Modeling and Analysis Overview

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Prudence Parsons
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1 U" U' diagnostic quality CoO image quality U throughput purchase T price IQ spec typical case BoM B profit margin standard workstation CPU budget S Moore's law memory budget common console render engine P' M processing P pixel library memory depth limit M' by Gerrit Muller HSN-NISE gaudisite@gmail.com Abstract The course Modeling and Analysis is described. The program consists of 10 modules. The course format, iterating theory, illustration and interaction is explained. The course heavily emphasizes the practical application of the method. This presentation shows the overview of the modeling and analysis approach and the methods and techniques that will be elaborated in the rest of the course. facts from research measurements assumptions modeling analysis results decisions decision project man. business making specification The complete course MA 611 TM is owned by TNO-ESI. To teach this course a license from HSN-NISE is required. This material is preliminary course material. The final material and course information can be found at: status: preliminary draft collect input data usage context enterprise & users requirements black box view creation life cycle business life cycle context system realization technology model and analyse relevant issues for different stakeholders& concerns integration and reasoning

2 Positioning Modeling and Analysis in Architecting vague notion of the problem architecting architecture description: articulated structured problem and solution know-how vague notion of potential solutions Report Spec Design basic methods modeling and analysis architecting method: framework submethods integration methods 2 Gerrit Muller MAOmethod

3 Modeling and Analysis supports: understanding exploration optimization verification Type of model depends on project phase Models have a goal Goals evolve and models evolve Techniques are used to reach this goal 3 Gerrit Muller MAOwhyModeling

4 Purpose of Modeling specification facts from research modeling project verification measurements results assumptions analysis decisions uncertainties unknowns errors accuracy working range credibility risk customer satisfaction time, cost, effort profit margin 4 Gerrit Muller MAOpurpose

5 What to Model? business: profit, etc. operational costs stakeholder benefits workload risks usage context key performance: throughput, response reliability availability scalability... and their mutual relations (emerging?) properties: resource utilization load latency, throughput quality, accuracy... system enterprise & users business: profit, etc. operational costs stakeholder benefits workload risks requirements black box view creation life cycle business life cycle context realization technology 5 Gerrit Muller MAOwhatModeling

6 Program of Modeling and Analysis Course 1. overall approach intro, overall approach, exercise overall approach day 1 day 2 day 3 2. input facts, data, uncertainties quantification, measurements, modeling, validation, technology background, lifecycle and business input sources 3. system modeling purpose, approaches, patterns, modularity, parametrization, means, exploration, visualization, micro-benchmarking, characterization, performance as example 4. application, life-cycle modeling reiteration of modeling approach (see module 3), applied on customer application and business, and life cycle 5. integration and reasoning relating key driver models to models, model based threads of reasoning, FMEA-like approach, modeling in project life-cycle 6. analysis, using models sensitivity, robustness, worst case, working range, scalability, exceptions, changes 6 Gerrit Muller ESICmodelingAndAnlysisModules

7 Overview of Approach facts from research measurements assumptions modeling analysis results decision making decisions project man. business specification usage context enterprise & users collect input data requirements black box view creation life cycle business life cycle context system realization technology model and analyse relevant issues for different stakeholders& concerns integration and reasoning U" U' diagnostic quality CoO image quality U throughput T purchase price IQ spec typical case BoM B profit margin standard workstation S CPU budget Moore's law memory budget common console render engine P' M processing P pixel library memory depth limit M' 7 Gerrit Muller MAOoverview

8 Iteration over viewpoints usage context enterprise & users context understanding requirements black box view intention system realization technology objective driven opportunities constraint awareness creation life cycle business life cycle context know how based 8 Gerrit Muller MAOiteration

High Level Modeling to Support Software Design

High Level Modeling to Support Software Design by Gerrit Muller Buskerud University College e-mail: gaudisite@gmail.com www.gaudisite.nl Abstract High level models are simple models with the primary goal to support understanding, analysis, communication