Risk ManagementRisks and Risk ManagementRisks a.docxjoellemurphey
Risk Management
*
Risks and Risk ManagementRisks are potential events that have negative impacts on safety or project technical performance, cost or scheduleRisks are an inevitable fact of life – risks can be reduced but never eliminatedRisk Management comprises purposeful thought to the sources, magnitude, and mitigation of risk, and actions directed toward its balanced reductionBeneficial Risk - The same tools and perspectives that are used to discover, manage and reduce risks can be used to discover, manage and increase project opportunities (increased performance).
*
*
What if?
IF
Predict “IF” IdentifyEvaluate “IF” AnalyzePlan for “IF” PlanTracking “IF” TrackBudget for “IF” Control
Risk Management
LawsTermsTypes of RiskRisk Management
LawsMurphy’s Law
If something can go wrong it will go wrong
Finagle’s Law of Dynamic Negatives (corollary to Murphy’s Law
Things will go wrong at the worst possible time
What is Risk Management?Seeks or identifies risksAssesses the likelihood and impact of these risksDevelops mitigation options for all identified risksIdentifies the most significant risks and chooses which mitigation options to implementTracks progress to confirm that cumulative project risk is indeed decliningCommunicates and documents the project risk statusRepeats this process throughout the project life
Risk management is a continuous and iterative decision making technique designed to improve the probability of success. It is a proactive approach that:
*
*
Risk Matrix
*
Impact
Probability of Occurrence
3
2
4
1
Risk Warning SignsTPMsSchedule ProjectionsCost ProjectionsSupplier problemsLate technology demonstrations
Types of RiskTechnical Risks
Programmatic RisksCost Schedule
Supportability Risks
Beneficial Risks
Risk AnalysisWhat Could Go WrongWhat is the ProbabilityWhat is the Magnitude of ImpactCostSchedulePerformance
Alternate Strategies (Off Ramps)
Beneficial RiskHigh Risk – High Payoff
Mitigation StrategyAlternate PlansCriteriaScheduleBudget
Risk HandlingHave a PlanTotal ProgramBudget (Cost / Schedule) for PlanGet “Buy-In”Monitor StatusMetricsClose out
Risk – In GeneralRisk is HealthyNot Identifying Risk shows:You don’t understand the program
AND/ORYou are dishonest
AND/ORYou think the customer is stupidIdentify all potential RiskKnock them down with Mitigation Plans
Summary
“It’s risky not to embrace risk.”
SE = Technical Program MgmtKey focus of systems engineeringincludes the direction of a totally integrated effort of system design, test and evaluation, production, and logistics support over the system life cycleThe goal is timely deployment of an effective system, sustaining it, and satisfying the user’s need at an affordable cost.Involves balancing a system’s cost, schedule, and performance while controlling risk.
*
Technical Performance MeasuresTPMs are measures of the system technical performance that have been chosen because they ...
Routine data quality assessment tool june 2008swiss1234
This document provides instructions for conducting a Routine Data Quality Assessment (RDQA) to evaluate program or project data quality. It outlines a 6-step process: 1) determine the purpose, 2) select levels and sites, 3) identify indicators and data sources, 4) conduct site visits, 5) review outputs and findings, and 6) develop a strengthening plan. The checklist is meant to assess data quality and systems at various levels, from service delivery points to central aggregation sites. Results are summarized using graphs and an action plan is developed to identify weaknesses and areas for improvement.
Routine data quality assessment tool june 2008swiss1234
This document provides instructions for conducting a Routine Data Quality Assessment (RDQA) to evaluate program or project monitoring and evaluation systems. The RDQA involves selecting levels of the data reporting system to review, identifying indicators and time periods to assess, conducting site visits using checklists, and developing an action plan to strengthen areas of weakness. Site visits include verifying reported data against source documents, assessing data management processes, and providing recommendations. Dashboards then summarize findings to prioritize improvements to data quality.
The document discusses risk management and identifying risks on projects. It provides several approaches to risk identification, including analyzing risk sources both internally and externally, considering objectives and scenarios, using risk taxonomies, and checking common risk lists. Specific methods covered are objectives-based identification, scenario analysis, taxonomy-based identification, common-risk checking, and risk charting. The document then discusses scope risks and schedule risks specifically, providing examples of each and questions to consider to identify those risks.
The document discusses software measurement standards and metrics for measuring non-functional elements of software. It covers:
1) Drivers for measuring elements like size, activity, quality, cost and workload using metrics like Automated Function Points and Automated Enhancement Points.
2) Measurement solutions from OMG standards to increase visibility on software size, activity, quality through metrics like AFP, AEP, AEFP and AETP.
3) Effective sizing metrics like AFP which measures functionality and AEP which measures enhancements and maintenance activities between releases.
The document discusses various techniques for planning software projects, including scoping the project, estimating effort and timelines, identifying risks, creating schedules, and developing control strategies. It covers estimating project size through techniques like function point analysis and lines of code counting. It also discusses decomposing projects into sub-problems and estimating effort for each through methods like problem-based estimation and process-based estimation using standard components. Data flow diagrams and entity relationship diagrams are presented as tools for modeling systems and defining requirements.
The document discusses various techniques for planning software projects, including scoping the project, estimating effort and timelines, identifying risks, creating schedules, and developing control strategies. It covers estimating project size through techniques like function point analysis and lines of code counting. It also discusses decomposing projects into sub-problems and estimating effort for each through methods like problem-based estimation and process-based estimation using standard components. Data flow diagrams and entity relationship diagrams are presented as tools for modeling systems and defining requirements.
Risk ManagementRisks and Risk ManagementRisks a.docxjoellemurphey
Risk Management
*
Risks and Risk ManagementRisks are potential events that have negative impacts on safety or project technical performance, cost or scheduleRisks are an inevitable fact of life – risks can be reduced but never eliminatedRisk Management comprises purposeful thought to the sources, magnitude, and mitigation of risk, and actions directed toward its balanced reductionBeneficial Risk - The same tools and perspectives that are used to discover, manage and reduce risks can be used to discover, manage and increase project opportunities (increased performance).
*
*
What if?
IF
Predict “IF” IdentifyEvaluate “IF” AnalyzePlan for “IF” PlanTracking “IF” TrackBudget for “IF” Control
Risk Management
LawsTermsTypes of RiskRisk Management
LawsMurphy’s Law
If something can go wrong it will go wrong
Finagle’s Law of Dynamic Negatives (corollary to Murphy’s Law
Things will go wrong at the worst possible time
What is Risk Management?Seeks or identifies risksAssesses the likelihood and impact of these risksDevelops mitigation options for all identified risksIdentifies the most significant risks and chooses which mitigation options to implementTracks progress to confirm that cumulative project risk is indeed decliningCommunicates and documents the project risk statusRepeats this process throughout the project life
Risk management is a continuous and iterative decision making technique designed to improve the probability of success. It is a proactive approach that:
*
*
Risk Matrix
*
Impact
Probability of Occurrence
3
2
4
1
Risk Warning SignsTPMsSchedule ProjectionsCost ProjectionsSupplier problemsLate technology demonstrations
Types of RiskTechnical Risks
Programmatic RisksCost Schedule
Supportability Risks
Beneficial Risks
Risk AnalysisWhat Could Go WrongWhat is the ProbabilityWhat is the Magnitude of ImpactCostSchedulePerformance
Alternate Strategies (Off Ramps)
Beneficial RiskHigh Risk – High Payoff
Mitigation StrategyAlternate PlansCriteriaScheduleBudget
Risk HandlingHave a PlanTotal ProgramBudget (Cost / Schedule) for PlanGet “Buy-In”Monitor StatusMetricsClose out
Risk – In GeneralRisk is HealthyNot Identifying Risk shows:You don’t understand the program
AND/ORYou are dishonest
AND/ORYou think the customer is stupidIdentify all potential RiskKnock them down with Mitigation Plans
Summary
“It’s risky not to embrace risk.”
SE = Technical Program MgmtKey focus of systems engineeringincludes the direction of a totally integrated effort of system design, test and evaluation, production, and logistics support over the system life cycleThe goal is timely deployment of an effective system, sustaining it, and satisfying the user’s need at an affordable cost.Involves balancing a system’s cost, schedule, and performance while controlling risk.
*
Technical Performance MeasuresTPMs are measures of the system technical performance that have been chosen because they ...
Routine data quality assessment tool june 2008swiss1234
This document provides instructions for conducting a Routine Data Quality Assessment (RDQA) to evaluate program or project data quality. It outlines a 6-step process: 1) determine the purpose, 2) select levels and sites, 3) identify indicators and data sources, 4) conduct site visits, 5) review outputs and findings, and 6) develop a strengthening plan. The checklist is meant to assess data quality and systems at various levels, from service delivery points to central aggregation sites. Results are summarized using graphs and an action plan is developed to identify weaknesses and areas for improvement.
Routine data quality assessment tool june 2008swiss1234
This document provides instructions for conducting a Routine Data Quality Assessment (RDQA) to evaluate program or project monitoring and evaluation systems. The RDQA involves selecting levels of the data reporting system to review, identifying indicators and time periods to assess, conducting site visits using checklists, and developing an action plan to strengthen areas of weakness. Site visits include verifying reported data against source documents, assessing data management processes, and providing recommendations. Dashboards then summarize findings to prioritize improvements to data quality.
The document discusses risk management and identifying risks on projects. It provides several approaches to risk identification, including analyzing risk sources both internally and externally, considering objectives and scenarios, using risk taxonomies, and checking common risk lists. Specific methods covered are objectives-based identification, scenario analysis, taxonomy-based identification, common-risk checking, and risk charting. The document then discusses scope risks and schedule risks specifically, providing examples of each and questions to consider to identify those risks.
The document discusses software measurement standards and metrics for measuring non-functional elements of software. It covers:
1) Drivers for measuring elements like size, activity, quality, cost and workload using metrics like Automated Function Points and Automated Enhancement Points.
2) Measurement solutions from OMG standards to increase visibility on software size, activity, quality through metrics like AFP, AEP, AEFP and AETP.
3) Effective sizing metrics like AFP which measures functionality and AEP which measures enhancements and maintenance activities between releases.
The document discusses various techniques for planning software projects, including scoping the project, estimating effort and timelines, identifying risks, creating schedules, and developing control strategies. It covers estimating project size through techniques like function point analysis and lines of code counting. It also discusses decomposing projects into sub-problems and estimating effort for each through methods like problem-based estimation and process-based estimation using standard components. Data flow diagrams and entity relationship diagrams are presented as tools for modeling systems and defining requirements.
The document discusses various techniques for planning software projects, including scoping the project, estimating effort and timelines, identifying risks, creating schedules, and developing control strategies. It covers estimating project size through techniques like function point analysis and lines of code counting. It also discusses decomposing projects into sub-problems and estimating effort for each through methods like problem-based estimation and process-based estimation using standard components. Data flow diagrams and entity relationship diagrams are presented as tools for modeling systems and defining requirements.
The document describes a method for identifying process-related risks from event logs in order to predict potential delays in business processes. It involves:
1. Defining Process Risk Indicators (PRIs) that indicate a higher likelihood of delays, such as atypical activity durations, multiple activity repetitions, or high resource workload.
2. Configuring the PRIs by analyzing past event logs to determine appropriate thresholds that achieve a desired prediction precision.
3. Applying the configured PRIs to a current case by comparing its attributes to the PRI thresholds to identify if any risks are present and predict the likelihood of a delay.
The method was implemented and validated using real event logs from an insurance company, achieving over
This document provides an overview of performance testing and the Rational Performance Tester tool. It discusses why performance testing is important, different types of performance testing, performance engineering methodology, performance objectives and metrics. It also provides an overview of the Rational Performance Tester tool, describing its test creation, editing, workload scheduling, execution and results evaluation capabilities.
Recommender Systems from A to Z – The Right DatasetCrossing Minds
In the last years a lot of improvements were done in the field of Machine Learning and the Tools that support the community of developers. But still, implementing a recommender system is very hard.
That is why at Crossing Minds, we decided to create a series of 4 meetups to discuss how to implement a recommender system end-to-end:
Part 1 – The Right Dataset
Part 2 – Model Training
Part 3 – Model Evaluation
Part 4 – Real-Time Deployment
This first meetup will be about building the right dataset and doing all the preprocessing needed to create different models. We will talk about explicit vs implicit feedback, dataset analysis, likes/dislikes vs ratings, users and items features, normalization and similarities.
This document discusses reproducibility in R and tools provided by Revolution Analytics to improve reproducibility. It summarizes R's growing popularity, its use by major companies like Google and Facebook, and fields that use R like insurance, finance, agriculture, and more. It then discusses the importance of reproducible research and defines reproducibility. Finally, it outlines Revolution Analytics' reproducibility tools like Revolution R Open, a static CRAN mirror, daily CRAN snapshots, and the checkpoint package to ensure projects use consistent package versions.
The document discusses the NASA approach to prioritizing software verification and validation (IV&V) tasks. It describes the Software Integrity Level Assessment Process (SILAP) used to determine the risk level of software components and identify the appropriate set of IV&V tasks. SILAP involves assessing the consequence of potential defects and error potential of software based on factors like developer experience and complexity. The resulting risk scores map to specific IV&V tasks to establish confidence in software fitness for purpose.
The document discusses various software metrics that can be used to measure attributes of software products and processes. It describes metrics for size (e.g. lines of code), complexity (e.g. cyclomatic complexity), quality (e.g. defects per KLOC), design (e.g. coupling and cohesion), and object-oriented software (e.g. weighted methods per class). The goals of metrics include estimating costs, evaluating quality, and improving processes and products.
Simplifying effort estimation based on use case pointsAbdulrhman Shaheen
This document describes an experiment to evaluate methods for simplifying the use case points (UCP) software effort estimation technique while maintaining accuracy. The experiment analyzed 14 projects to test hypotheses around simplifying factors like actors, transactions vs steps, and technical/environmental factors. Results found that transactions outperformed steps, many factors had minor impact or overlapped and could be removed, and total steps or transactions could estimate effort nearly as well as UCP with simpler calculations. Threats to the study's validity were also addressed.
The document provides guidance for project tollgates at Tollgate Guiding Thoughts. Tollgates will focus on the 15 deliverable format and demonstrating the logical thought process through each project phase. Presentations should show work to complete a phase and tasks/dates for the next phase, and identify any barriers needing assistance. The primary tools listed are suggested but not mandatory ways to show project progression.
The document discusses metrics for evaluating the quality of software specifications. It defines key terms like measures, metrics, and indicators. It then provides examples of metrics that can measure the completeness, lack of ambiguity, and other qualities of a software specification. These include calculating the total number of requirements and the number that are unambiguous. The document also discusses using metrics in small organizations and provides an example where metrics are used to analyze efforts to reduce the time taken to implement change requests.
The document evaluates alternative methods to approximating historical value at risk (HsVaR) that can significantly reduce computational requirements compared to the full revaluation method, while maintaining acceptable accuracy. It considers a sample portfolio and calculates HsVaR using full revaluation and approximation methods involving delta, delta-gamma, and delta-gamma-theta. The results show the approximation methods produce HsVaR values close to full revaluation, within 1-18%, while requiring far fewer valuations, resulting in up to 99.6% reduction in computations. This demonstrates the tradeoff between accuracy and reduced processing from using approximation methods.
The document describes a new system being implemented to improve an executive appointment process. The current system has several problems, including being time-consuming and prone to errors. The new system is a web-based data entry app that allows information to be directly input and instantly accessible across departments. This is expected to increase efficiency, decrease frustration and errors, and reduce downtime and costs associated with the current system. The impact will be measured through surveys, analyzing downtime records, and comparing efficiency metrics like labor costs and number of steps per appointment before and after the new system. Diagrams depict the existing and modified appointment processes and a prototype of the new system is demonstrated.
The document discusses topics related to rapid software development and evolution, including agile methods, extreme programming, rapid application development, and software prototyping. It provides details on characteristics of rapid application development processes like concurrent specification, design, and implementation. Iterative development approaches are covered along with advantages and challenges. Specific agile methods like extreme programming, with practices like test-driven development and pair programming, are also summarized.
We have experience with testing projects, both large and small. Sometimes our test estimates are accurate—and sometimes they’re not. We often miss deadlines because there are no defined criteria used to create our estimates. Sometimes we miss our schedules due to crunched testing timelines. Shyam Sunder briefly describes the different test estimation techniques including Simple, Medium, Complex; Top Down, Bottom Up; and Test Point Analysis. To assist in better estimating in the future, Shyam has prepared test estimation templates and guidelines, which can significantly help organizations in proper estimation of testing projects. Through his work, effort and schedule variations have significantly improved from ±60 percent to ±2 percent. Shyam explains the test estimation templates in detail and demonstrates how to choose the estimation templates for your organization’s software development process. Learn why effective software test estimation techniques help in tracking and controlling cost/effort overruns significantly.
How do you know what to monitor in your environment? Failure modes have become so complex that we need a cross-functional view of the system to identify what failure looks like. This talks walks through the FMEA process as applied to monitoring and metrics collection. The process will help you identify your failure points and the risks associated with a particular failure mode.
PG&E's Distribution Resources Plan (DRP) evaluates the locational benefits and costs of distributed energy resources (DERs) on PG&E's distribution system. The plan analyzes over 102,000 distribution line sections across PG&E's service territory to determine each section's integration capacity for 10 different DER types. The analysis considers various power system criteria like thermal limits, voltage regulation, protection, and reliability. The DRP aims to identify optimal locations for DER deployment based on reductions in local grid upgrades and investments.
Performance doesn’t have the same definition between system administrators, developpers and business teams. What is Performance ? High CPU usage, not scalable web site, low business transaction rate per sec, slow response time, … This presentation is about maths, code performance, load testing, web performance, best practices, … Working on performance optimizaton is a very broad topic. It’s important to really understand main concepts and to have a clean and strong methodology because it could be a very time consumming activity. Happy reading !
Shyam Nagabandi has over 8 years of experience in software testing, including 4 years testing utilities systems. He has expertise in mainframe, web, and performance testing. Some of his skills include test planning, test case development, defect management, and experience with tools like HP LoadRunner and ALM. He has worked as a test lead on several projects for Southern California Edison.
This talk will review a number of application assessment techniques and discuss the types of security vulnerabilities they are best suited to identify as well as how the different approaches can be used in combination to produce more thorough and insightful results. Code review will be compared to penetration testing and the capabilities of automated tools will be compared to manual techniques. In addition, the role of threat modeling and architecture analysis will be examined. The goal is to illuminate assessment techniques that go beyond commodity point-and-click approaches to web application or code scanning.
From the OWASP Northern Virginia meeting August 6, 2009.
This document provides an overview of risk-adjusted estimating techniques for quantifying and accounting for uncertainty in project cost estimates. It discusses point estimating, uncertainty in estimates, and different types of risks including aleatory, systemic, and project-specific risks. It also covers quantifying uncertainty through qualitative analysis, quantitative analysis using historical data, and Monte Carlo simulation. The document emphasizes that simply adding individual estimates does not accurately capture total project uncertainty and risk, and that simulation methods are better for estimating overall program costs.
This document outlines a 4-day Python programming class covering basic Python, advanced Python, web scraping with Python, and building a web application with Python. On the fourth day, students will learn about CRUD operations, databases, and the ORM pattern. They will also learn to build an HTTP server, develop web applications with the Flask framework, access GPIO pins on the Raspberry Pi, and control an LCD display on the Raspberry Pi. As a final project, students will build a simple control center web application for the Raspberry Pi that accesses I/O using Flask and Python.
This document provides information about accessing and parsing web data using Python and BeautifulSoup. It discusses setting up a development environment on a Raspberry Pi with Python, Flask, and BeautifulSoup installed. It covers retrieving HTML data using urllib and parsing it using BeautifulSoup to extract tags and attributes. Common issues like HTTP errors and missing tags are addressed. Exercises demonstrate getting title data from a URL and extracting tags by class attribute.
More Related Content
Similar to Determination of Repro Rates 20140724.pdf
The document describes a method for identifying process-related risks from event logs in order to predict potential delays in business processes. It involves:
1. Defining Process Risk Indicators (PRIs) that indicate a higher likelihood of delays, such as atypical activity durations, multiple activity repetitions, or high resource workload.
2. Configuring the PRIs by analyzing past event logs to determine appropriate thresholds that achieve a desired prediction precision.
3. Applying the configured PRIs to a current case by comparing its attributes to the PRI thresholds to identify if any risks are present and predict the likelihood of a delay.
The method was implemented and validated using real event logs from an insurance company, achieving over
This document provides an overview of performance testing and the Rational Performance Tester tool. It discusses why performance testing is important, different types of performance testing, performance engineering methodology, performance objectives and metrics. It also provides an overview of the Rational Performance Tester tool, describing its test creation, editing, workload scheduling, execution and results evaluation capabilities.
Recommender Systems from A to Z – The Right DatasetCrossing Minds
In the last years a lot of improvements were done in the field of Machine Learning and the Tools that support the community of developers. But still, implementing a recommender system is very hard.
That is why at Crossing Minds, we decided to create a series of 4 meetups to discuss how to implement a recommender system end-to-end:
Part 1 – The Right Dataset
Part 2 – Model Training
Part 3 – Model Evaluation
Part 4 – Real-Time Deployment
This first meetup will be about building the right dataset and doing all the preprocessing needed to create different models. We will talk about explicit vs implicit feedback, dataset analysis, likes/dislikes vs ratings, users and items features, normalization and similarities.
This document discusses reproducibility in R and tools provided by Revolution Analytics to improve reproducibility. It summarizes R's growing popularity, its use by major companies like Google and Facebook, and fields that use R like insurance, finance, agriculture, and more. It then discusses the importance of reproducible research and defines reproducibility. Finally, it outlines Revolution Analytics' reproducibility tools like Revolution R Open, a static CRAN mirror, daily CRAN snapshots, and the checkpoint package to ensure projects use consistent package versions.
The document discusses the NASA approach to prioritizing software verification and validation (IV&V) tasks. It describes the Software Integrity Level Assessment Process (SILAP) used to determine the risk level of software components and identify the appropriate set of IV&V tasks. SILAP involves assessing the consequence of potential defects and error potential of software based on factors like developer experience and complexity. The resulting risk scores map to specific IV&V tasks to establish confidence in software fitness for purpose.
The document discusses various software metrics that can be used to measure attributes of software products and processes. It describes metrics for size (e.g. lines of code), complexity (e.g. cyclomatic complexity), quality (e.g. defects per KLOC), design (e.g. coupling and cohesion), and object-oriented software (e.g. weighted methods per class). The goals of metrics include estimating costs, evaluating quality, and improving processes and products.
Simplifying effort estimation based on use case pointsAbdulrhman Shaheen
This document describes an experiment to evaluate methods for simplifying the use case points (UCP) software effort estimation technique while maintaining accuracy. The experiment analyzed 14 projects to test hypotheses around simplifying factors like actors, transactions vs steps, and technical/environmental factors. Results found that transactions outperformed steps, many factors had minor impact or overlapped and could be removed, and total steps or transactions could estimate effort nearly as well as UCP with simpler calculations. Threats to the study's validity were also addressed.
The document provides guidance for project tollgates at Tollgate Guiding Thoughts. Tollgates will focus on the 15 deliverable format and demonstrating the logical thought process through each project phase. Presentations should show work to complete a phase and tasks/dates for the next phase, and identify any barriers needing assistance. The primary tools listed are suggested but not mandatory ways to show project progression.
The document discusses metrics for evaluating the quality of software specifications. It defines key terms like measures, metrics, and indicators. It then provides examples of metrics that can measure the completeness, lack of ambiguity, and other qualities of a software specification. These include calculating the total number of requirements and the number that are unambiguous. The document also discusses using metrics in small organizations and provides an example where metrics are used to analyze efforts to reduce the time taken to implement change requests.
The document evaluates alternative methods to approximating historical value at risk (HsVaR) that can significantly reduce computational requirements compared to the full revaluation method, while maintaining acceptable accuracy. It considers a sample portfolio and calculates HsVaR using full revaluation and approximation methods involving delta, delta-gamma, and delta-gamma-theta. The results show the approximation methods produce HsVaR values close to full revaluation, within 1-18%, while requiring far fewer valuations, resulting in up to 99.6% reduction in computations. This demonstrates the tradeoff between accuracy and reduced processing from using approximation methods.
The document describes a new system being implemented to improve an executive appointment process. The current system has several problems, including being time-consuming and prone to errors. The new system is a web-based data entry app that allows information to be directly input and instantly accessible across departments. This is expected to increase efficiency, decrease frustration and errors, and reduce downtime and costs associated with the current system. The impact will be measured through surveys, analyzing downtime records, and comparing efficiency metrics like labor costs and number of steps per appointment before and after the new system. Diagrams depict the existing and modified appointment processes and a prototype of the new system is demonstrated.
The document discusses topics related to rapid software development and evolution, including agile methods, extreme programming, rapid application development, and software prototyping. It provides details on characteristics of rapid application development processes like concurrent specification, design, and implementation. Iterative development approaches are covered along with advantages and challenges. Specific agile methods like extreme programming, with practices like test-driven development and pair programming, are also summarized.
We have experience with testing projects, both large and small. Sometimes our test estimates are accurate—and sometimes they’re not. We often miss deadlines because there are no defined criteria used to create our estimates. Sometimes we miss our schedules due to crunched testing timelines. Shyam Sunder briefly describes the different test estimation techniques including Simple, Medium, Complex; Top Down, Bottom Up; and Test Point Analysis. To assist in better estimating in the future, Shyam has prepared test estimation templates and guidelines, which can significantly help organizations in proper estimation of testing projects. Through his work, effort and schedule variations have significantly improved from ±60 percent to ±2 percent. Shyam explains the test estimation templates in detail and demonstrates how to choose the estimation templates for your organization’s software development process. Learn why effective software test estimation techniques help in tracking and controlling cost/effort overruns significantly.
How do you know what to monitor in your environment? Failure modes have become so complex that we need a cross-functional view of the system to identify what failure looks like. This talks walks through the FMEA process as applied to monitoring and metrics collection. The process will help you identify your failure points and the risks associated with a particular failure mode.
PG&E's Distribution Resources Plan (DRP) evaluates the locational benefits and costs of distributed energy resources (DERs) on PG&E's distribution system. The plan analyzes over 102,000 distribution line sections across PG&E's service territory to determine each section's integration capacity for 10 different DER types. The analysis considers various power system criteria like thermal limits, voltage regulation, protection, and reliability. The DRP aims to identify optimal locations for DER deployment based on reductions in local grid upgrades and investments.
Performance doesn’t have the same definition between system administrators, developpers and business teams. What is Performance ? High CPU usage, not scalable web site, low business transaction rate per sec, slow response time, … This presentation is about maths, code performance, load testing, web performance, best practices, … Working on performance optimizaton is a very broad topic. It’s important to really understand main concepts and to have a clean and strong methodology because it could be a very time consumming activity. Happy reading !
Shyam Nagabandi has over 8 years of experience in software testing, including 4 years testing utilities systems. He has expertise in mainframe, web, and performance testing. Some of his skills include test planning, test case development, defect management, and experience with tools like HP LoadRunner and ALM. He has worked as a test lead on several projects for Southern California Edison.
This talk will review a number of application assessment techniques and discuss the types of security vulnerabilities they are best suited to identify as well as how the different approaches can be used in combination to produce more thorough and insightful results. Code review will be compared to penetration testing and the capabilities of automated tools will be compared to manual techniques. In addition, the role of threat modeling and architecture analysis will be examined. The goal is to illuminate assessment techniques that go beyond commodity point-and-click approaches to web application or code scanning.
From the OWASP Northern Virginia meeting August 6, 2009.
This document provides an overview of risk-adjusted estimating techniques for quantifying and accounting for uncertainty in project cost estimates. It discusses point estimating, uncertainty in estimates, and different types of risks including aleatory, systemic, and project-specific risks. It also covers quantifying uncertainty through qualitative analysis, quantitative analysis using historical data, and Monte Carlo simulation. The document emphasizes that simply adding individual estimates does not accurately capture total project uncertainty and risk, and that simulation methods are better for estimating overall program costs.
Similar to Determination of Repro Rates 20140724.pdf (20)
This document outlines a 4-day Python programming class covering basic Python, advanced Python, web scraping with Python, and building a web application with Python. On the fourth day, students will learn about CRUD operations, databases, and the ORM pattern. They will also learn to build an HTTP server, develop web applications with the Flask framework, access GPIO pins on the Raspberry Pi, and control an LCD display on the Raspberry Pi. As a final project, students will build a simple control center web application for the Raspberry Pi that accesses I/O using Flask and Python.
This document provides information about accessing and parsing web data using Python and BeautifulSoup. It discusses setting up a development environment on a Raspberry Pi with Python, Flask, and BeautifulSoup installed. It covers retrieving HTML data using urllib and parsing it using BeautifulSoup to extract tags and attributes. Common issues like HTTP errors and missing tags are addressed. Exercises demonstrate getting title data from a URL and extracting tags by class attribute.
This document outlines a 4-day Python Programming class taught by Paul Yang in 2016. The agenda covers basic Python on day 1, advanced Python on day 2, web scraping with Python on day 3, and web application development with Python on day 4. Day 1 of the class focuses on introducing Python, setting up the development environment, and covering basic Python concepts like data types, control flow, functions, and I/O. The class is intended to help students understand the history and features of Python, install Anaconda for package management, and get familiar with common data types, functions, and programming constructs in Python.
The document discusses various Python programming concepts including generator functions, list comprehensions, list processing features, and performance analysis using tools like timeit and memory_profiler. It provides examples of generator functions that produce sequences iteratively using yield instead of returning a list, and explores list comprehensions as a more concise way to create lists from expressions compared to traditional for loops. The document also demonstrates measuring the time and memory usage of functions to analyze performance differences between approaches.
The document provides an agenda for a hands-on training on RHEL5 Xen virtualization technology. It discusses key concepts of virtualization including types of Xen virtualization, performance, and supporting status in RHEL5. Labs cover installing guest systems via paravirtualization and full virtualization, configuring networks, and known issues workarounds. The training aims to introduce virtualization technology, the RHEL5 implementation, and provide hands-on experience through guided labs.
This document provides an overview and instructions for validating the Intel AT-d platform on Intel vPro systems. It describes the hardware and firmware prerequisites, how to enable AT-d in the BIOS and Management Engine, and how to perform validation tests. The validation process includes checking AT-d hardware and software straps, enabling AT-d, and verifying BIOS compliance. It also outlines the steps for assigning an administrator, managing users, and configuring devices for encryption with AT-d.
HP Performance Tracking is a set of tools used by HP to measure the performance of PCs against HP set limits. The tools are based on the Microsoft Windows Assessment Kit and concentrate on power up/down measurements. HP Performance Tracking includes a customized HP client, a SharePoint site for uploading results, a SQL database to store results, and a viewer to view and analyze the results. The client collects additional HP-specific data and measures performance against HP limits to identify failures. Results are uploaded to SharePoint and transferred nightly to the SQL database for analysis in the viewer.
The custom HP Perftrack client allows HP to:
- Include custom color coded HP performance limits to control when a service incident should be written.
- Zip up results for consistent reporting instead of screen captures, and capture additional system information.
- Add additional tests beyond what the Microsoft Assessment Kit includes, such as first logon command time.
- HP Perftrack uses the same underlying tests as the ADK but with a smaller footprint and customized tests and limits.
The document provides instructions for analyzing performance issues using the Windows Assessment and Deployment Kit (ADK). It outlines the process for setting up and running ADK tests, managing results, and debugging issues. Key steps include installing the Windows Assessment Console (WAC) to view XML results files and launch the Windows Performance Analyzer (WPA) to analyze detail trace files to identify causes of performance problems like prolonged fast boot shutdown times.
A Special-Purpose Peer-to-Peer File Sharing System for Mobile ad Hoc Networks...Paul Yang
1) The document describes ORION, a peer-to-peer file sharing system designed for mobile ad hoc networks. ORION uses an overlay network constructed on-demand to efficiently route search queries and file transfers.
2) ORION maintains routing tables to track responses to queries and paths for file transfers. It uses link layer feedback to detect and route around failures during transfers.
3) Simulation results show ORION significantly outperforms off-the-shelf P2P systems in search accuracy and reliability of file transfers in mobile ad hoc networks.
A brief study on bottlenecks to Intel vs. Acer v0.1.pdfPaul Yang
This document discusses potential bottlenecks in the relationship between Intel and Acer from both companies' perspectives. It outlines identifying problems, determining causes, potential options for mitigating issues, verifying effectiveness of options, and developing an action plan. Specifically, it examines messy distribution channels, endless price bargaining, and declining support from Intel partners. More data is needed to fully understand organizational changes, strategies, requirements, and value propositions from both sides.
This document discusses opportunities for Arm in data center and edge computing infrastructure. It outlines Arm's growing footprint in servers through partners like AWS, Ampere, Marvell, and provides an overview of the Neoverse roadmap. It also discusses how Arm can address markets like smartNICs and uCPE through integrated solutions with better performance and cost than x86.
Building PoC ready ODM Platforms with Arm SystemReady v5.2.pdfPaul Yang
The purpose of this technical talk with the demo is to show ODMs, OEMs, and ISVs how to leverage SystemReady Lab, showcase the use-case based on the virtualization platform for the edge, and deploy open-source tools that set up ODMs to develop their Arm platforms.
Mitigating routing misbehavior in mobile ad hoc networks Paul Yang
Mitigating Routing Misbehavior in Mobile Ad Hoc Networks”, Sergio Marti,T.J. Giuli, Kevin Lai, and Mary Baker,MobiCom 2000
Introduces two techniques that improve throughput in an ad hoc network in the presence of “misbehaving” nodes.
Towards Routing Security, Fairness, and Robustness in Mobile Ad Hoc Networks
From Birds to Network Nodes
Components in Each Node
Information Flow in Each Node
Information Flow Between Nodes
Routing Security and Authentication Mechanism for Mobile Ad Hoc NetworksPaul Yang
The document proposes a two-tier authentication mechanism for routing security in mobile ad hoc networks (MANETs). The first tier, called cluster authentication, uses message authentication codes and hash functions to verify if a node belongs to the same group and prevent external attacks. The second tier, called individual authentication, applies secret sharing to authenticate the identity of specific nodes and prevent internal attacks. Together, the two-tier mechanism provides security against both external and internal threats with reasonable computational complexity and bandwidth usage for MANETs.
English teaching in icebreaker and grammar analysisPaul Yang
The document discusses grammar analysis and ice breaker series. It provides an overview of the ice breaker series which aims to help students practice spoken English through scenario-based conversations. It also compares the present simple tense and present perfect tense through examples and explanations of when to use each. The differences between the past simple tense, past progressive tense, and past perfect tense are also outlined through examples to help understand them logically rather than through memorization.
Accident detection system project report.pdfKamal Acharya
The Rapid growth of technology and infrastructure has made our lives easier. The
advent of technology has also increased the traffic hazards and the road accidents take place
frequently which causes huge loss of life and property because of the poor emergency facilities.
Many lives could have been saved if emergency service could get accident information and
reach in time. Our project will provide an optimum solution to this draw back. A piezo electric
sensor can be used as a crash or rollover detector of the vehicle during and after a crash. With
signals from a piezo electric sensor, a severe accident can be recognized. According to this
project when a vehicle meets with an accident immediately piezo electric sensor will detect the
signal or if a car rolls over. Then with the help of GSM module and GPS module, the location
will be sent to the emergency contact. Then after conforming the location necessary action will
be taken. If the person meets with a small accident or if there is no serious threat to anyone’s
life, then the alert message can be terminated by the driver by a switch provided in order to
avoid wasting the valuable time of the medical rescue team.
Road construction is not as easy as it seems to be, it includes various steps and it starts with its designing and
structure including the traffic volume consideration. Then base layer is done by bulldozers and levelers and after
base surface coating has to be done. For giving road a smooth surface with flexibility, Asphalt concrete is used.
Asphalt requires an aggregate sub base material layer, and then a base layer to be put into first place. Asphalt road
construction is formulated to support the heavy traffic load and climatic conditions. It is 100% recyclable and
saving non renewable natural resources.
With the advancement of technology, Asphalt technology gives assurance about the good drainage system and with
skid resistance it can be used where safety is necessary such as outsidethe schools.
The largest use of Asphalt is for making asphalt concrete for road surfaces. It is widely used in airports around the
world due to the sturdiness and ability to be repaired quickly, it is widely used for runways dedicated to aircraft
landing and taking off. Asphalt is normally stored and transported at 150’C or 300’F temperature
Blood finder application project report (1).pdfKamal Acharya
Blood Finder is an emergency time app where a user can search for the blood banks as
well as the registered blood donors around Mumbai. This application also provide an
opportunity for the user of this application to become a registered donor for this user have
to enroll for the donor request from the application itself. If the admin wish to make user
a registered donor, with some of the formalities with the organization it can be done.
Specialization of this application is that the user will not have to register on sign-in for
searching the blood banks and blood donors it can be just done by installing the
application to the mobile.
The purpose of making this application is to save the user’s time for searching blood of
needed blood group during the time of the emergency.
This is an android application developed in Java and XML with the connectivity of
SQLite database. This application will provide most of basic functionality required for an
emergency time application. All the details of Blood banks and Blood donors are stored
in the database i.e. SQLite.
This application allowed the user to get all the information regarding blood banks and
blood donors such as Name, Number, Address, Blood Group, rather than searching it on
the different websites and wasting the precious time. This application is effective and
user friendly.
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELijaia
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Determination of Equivalent Circuit parameters and performance characteristic...pvpriya2
Includes the testing of induction motor to draw the circle diagram of induction motor with step wise procedure and calculation for the same. Also explains the working and application of Induction generator
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
2. Agenda
• Failure Rate Definition - General
• Failure Rate Definition – HP
• Severity assessment tool
• Design what to sample
• Severity resolution Flow
• Q & A
3. Failure Rate
Definition -
General
Wikipedia - Failure rate is The total
number of failures within an
item population, divided by the total time
expended by that population, during a
particular measurement interval under
stated conditions.
4. Failure Rate Definition - General
n Failure rate (HP)
(year-1)
¡ N = number of failures (-)
¡ Z = number of elements of the given type
in the network (-)
¡ P = the considered period (year)
P
Z
N
λ
×
=
5. Failure Rate Definition - HP
HP, we use the more sophisticated way - Issue
Severity / Priority to know about the issue status to
consider all the stakeholders’ interest and concern
•R&D (SEPM, Platform PM, PE, SCIT…etc)
•Supply Chain (SCPE, SCPM)
•TCE&Q
6. Failure Rate Definition - HP
issue severity is a index combining the several factors with different
weights in line with different party’s concerns.
ØImpact
ØFrequency of Occurrence
ØSegment
ØPercentage of Units Failed(DPPM)
ØPercentage of Cycles Failed(DPPM)
8. Design what to sample
• Choose the right sample manifest. Don’t compare something in the
different bases.
• Define or at least make a best guess of what dependent variables
contributes to it before making the manifest
• Sample the failure in specific Iteration, like 500 loops or in specific
time duration like 12 hours
• the clear cause-effects relationship is not just for debug, also for
reliable measurement.
9. Severity resolution Flow
Impact assessment to HP user
Failure rate exposure assessment
Impact assessment to HP biz (TCE&Q,
Supply Chain, RD)
Severity resolution