Scripting Technique To Transform Use Case Scenarios To Test Cases - NASA

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Scripting Technique to Transform UseCase Scenarios to Test Cases2012 Annual IV&V WorkshopJesse Musgrove, Andy Chen, Jim Savarino,Shirley Savarino 2009 TASC, Inc.

Background E-911 emergency communication networks has a complex systemof systems architecture. New techniques were needed to aid IV&V in analyzing this type ofcommunication network. Simulink (Architecture) model and Layered Queuing Network(Performance) model of the overall system were developed toassure the correctness of sub-system interfaces and to evaluatethe boundary conditions The use of the system is specified in Use Case Scenarios includevarious call attributes, scripts were utilized to transform theseUse Case Scenarios into test cases for the system simulation. This presentation describes techniques for the transformation ofUse Case Scenarios into Test Cases and how it also enabled us tosimulate more realistic real-world operations. 2009 TASC, Inc.2

Scripting Products and Process OverviewThe Data Dictionary captures aUse Case and feeds the Simulinkand Layered Queuing Network(LQN) models. We pulled allvariables out of the model andmade this aspect table drivenData Dictionary:Parameters andVariables for aparticular instance(Use Case)GUITranslates a usecase to input datafor each model.Architecture (Simulink Model)- Varying levels of fidelity- Allows concatenation of Use Cases- Allows verification of interfacesThe Simulink model reflects the systemarchitecture at various levels of abstraction.Erlang distribution used for internal callprocessing parameters.C# based Graphical User Interface(GUI) takes the parametric UseCase and turns it into individualcalls and attributes for Simulink, callrate and call type probabilities forLQN.Performance (LQN Model)- Performance across a time range- Evaluate Boundary ConditionsModels arevalidated againsteach other forcorrectness 2009 TASC, Inc.The LQN model allows rapidprototyping and is a “process model”.Inputs are parametric, characterizingthe use case3

Data Dictionary Use Case data values captured in Excel, automated feed toeach model Data Dictionary Rigor – required where we obtained datafrom and can be validated as artifacts become availableActionGet ANI ALIActorCPE NACDSSV (seconds)0Variance0SSV obtained from:Estimated valueDefinitionRequest the ANI/ALI from MSAG.Find Call TakerPhone to ALICPE NACDMSAG0200.3Estimated valueEstimated valueRoute the call to a call taker.Lookup the address based on the phone number.OpeningEnglish Call Taker42Estimated valueDuring this time the call taker establishes whether or not the call was anaccident and either begins to identify the caller's language or begin'sgetting information.Hang UpEvaluate LanguageEnglish Call TakerEnglish Call Taker31000Estimated valueEstimated valueHang up if the call was a mis-dial.If the call wasn't an accident, evaluate the caller's language.Verify Accidental CallEnglish Call Taker216Estimated valueIf the call was unintentional and the caller is unaware, the call takermust stay on the line until they can be reasonably sure it was accidental.Transfer CallEnglish Call Taker30Estimated valueIn the case the caller is Spanish speaking, transfer the call.Get Info LocationEnglish Call Taker2812Estimated valueIf the caller is an English speaker, get information and verify theirlocation.Explain DupEnglish Call Taker51Estimated valueIf the incident occurred at the location of an already-reported incident,explain that it is a duplicate and end the call.Get Incident TypeContinue Getting Info 1English Call TakerEnglish Call Taker132074Estimated valueEstimated valueGet information about the emergency.Continue Getting Info 2Dial appropriateEnglish Call TakerEnglish Call Taker7712304Estimated valueEstimated valueContact FLSEnglish Call Taker2013Estimated valueContact Foreign Language Servies (this happens when the caller isneither English nor Spanish-speaking).F Get Info LocationEnglish Call Taker8428Estimated valueSame as above, but through the FLS.F Explain DupEnglish Call Taker107Estimated valueSame as above, but through the FLS. 2009 TASC, Inc.If the caller is calling about a non-emergency, quickly give them thecorrect number and end the call.4

Data Dictionary and Ingest From TASC TSAT experience, goal is to have a datadictionary that automatically feeds into the model andsimulation– Each instantiation of the data dictionary is a use case (e.g. howsystem works at a certain time)– The use cases can be concatenated to come up with a combination ofuse cases, or a use case scenario Data Dictionary came from the LQN development, but usesthe same information for Simulink simulation Differences in how Data Dictionary used in LQN andSimulink– LQN model works off a single use case while the Simulink modelworks off of both a single use case as well as a use case scenario– LQN model uses average values and means-standard deviation/probabilities– Simulink model requires these statistical values to manifestthemselves in a sequence of calls we accomplished this with theC# based GUI to perform the translation 2009 TASC, Inc.5

C# Based GUI for LQN and Simulink Inputs 2009 TASC, Inc.6

LQN Input and Output ExamplesInput Example Input variables extracted fromData Dictionary’s steady-statevalues Varying the call rate andobserve the performanceresponse of the model Important output parameters:– Average Wait Time in Queue– Percent Utilization– Maximum call rate when thesystem becomes saturated(wait time - infinite)Output Example 2009 TASC, Inc.7

Input to Simulink Generated by Graphical UserInterfaceCall 4729133.035060 2009 TASC, Inc.Note: there wereactually around320K calls for the24 hour period8

Simulink Data Flow The objective is to represents an IP packet switching network withan acceptable fidelity Input data (generated by GUI) in Excel spreadsheet format witheach row represents a call and each column represents a callattribute Script reads in the spreadsheet and saves the input data inMATLAB workspace in an array format Simulink model uses SimEvents to generate entities based onarray vectors with attributes, and routes them through the system Results are shown in graphical format, and data is logged for postanalysisCall Input Data Excel Spreadsheet Number of Calls Call Parameters(Attributes) Probabilities arecomputed by aggregatedattribute values Time of calls is made anexplicit call ipt Creates array from InputSpreadsheet Represents SystemTopology Each Vector (Row)represents a call withdesignated attributes System and Subsystems External MATLABfunctions Time increasesmonotonically withinarray Call Routing and Delay 2009 TASC, Inc.Results Graphical Output Verified call routingbased on attributes Verified appropriateimplementation of delays(Call Taker andDispatcher processing)9

Simulink and LQN Results Comparison at 13k Calls/hour for24 hrs (we wanted to make sure models were in sync)Simulink ResultsThis data avail inSimulink, not LQNThis data avail inSimulink, not LQNLQN ResultsCallRate13300AvgECTQueueTime ECT ngAcceptablePercentAvgSCTQueueTime0.885415365SCT Utilization0.0001 ent0.99999948Note: some variation due to translation (e.g. LQN had 13300 calls and Simulink had 13500calls/hour in the 24 hour period) 2009 TASC, Inc.10

The use of the system is specified in Use Case Scenarios include various call attributes, scripts were utilized to transform these Use Case Scenarios into test cases for the system simulation. This presentation describes techniques for the transformation of Use Case Scenarios into Test Cases and how it also enabled us to

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