive Done as little as possible, at the end Getting the Payoff With MDD 5

6 Realities of Code-Driven Development Can Model Driven Development help? Not all MDD approaches and technologies are effective Code-focused UML models often introduce even more complexity Abstraction level quickly drops to code level Models laden with code-level details are difficult to maintain Code-focused models hardwire threading and processor configurations, and other key platform details Achieving runtime performance gets increasingly elusive through the product s lifecycle UML itself does not address process/method level issues Getting the Payoff With MDD 6

7 Problem-Space Focused MDD An agile, problem-space focused MDD approach with frequent test cycles is effective for developing highcomplexity, high-performance systems: Facilitate an architectural focus throughout system lifecycle Manage overall system complexity with separation Attack biggest risks early and often Automated transformation of models to deliverable product Platform-Independent Model Driven Development (PI-MDD) embodies this focus Getting the Payoff With MDD 7

8 Platform Independent MDD When executed properly, the Platform-Independent MDD approach brings compelling benefits Models are Platform Independent and readily re-deployable Readily change task/processor topology Change infrastructure and implementation strategies without affecting models Builds a product-line architecture and platform Flexible generation technology supports automatically applied custom optimizations, for high run-time performance Models stay at problem space level with no abstraction erosion Simple models, high resulting system quality Productivity much higher than other MDD approaches Getting the Payoff With MDD 8

9 Platform Independent MDD The PI-MDD method brings consistency and best-practice: A well defined process, populated with consistent step-by-step techniques Effective tooling facilitates substantial automation Model checking Code generation Document generation, data interchange Integrated with and reinforces sound engineering practice Development steps elevate visibility and manageability Review activities integrated and effective Strong focus on business results at all practice points Establishes a natural architectural base for Product Lines, with sweeping component reuse Training, industry commonality and standards base promote Consistent techniques, shared experiences Wealth of outside experience and resources Rich tool offerings and extensible environments Getting the Payoff With MDD 9

10 Platform Independent MDD Code generation from UML models with implementation-language actions is limited by action-blindness Unknown action behavior requires generation of all possible support infrastructure, accessors, etc. The actions themselves are not generated, they are just copied through, and cannot be optimized Code generation from PI-MDD models with platform independent actions provides action-visibility to the code generation PI-MDD action-visibility facilitates Self-Optimization 3X smaller code* 7X faster code* * Comparison of code generated from PI-MDD and code-focused MDD for performance-critical implementation constructs. Getting the Payoff With MDD 10

11 Real Gains - outline Why PI-MDD? PI-MDD Methodology Requirements and Systems Engineering Logical Architecture Tight develop/test iterations Platform Independent Modeling Generating High Performance Implementation Doing it For Real Getting the Payoff With MDD 11

12 Comparison with other MDD Forms Some aspects of PI-MDD modeling are very similar to more general MDD modeling Use Case Logical Component System-Level Scenario Component-Level Scenarios Other aspects of PI-MDD have a unique Platform Independent emphasis Classes State machines Actions Dynamic Verification Getting the Payoff With MDD 12

13 Logical Architecture - Domains Logical Architecture is a hierarchy of Domain Packages and Dependencies: Getting the Payoff With MDD 13

14 Logical Architecture - Domains PI-MDD Domain Modeling produces your system s Logical Architecture Each Logical Component is a Domain, a separate, conceptual universe Pertaining to a distinct subject matter Interacts with other components exclusively through published services Getting the Payoff With MDD 14

15 Logical Architecture Domains Logical Component focus naturally builds a foundation for Product Line development Component-level reuse multiplied by Platform Independence yield game-changing agility and asset longevity Getting the Payoff With MDD 15

16 Logical Architecture System Scenarios System Scenario Models show the allocation of behavioral responsibility among domains: Getting the Payoff With MDD 16

17 Logical Architecture System Scenarios System Scenario Models form the basis of Sprint definition a Story: Getting the Payoff With MDD 17

18 PIM - Classes PI-MDD Class Model shows a Platform Independent Model for a domain: Attributes use PIM atomic data types Associations gain prominence in a PIM Data structure details are exposed in associations Implementation details are separated from PIM-level classes they are woven in at code generation time Getting the Payoff With MDD 18

19 PIM - Classes Platform Independent Class Model Getting the Payoff With MDD 19

20 PIM State Machines State Models Simplified execution mechanics for broader use «State» Verifying //# If there are x number of track observations of y quality or better in a row,... CANCEL Entity:Timeout; Degraded Observed Confirmed/reportable = TRUE; Timeout «State» Tracking //# If the quality of the last x TrackObservations is below y... CANCEL Entity:Timeout; Timeout Observed «State» Disappearing //# delete all track observations associated with this entity... Getting the Payoff With MDD 20

21 PIM - Actions The final element making an PI-MDD PIM platform independent: Platform Independent Action Language (PAL) Defines model-level processing Performed by an operation or state action PAL solves a number of difficult issues with code in models: Simple, easy to learn Conforms to OMG standard UML Action Semantics PIM-level, not implementation code Convenient and complete set of modeling processing primitives Enables automated transformation to optimized implementations Getting the Payoff With MDD 21

22 PIM - Actions Each domain interface operation, class operation, and state/transition action is defined by PAL: Getting the Payoff With MDD 22

23 PIM - Dynamic Verification Dynamic Verification Execution of PI-MDD models to verify behavior Independent of target execution environment Within the context of a single domain, or a tightly related set of domains Test cases are derived from Scenario Models DV is distinct from subsequent integration phases: Software Integration Hardware Integration The platform-independence of the models facilitate a broad range of test platforms and configurations Getting the Payoff With MDD 23

24 PI-MDD PIM Virtual Machine UML2 defines core execution semantics Class instance creation, deletion, linkage Signal generation, reception State machine mechanics PAL statements, expressions Many different implementations can support PI-MDD PIM execution Simple workstation-based functional test program Fully optimized, multi-processor, multi-task embedded product deployment Transformation generates the appropriate implementation Getting the Payoff With MDD 24

25 Transformation Rule/Template Transformation Rule/Template Navigates model elements Creates output files Controls transformation of models to any form code doc (rtf) html csv xml Any text Getting the Payoff With MDD 25

26 Transformation Rule/Template Rules/Templates control the Transformation Engine Getting the Payoff With MDD 26

27 Component Deployment UML Deployment reflects the Physical System Architecture Nodes represent execution units Communication paths connect nodes Use multiple diagrams for multiple configurations Capture topology/deployment in markings Getting the Payoff With MDD 27

28 Transformation Markings Additional information may be needed to guide transformation Platform specific Project specific PIM markings are used to supplement PIM information Getting the Payoff With MDD 28

29 Transformation Markings Markings specify topology: task, processor, routing, etc: Getting the Payoff With MDD 29

30 Transformation Markings Markings can help with other platform-specific information Optimization decisions Realized code integration Project file generation Getting the Payoff With MDD 30

31 Transformation Markings Markings drive Transformation through Rule references: Getting the Payoff With MDD 31

32 PI-MDD Methodology Summary The PI-MDD methodology for developing high performance Systems Delivers results through Simplicity derived from Separation Agile development cycles attack key risks early and often Key automation and platform independence of models facilitate test Components can be modeled (platform independent), or code-sourced PI-MDD platform independent components are Complete, and tested via model-level execution Generated to optimized implementation code Getting the Payoff With MDD 32

33 Real Gains - outline Why PI-MDD? PI-MDD Methodology Doing it For Real Real Systems Real People Getting the Payoff With MDD 33

34 Real Systems Pathfinder s exclusive focus is transforming organizations to apply this approach for complex, high performance systems In this arena there are a host of challenges that complicate MDD methodology deployment: Existing/imposed overarching architecture Large portions of Legacy code and other hand coded components Custom hardware, fancy algorithms, and other nasty bits Performance concerns Getting the Payoff With MDD 34

35 Real Systems Imposed Overall Architecture You may be building only a portion of the overall system Some components and interfaces are fixed Logical Architecture builds the essential adaptation framework Build a logical architecture within the subsystem to be developed with PI-MDD Manifest domains for each unique external interface Proper problem-space focus is an essential technique to organize and build interfaces to complex, pre-existing systems Getting the Payoff With MDD 35

36 Real Systems Nearly all PI-MDD systems in the real world encompass large legacy code bodies or other non-pi-mdd components Logical Components are abstracted for all elements providing a uniform interface paradigm Build a proper logical architecture with a problem space focus, for old and new components alike Map legacy component capabilities to one or more domains Connect the underlying code capabilities to the domain interfaces using a wrapper or Façade pattern for these elements Be sure to select PI-MDD tooling with demonstrated strengths in this area Getting the Payoff With MDD 36

37 Real Systems Our high performance systems do lots of neat things Interface with custom hardware Implement signal processing and other complicated algorithms High volume data transfers throughout a distributed topology All with high performance and reliability Even with great code generation technology, some of this is still done via handwritten code Create domains to provide these code-focused capabilities Connect the underlying code capabilities to the domain interfaces for these elements Sometimes, project-specific code patterns are needed Use tooling that easily supports custom code generation transformations Getting the Payoff With MDD 37

38 Real Systems Performance Concerns Our systems need to run fast! Aren t higher levels of abstraction slower? Don t we need to carefully and lovingly craft all implementation code by hand? Coding actions with implementation code imposes critical limitations: They do not directly support manipulation of UML primitives Typically handwritten code builds dependencies on deployment topology and other transient details Implementation strategies/patterns are hard coded and cannot be optimized after coding starts Not every C/C++ programmer writes fast and safe code Getting the Payoff With MDD 38

39 Real Systems Platform-independent Action Language directly addresses these issues Simple, extensible Eliminates unsafe constructs Platform independent: Portability to new target environments Deployable to any topology without change Action visibility facilitates Self Optimized target code generation Rules-based code generation is extended with project-specific optimizations Getting the Payoff With MDD 39

40 Real People Larger teams have developers with average level of capability and motivation A well-documented methodology helps keep everyone on track Effective tools provide methodology automation Automatic governance, enforcement Reduces opportunity for human error But culture change is difficult, and people need help Keep a clear focus on core business requirements driving change Use training and mentoring to move the transition quickly and reduce frustration Getting the Payoff With MDD 40

41 Real People Leadership challenges: Articulate goals Measure results Finding the right blend use PI-MDD as a framework to bind together heterogeneous components Getting the Payoff With MDD 41

42 Real People Articulate goals Why is MDD being applied? Agile? TDD? What business results are expected Productivity Manageability Reuse What technical results are expected Quality Performance Architectural flexibility Getting the Payoff With MDD 42

43 Real People Measure results Everyone needs to know how well it is working Management Individual engineers External stakeholders Compare results to expectations Use objective data to Identify where things are working, where they are not Improve the application of the approach, technology Actively manage the process Getting the Payoff With MDD 43

44 Summary Business drivers require quantum leaps forward in agility, productivity, quality and manageability Change is difficult, but large magnitude gains do not come from casual, incremental changes to status quo An agile, problem-space focused MDD approach can form the basis for meeting these requirements Improve communication with elevated abstraction Manage complexity with separation Structured methodology improves quality, enables automation Automate and optimize with open, effective tooling A careful blend of approaches, tooling, and modeled/hand coded components can meet real-world challenges Apply proven training and expert mentoring to manage key risks Getting the Payoff With MDD 44

45 Pathfinder Solutions Mission: Generate immediate, bottom line, business results in customer organizations through the adoption of agile, model driven and test driven approaches and technology for systems engineering, software architecture and development. The leading provider of model-driven technology, training and expertise for high performance, embedded, and realtime systems development: Formed in 1995 to bring more complete solutions to customers. We provide training, mentoring, tools, and components for systems engineering, software architecture and development. Rational partner since 1999 PathMATE: the leading PI-MDD automation environment, integrated with RSA, Rhapsody and other UML environments Advanced Getting the Payoff With MDD 45

46 Contact Us Mary Ann Kipp: x115 Peter Fontana: x111 Getting the Payoff With MDD 46