SlideShare a Scribd company logo
Verification Metrics

         Dave Williamson
CPU Verification and Modeling Manager

       Austin Design Center

              June 2006



                                        1
Verification Metrics: Why do we care?

 Predicting functional closure of a design is hard

 Design verification is typically the critical path

 CPU design projects rarely complete on schedule

 Cost of failure to predict design closure is significant


                                                  2
Two key types of metrics
  Verification test plan based metrics
      Amount of direct tests completed
      Amount of random testing completed
      Number of assertions written
      Amount of functional coverage written and hit
      Verification reviews completed

   Health of the design metrics
      Simulation passing rates
      Bug rate
      Code stability
      Design reviews completed
                                                       3
Challenges and limitations
   Limitations of test plan based metrics
      Will give a best case answer for completion date
      The plan will grow as testing continues

   Limitations of health of the design based metrics
      Can give false impressions if used independent from test plan metrics
      Requires good historical data on similar project for proper interpretation

   General concerns to be aware of for all metrics
     What you measure will affect what you do
     Gathering metrics is not free
     Historical data can be misleading
     Don’t be a slave to the metrics:
         they are a great tool, but not the complete answer

                                                                   4
Bug rate example
                                                                                   Bug History

                  1200                                                                                                                                                         20
                                                                                                      Knee in curve
                                                                                                                                                                               18
                  1000
                                                                                                                                                                               16




                                                                                                                                                                                    Bug Rate Rolling Average
                                                                                                                                                                               14
                   800
Total Bug Count




                                                                                                                                                                               12

                   600                                                                                                                                                         10

                                                                                                                                                                               8
                   400
                                                                                                                                                                               6

                                                                                                                                                                               4
                   200
                                                                                                                                                                               2

                     0                                                                                                                                                         0
                                     13
                                          17
                                               21
                                                    25
                                                         29
                                                              33
                                                                   37
                                                                        41


                                                                                  49




                                                                                                      65
                                                                                                           69




                                                                                                                               85




                                                                                                                                              97
                                                                                                                                                   101
                                                                                                                                                         105
                                                                                                                                                               109
                         1
                             5
                                 9




                                                                             45


                                                                                       53
                                                                                            57
                                                                                                 61




                                                                                                                73
                                                                                                                     77
                                                                                                                          81


                                                                                                                                    89
                                                                                                                                         93




                                                                                                                                                                     113
                                                                                            Week number

                                                    Total Bug Count                Weekly Bug Count (4wk rolling average)

                                                                                                                                                                           5
Bug rate by unit example
                                                   Bug breakdown per design unit

 300




 250




 200




 150




 100




 50




  0




                                                                                                                           1
                                                                                                                           5

                                                                                                                           9

                                                                                                                           3
   1

       5

           9
               13

                    17

                         21



                                   29

                                        33

                                             37



                                                       45

                                                            49

                                                                 53

                                                                      57

                                                                           61

                                                                                65

                                                                                     69

                                                                                          73

                                                                                               77




                                                                                                              89

                                                                                                                   93

                                                                                                                         97
                              25




                                                  41




                                                                                                    81

                                                                                                         85




                                                                                                                        10
                                                                                                                        10

                                                                                                                        10

                                                                                                                        11
                                                                                                                               6
Functional Coverage closure example




                          New coverage
                          points added




                                  7

More Related Content

What's hot

Db access ceemea conference, london
Db access ceemea conference, londonDb access ceemea conference, london
Db access ceemea conference, london
evraz_company
 
IPL SCHEDULE 2010
IPL SCHEDULE 2010IPL SCHEDULE 2010
IPL SCHEDULE 2010
K Rajiv
 
презентация для инвесторов, май 2012
презентация для инвесторов, май 2012презентация для инвесторов, май 2012
презентация для инвесторов, май 2012
evraz_company
 
Business review templates
Business review templatesBusiness review templates
Arizona Real Estate Foreign Buyer Guide
Arizona Real Estate Foreign Buyer GuideArizona Real Estate Foreign Buyer Guide
Arizona Real Estate Foreign Buyer Guide
ARIZONA RETIREMENT COMMUNITIES
 
Une080425
Une080425Une080425
Une080425
anhaa.nuuts
 
Arizona Residential Real Estate Purchase Contract
Arizona Residential Real Estate  Purchase ContractArizona Residential Real Estate  Purchase Contract
Arizona Residential Real Estate Purchase Contract
ARIZONA RETIREMENT COMMUNITIES
 
Personalised Graph-Based Selection of Web APIs
Personalised Graph-Based Selection of Web APIsPersonalised Graph-Based Selection of Web APIs
Personalised Graph-Based Selection of Web APIs
Milan Dojchinovski
 
Olympic Activity Impact Area (TfL)
Olympic Activity Impact Area (TfL)Olympic Activity Impact Area (TfL)
Olympic Activity Impact Area (TfL)
tflslideshare
 
Tajmahal e a4
Tajmahal e a4Tajmahal e a4
Tajmahal e a4
paciffic
 
Session 3 b marie ruel
Session 3 b marie ruelSession 3 b marie ruel
Session 3 b marie ruel
IFPRI
 
Impact of Agricultural Research in Sub-Saharan Africa
Impact of Agricultural Research in Sub-Saharan AfricaImpact of Agricultural Research in Sub-Saharan Africa
Impact of Agricultural Research in Sub-Saharan Africa
International Institute of Tropical Agriculture
 
Rbec country offices gender survey 2012
Rbec country offices  gender survey 2012Rbec country offices  gender survey 2012
Rbec country offices gender survey 2012
Barbora Galvankova
 

What's hot (13)

Db access ceemea conference, london
Db access ceemea conference, londonDb access ceemea conference, london
Db access ceemea conference, london
 
IPL SCHEDULE 2010
IPL SCHEDULE 2010IPL SCHEDULE 2010
IPL SCHEDULE 2010
 
презентация для инвесторов, май 2012
презентация для инвесторов, май 2012презентация для инвесторов, май 2012
презентация для инвесторов, май 2012
 
Business review templates
Business review templatesBusiness review templates
Business review templates
 
Arizona Real Estate Foreign Buyer Guide
Arizona Real Estate Foreign Buyer GuideArizona Real Estate Foreign Buyer Guide
Arizona Real Estate Foreign Buyer Guide
 
Une080425
Une080425Une080425
Une080425
 
Arizona Residential Real Estate Purchase Contract
Arizona Residential Real Estate  Purchase ContractArizona Residential Real Estate  Purchase Contract
Arizona Residential Real Estate Purchase Contract
 
Personalised Graph-Based Selection of Web APIs
Personalised Graph-Based Selection of Web APIsPersonalised Graph-Based Selection of Web APIs
Personalised Graph-Based Selection of Web APIs
 
Olympic Activity Impact Area (TfL)
Olympic Activity Impact Area (TfL)Olympic Activity Impact Area (TfL)
Olympic Activity Impact Area (TfL)
 
Tajmahal e a4
Tajmahal e a4Tajmahal e a4
Tajmahal e a4
 
Session 3 b marie ruel
Session 3 b marie ruelSession 3 b marie ruel
Session 3 b marie ruel
 
Impact of Agricultural Research in Sub-Saharan Africa
Impact of Agricultural Research in Sub-Saharan AfricaImpact of Agricultural Research in Sub-Saharan Africa
Impact of Agricultural Research in Sub-Saharan Africa
 
Rbec country offices gender survey 2012
Rbec country offices  gender survey 2012Rbec country offices  gender survey 2012
Rbec country offices gender survey 2012
 

Viewers also liked

Software metrics
Software metricsSoftware metrics
Software metrics
Ione Donosa
 
A contextual approach to improving software metrics practices
A contextual approach to improving software metrics practicesA contextual approach to improving software metrics practices
A contextual approach to improving software metrics practices
Johnny Kingdom
 
Tools for Software Verification and Validation
Tools for Software Verification and ValidationTools for Software Verification and Validation
Tools for Software Verification and Validation
aliraza786
 
Establishing a Software Measurement Process
Establishing a Software Measurement ProcessEstablishing a Software Measurement Process
Establishing a Software Measurement Process
aliraza786
 
Survey on Software Defect Prediction
Survey on Software Defect PredictionSurvey on Software Defect Prediction
Survey on Software Defect Prediction
Sung Kim
 
Quality in software industry
Quality in software industryQuality in software industry
Quality in software industry
Richa Goel
 
Total quality control
Total quality controlTotal quality control
Total quality control
Aakash Bhongade
 
Chapter 6 software metrics
Chapter 6 software metricsChapter 6 software metrics
Chapter 6 software metrics
despicable me
 
Recommendations to Avoid Problems and Difficulties in Implementing CMMI High ...
Recommendations to Avoid Problems and Difficulties in Implementing CMMI High ...Recommendations to Avoid Problems and Difficulties in Implementing CMMI High ...
Recommendations to Avoid Problems and Difficulties in Implementing CMMI High ...
isabelmargarido
 
Survey on Software Defect Prediction (PhD Qualifying Examination Presentation)
Survey on Software Defect Prediction (PhD Qualifying Examination Presentation)Survey on Software Defect Prediction (PhD Qualifying Examination Presentation)
Survey on Software Defect Prediction (PhD Qualifying Examination Presentation)
lifove
 
13 software metrics
13 software metrics13 software metrics

Viewers also liked (11)

Software metrics
Software metricsSoftware metrics
Software metrics
 
A contextual approach to improving software metrics practices
A contextual approach to improving software metrics practicesA contextual approach to improving software metrics practices
A contextual approach to improving software metrics practices
 
Tools for Software Verification and Validation
Tools for Software Verification and ValidationTools for Software Verification and Validation
Tools for Software Verification and Validation
 
Establishing a Software Measurement Process
Establishing a Software Measurement ProcessEstablishing a Software Measurement Process
Establishing a Software Measurement Process
 
Survey on Software Defect Prediction
Survey on Software Defect PredictionSurvey on Software Defect Prediction
Survey on Software Defect Prediction
 
Quality in software industry
Quality in software industryQuality in software industry
Quality in software industry
 
Total quality control
Total quality controlTotal quality control
Total quality control
 
Chapter 6 software metrics
Chapter 6 software metricsChapter 6 software metrics
Chapter 6 software metrics
 
Recommendations to Avoid Problems and Difficulties in Implementing CMMI High ...
Recommendations to Avoid Problems and Difficulties in Implementing CMMI High ...Recommendations to Avoid Problems and Difficulties in Implementing CMMI High ...
Recommendations to Avoid Problems and Difficulties in Implementing CMMI High ...
 
Survey on Software Defect Prediction (PhD Qualifying Examination Presentation)
Survey on Software Defect Prediction (PhD Qualifying Examination Presentation)Survey on Software Defect Prediction (PhD Qualifying Examination Presentation)
Survey on Software Defect Prediction (PhD Qualifying Examination Presentation)
 
13 software metrics
13 software metrics13 software metrics
13 software metrics
 

Similar to Verification Metrics

It's An A.R.M.'s Race (Acquisition, Retention, and Monetization in Mobile Gam...
It's An A.R.M.'s Race (Acquisition, Retention, and Monetization in Mobile Gam...It's An A.R.M.'s Race (Acquisition, Retention, and Monetization in Mobile Gam...
It's An A.R.M.'s Race (Acquisition, Retention, and Monetization in Mobile Gam...
Brian Sapp
 
Value PMS Motilal Oswal
Value PMS Motilal OswalValue PMS Motilal Oswal
Value PMS Motilal Oswal
chetsons
 
Trust in banks
Trust in banksTrust in banks
Trust in banks
Tamara Avdieieva
 
Exploring ICI water conservation in your service area
Exploring ICI water conservation in your service areaExploring ICI water conservation in your service area
Exploring ICI water conservation in your service area
brentmwhite
 
Layout l01 eng_a3
Layout l01 eng_a3Layout l01 eng_a3
Layout l01 eng_a3
kmaa
 
Concept Design and Validation of LNG Powered Commuter Ferry
Concept Design and Validation of LNG Powered Commuter FerryConcept Design and Validation of LNG Powered Commuter Ferry
Concept Design and Validation of LNG Powered Commuter Ferry
Callum Campbell
 
Reducing Time to Market while ensuring Product Quality and Reliability to Gai...
Reducing Time to Market while ensuring Product Quality and Reliability to Gai...Reducing Time to Market while ensuring Product Quality and Reliability to Gai...
Reducing Time to Market while ensuring Product Quality and Reliability to Gai...
Sharon Rozzi
 
Historic interest rate charts
Historic interest rate chartsHistoric interest rate charts
Historic interest rate charts
primelendingdallas
 
Data-driven teacher effectiveness: Where to begin?
Data-driven teacher effectiveness: Where to begin?Data-driven teacher effectiveness: Where to begin?
Data-driven teacher effectiveness: Where to begin?
Catapult Learning
 
Competition Across Digital Industries Competition Flyer
Competition Across Digital Industries Competition FlyerCompetition Across Digital Industries Competition Flyer
Competition Across Digital Industries Competition Flyer
Chinwag
 
Tsb collaborationacrossdigitalindustries6pagecompflyer
Tsb collaborationacrossdigitalindustries6pagecompflyerTsb collaborationacrossdigitalindustries6pagecompflyer
Tsb collaborationacrossdigitalindustries6pagecompflyer
Paul Hadley
 
Smart metering - the real energy benefits
Smart metering - the real energy benefitsSmart metering - the real energy benefits
Smart metering - the real energy benefits
Eric Salviac
 
Akvo's Admin Features
Akvo's Admin FeaturesAkvo's Admin Features
Akvo's Admin Features
Akvo_slideshare
 
Geom1-2hour3
Geom1-2hour3Geom1-2hour3
Geom1-2hour3
kquarton
 
July 2012 Monthly Report
July 2012 Monthly ReportJuly 2012 Monthly Report
July 2012 Monthly Report
One Columbus
 
Panel 4 carolina rossini
Panel 4  carolina rossiniPanel 4  carolina rossini
Panel 4 carolina rossini
Carolina Rossini
 
Panel4 carolinarossini
Panel4 carolinarossiniPanel4 carolinarossini
Panel4 carolinarossini
REA Brasil
 
AI Eng April 11
AI Eng April 11AI Eng April 11
AI Eng April 11
Embraer RI
 
Agile deployment predictive analytics on hadoop
Agile deployment predictive analytics on hadoopAgile deployment predictive analytics on hadoop
Agile deployment predictive analytics on hadoop
DataWorks Summit
 
Smaato - NOAH12 San Francisco
Smaato - NOAH12 San FranciscoSmaato - NOAH12 San Francisco
Smaato - NOAH12 San Francisco
NOAH Advisors
 

Similar to Verification Metrics (20)

It's An A.R.M.'s Race (Acquisition, Retention, and Monetization in Mobile Gam...
It's An A.R.M.'s Race (Acquisition, Retention, and Monetization in Mobile Gam...It's An A.R.M.'s Race (Acquisition, Retention, and Monetization in Mobile Gam...
It's An A.R.M.'s Race (Acquisition, Retention, and Monetization in Mobile Gam...
 
Value PMS Motilal Oswal
Value PMS Motilal OswalValue PMS Motilal Oswal
Value PMS Motilal Oswal
 
Trust in banks
Trust in banksTrust in banks
Trust in banks
 
Exploring ICI water conservation in your service area
Exploring ICI water conservation in your service areaExploring ICI water conservation in your service area
Exploring ICI water conservation in your service area
 
Layout l01 eng_a3
Layout l01 eng_a3Layout l01 eng_a3
Layout l01 eng_a3
 
Concept Design and Validation of LNG Powered Commuter Ferry
Concept Design and Validation of LNG Powered Commuter FerryConcept Design and Validation of LNG Powered Commuter Ferry
Concept Design and Validation of LNG Powered Commuter Ferry
 
Reducing Time to Market while ensuring Product Quality and Reliability to Gai...
Reducing Time to Market while ensuring Product Quality and Reliability to Gai...Reducing Time to Market while ensuring Product Quality and Reliability to Gai...
Reducing Time to Market while ensuring Product Quality and Reliability to Gai...
 
Historic interest rate charts
Historic interest rate chartsHistoric interest rate charts
Historic interest rate charts
 
Data-driven teacher effectiveness: Where to begin?
Data-driven teacher effectiveness: Where to begin?Data-driven teacher effectiveness: Where to begin?
Data-driven teacher effectiveness: Where to begin?
 
Competition Across Digital Industries Competition Flyer
Competition Across Digital Industries Competition FlyerCompetition Across Digital Industries Competition Flyer
Competition Across Digital Industries Competition Flyer
 
Tsb collaborationacrossdigitalindustries6pagecompflyer
Tsb collaborationacrossdigitalindustries6pagecompflyerTsb collaborationacrossdigitalindustries6pagecompflyer
Tsb collaborationacrossdigitalindustries6pagecompflyer
 
Smart metering - the real energy benefits
Smart metering - the real energy benefitsSmart metering - the real energy benefits
Smart metering - the real energy benefits
 
Akvo's Admin Features
Akvo's Admin FeaturesAkvo's Admin Features
Akvo's Admin Features
 
Geom1-2hour3
Geom1-2hour3Geom1-2hour3
Geom1-2hour3
 
July 2012 Monthly Report
July 2012 Monthly ReportJuly 2012 Monthly Report
July 2012 Monthly Report
 
Panel 4 carolina rossini
Panel 4  carolina rossiniPanel 4  carolina rossini
Panel 4 carolina rossini
 
Panel4 carolinarossini
Panel4 carolinarossiniPanel4 carolinarossini
Panel4 carolinarossini
 
AI Eng April 11
AI Eng April 11AI Eng April 11
AI Eng April 11
 
Agile deployment predictive analytics on hadoop
Agile deployment predictive analytics on hadoopAgile deployment predictive analytics on hadoop
Agile deployment predictive analytics on hadoop
 
Smaato - NOAH12 San Francisco
Smaato - NOAH12 San FranciscoSmaato - NOAH12 San Francisco
Smaato - NOAH12 San Francisco
 

More from DVClub

IP Reuse Impact on Design Verification Management Across the Enterprise
IP Reuse Impact on Design Verification Management Across the EnterpriseIP Reuse Impact on Design Verification Management Across the Enterprise
IP Reuse Impact on Design Verification Management Across the Enterprise
DVClub
 
Cisco Base Environment Overview
Cisco Base Environment OverviewCisco Base Environment Overview
Cisco Base Environment Overview
DVClub
 
Intel Xeon Pre-Silicon Validation: Introduction and Challenges
Intel Xeon Pre-Silicon Validation: Introduction and ChallengesIntel Xeon Pre-Silicon Validation: Introduction and Challenges
Intel Xeon Pre-Silicon Validation: Introduction and Challenges
DVClub
 
Verification of Graphics ASICs (Part II)
Verification of Graphics ASICs (Part II)Verification of Graphics ASICs (Part II)
Verification of Graphics ASICs (Part II)
DVClub
 
Verification of Graphics ASICs (Part I)
Verification of Graphics ASICs (Part I)Verification of Graphics ASICs (Part I)
Verification of Graphics ASICs (Part I)
DVClub
 
Stop Writing Assertions! Efficient Verification Methodology
Stop Writing Assertions! Efficient Verification MethodologyStop Writing Assertions! Efficient Verification Methodology
Stop Writing Assertions! Efficient Verification Methodology
DVClub
 
Validating Next Generation CPUs
Validating Next Generation CPUsValidating Next Generation CPUs
Validating Next Generation CPUs
DVClub
 
Verification Automation Using IPXACT
Verification Automation Using IPXACTVerification Automation Using IPXACT
Verification Automation Using IPXACT
DVClub
 
Validation and Design in a Small Team Environment
Validation and Design in a Small Team EnvironmentValidation and Design in a Small Team Environment
Validation and Design in a Small Team Environment
DVClub
 
Trends in Mixed Signal Validation
Trends in Mixed Signal ValidationTrends in Mixed Signal Validation
Trends in Mixed Signal Validation
DVClub
 
Verification In A Global Design Community
Verification In A Global Design CommunityVerification In A Global Design Community
Verification In A Global Design Community
DVClub
 
Design Verification Using SystemC
Design Verification Using SystemCDesign Verification Using SystemC
Design Verification Using SystemC
DVClub
 
Verification Strategy for PCI-Express
Verification Strategy for PCI-ExpressVerification Strategy for PCI-Express
Verification Strategy for PCI-Express
DVClub
 
SystemVerilog Assertions (SVA) in the Design/Verification Process
SystemVerilog Assertions (SVA) in the Design/Verification ProcessSystemVerilog Assertions (SVA) in the Design/Verification Process
SystemVerilog Assertions (SVA) in the Design/Verification Process
DVClub
 
Efficiency Through Methodology
Efficiency Through MethodologyEfficiency Through Methodology
Efficiency Through Methodology
DVClub
 
Pre-Si Verification for Post-Si Validation
Pre-Si Verification for Post-Si ValidationPre-Si Verification for Post-Si Validation
Pre-Si Verification for Post-Si Validation
DVClub
 
OpenSPARC T1 Processor
OpenSPARC T1 ProcessorOpenSPARC T1 Processor
OpenSPARC T1 Processor
DVClub
 
Intel Atom Processor Pre-Silicon Verification Experience
Intel Atom Processor Pre-Silicon Verification ExperienceIntel Atom Processor Pre-Silicon Verification Experience
Intel Atom Processor Pre-Silicon Verification Experience
DVClub
 
Using Assertions in AMS Verification
Using Assertions in AMS VerificationUsing Assertions in AMS Verification
Using Assertions in AMS Verification
DVClub
 
Low-Power Design and Verification
Low-Power Design and VerificationLow-Power Design and Verification
Low-Power Design and Verification
DVClub
 

More from DVClub (20)

IP Reuse Impact on Design Verification Management Across the Enterprise
IP Reuse Impact on Design Verification Management Across the EnterpriseIP Reuse Impact on Design Verification Management Across the Enterprise
IP Reuse Impact on Design Verification Management Across the Enterprise
 
Cisco Base Environment Overview
Cisco Base Environment OverviewCisco Base Environment Overview
Cisco Base Environment Overview
 
Intel Xeon Pre-Silicon Validation: Introduction and Challenges
Intel Xeon Pre-Silicon Validation: Introduction and ChallengesIntel Xeon Pre-Silicon Validation: Introduction and Challenges
Intel Xeon Pre-Silicon Validation: Introduction and Challenges
 
Verification of Graphics ASICs (Part II)
Verification of Graphics ASICs (Part II)Verification of Graphics ASICs (Part II)
Verification of Graphics ASICs (Part II)
 
Verification of Graphics ASICs (Part I)
Verification of Graphics ASICs (Part I)Verification of Graphics ASICs (Part I)
Verification of Graphics ASICs (Part I)
 
Stop Writing Assertions! Efficient Verification Methodology
Stop Writing Assertions! Efficient Verification MethodologyStop Writing Assertions! Efficient Verification Methodology
Stop Writing Assertions! Efficient Verification Methodology
 
Validating Next Generation CPUs
Validating Next Generation CPUsValidating Next Generation CPUs
Validating Next Generation CPUs
 
Verification Automation Using IPXACT
Verification Automation Using IPXACTVerification Automation Using IPXACT
Verification Automation Using IPXACT
 
Validation and Design in a Small Team Environment
Validation and Design in a Small Team EnvironmentValidation and Design in a Small Team Environment
Validation and Design in a Small Team Environment
 
Trends in Mixed Signal Validation
Trends in Mixed Signal ValidationTrends in Mixed Signal Validation
Trends in Mixed Signal Validation
 
Verification In A Global Design Community
Verification In A Global Design CommunityVerification In A Global Design Community
Verification In A Global Design Community
 
Design Verification Using SystemC
Design Verification Using SystemCDesign Verification Using SystemC
Design Verification Using SystemC
 
Verification Strategy for PCI-Express
Verification Strategy for PCI-ExpressVerification Strategy for PCI-Express
Verification Strategy for PCI-Express
 
SystemVerilog Assertions (SVA) in the Design/Verification Process
SystemVerilog Assertions (SVA) in the Design/Verification ProcessSystemVerilog Assertions (SVA) in the Design/Verification Process
SystemVerilog Assertions (SVA) in the Design/Verification Process
 
Efficiency Through Methodology
Efficiency Through MethodologyEfficiency Through Methodology
Efficiency Through Methodology
 
Pre-Si Verification for Post-Si Validation
Pre-Si Verification for Post-Si ValidationPre-Si Verification for Post-Si Validation
Pre-Si Verification for Post-Si Validation
 
OpenSPARC T1 Processor
OpenSPARC T1 ProcessorOpenSPARC T1 Processor
OpenSPARC T1 Processor
 
Intel Atom Processor Pre-Silicon Verification Experience
Intel Atom Processor Pre-Silicon Verification ExperienceIntel Atom Processor Pre-Silicon Verification Experience
Intel Atom Processor Pre-Silicon Verification Experience
 
Using Assertions in AMS Verification
Using Assertions in AMS VerificationUsing Assertions in AMS Verification
Using Assertions in AMS Verification
 
Low-Power Design and Verification
Low-Power Design and VerificationLow-Power Design and Verification
Low-Power Design and Verification
 

Recently uploaded

How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfHow to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
Chart Kalyan
 
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and MilvusBuilding Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
Zilliz
 
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Jeffrey Haguewood
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Alpen-Adria-Universität
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
Jakub Marek
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
danishmna97
 
Serial Arm Control in Real Time Presentation
Serial Arm Control in Real Time PresentationSerial Arm Control in Real Time Presentation
Serial Arm Control in Real Time Presentation
tolgahangng
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Tomaz Bratanic
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
Jason Packer
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
akankshawande
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
Pixlogix Infotech
 
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying AheadDigital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Wask
 
Recommendation System using RAG Architecture
Recommendation System using RAG ArchitectureRecommendation System using RAG Architecture
Recommendation System using RAG Architecture
fredae14
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
panagenda
 
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
saastr
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
Matthew Sinclair
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
Tatiana Kojar
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Zilliz
 
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Malak Abu Hammad
 

Recently uploaded (20)

How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfHow to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
 
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and MilvusBuilding Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
 
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
 
Serial Arm Control in Real Time Presentation
Serial Arm Control in Real Time PresentationSerial Arm Control in Real Time Presentation
Serial Arm Control in Real Time Presentation
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
 
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying AheadDigital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying Ahead
 
Recommendation System using RAG Architecture
Recommendation System using RAG ArchitectureRecommendation System using RAG Architecture
Recommendation System using RAG Architecture
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
 
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
 
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
 
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
 

Verification Metrics

  • 1. Verification Metrics Dave Williamson CPU Verification and Modeling Manager Austin Design Center June 2006 1
  • 2. Verification Metrics: Why do we care?  Predicting functional closure of a design is hard  Design verification is typically the critical path  CPU design projects rarely complete on schedule  Cost of failure to predict design closure is significant 2
  • 3. Two key types of metrics  Verification test plan based metrics  Amount of direct tests completed  Amount of random testing completed  Number of assertions written  Amount of functional coverage written and hit  Verification reviews completed  Health of the design metrics  Simulation passing rates  Bug rate  Code stability  Design reviews completed 3
  • 4. Challenges and limitations  Limitations of test plan based metrics  Will give a best case answer for completion date  The plan will grow as testing continues  Limitations of health of the design based metrics  Can give false impressions if used independent from test plan metrics  Requires good historical data on similar project for proper interpretation  General concerns to be aware of for all metrics  What you measure will affect what you do  Gathering metrics is not free  Historical data can be misleading  Don’t be a slave to the metrics:  they are a great tool, but not the complete answer 4
  • 5. Bug rate example Bug History 1200 20 Knee in curve 18 1000 16 Bug Rate Rolling Average 14 800 Total Bug Count 12 600 10 8 400 6 4 200 2 0 0 13 17 21 25 29 33 37 41 49 65 69 85 97 101 105 109 1 5 9 45 53 57 61 73 77 81 89 93 113 Week number Total Bug Count Weekly Bug Count (4wk rolling average) 5
  • 6. Bug rate by unit example Bug breakdown per design unit 300 250 200 150 100 50 0 1 5 9 3 1 5 9 13 17 21 29 33 37 45 49 53 57 61 65 69 73 77 89 93 97 25 41 81 85 10 10 10 11 6
  • 7. Functional Coverage closure example New coverage points added 7

Editor's Notes

  1. 1. More so than other areas of processor design, visibility of completion is still fairly low at the end of the project. Dreaded “when will we find the last bug” question. 2. Verification complexity increases non-linearly with design complexity 3. empirical evidence shows that projects are almost always delayed. Best case they hit the externally published schedule, but usually this is the 2 nd or 3 rd internal schedule… 4. Conservative estimates means lost design win opportunities, Optimistic estimates means slipped schedules or buggy silicon
  2. 1. Verification metrics are what is controlled by the DV team, health of the design is somewhat out of the control of the DV team 2. All metrics can be applied to full chip, or unit level of the design
  3. Test plan only covers what you know to do, not what do don’t know yet you need to do Test plan is non-exhaustive and when you find bugs in the design, new corner cases are exposed. This will happen all the way to the end of the project (historical data can help) Health of the design can look better or worse than what it really is based on what is currently happening on the testing side Most health of the design metrics are trailing indicators, so you really need good historical data on similar projects to make full use of them Need to be careful to avoid meeting the letter of the law but not the intent: For example, if you have hard metrics on cycles run per week or tests written per week, test/cycle quality might go down. Need to think up front about how you want to use metrics to make sure you track the right things and also need to account for the time to build the infrastructure required to do it Historical data is very useful, but every project is different, and generally speaking future projects are more complex than previous ones, so needs to be taken with a grain of salt Metrics won’t replace subjective gut feel from experience. If gut feel is that the design is not ready for tapeout, then it probably isn’t. Need to take metric results with a grain of salt. This applies to the final ‘when we done’ as well as determing critical priorities throughout the project
  4. Total bug graph fairly linear with one pronounced knee at about the 75% point Bugs per week pretty sporadic until it drops off at knee This is 4 week rolling average…results are even more sporadic if raw count is used
  5. Breakdown by unit can be useful to indicate early stablilty of certain units (or point to deficit testing) Relative number of bugs found per area is roughly consistent with expectations based on complexity of each unit SIMD unit was an early focus and got stable before the rest of the design
  6. Getting up to low 90% happens pretty quickly and most of the time is spent on closing the final 5% of the points Expect to have a few dips along the way as new coverage that wasn’t originally planned is added to the design May improve tracking in the future…breakout crosses vs. single points, add some way to indicate priority of points