This tutorial provides you a step-by-step guide on how to create and manage your STPA safety analysis project in XSTAMPP tool support, edit the STPA project data, export it in different formats, save and delete.
www.xstampp.de
The document discusses how to edit causal factors and scenarios in an STPA project. It explains that the control structure diagram parts will appear in the first column of the causal factors table, and that causal factors can be written generally or individually for each unsafe control action. It also notes that the latest version of the software allows safety analysts to edit causal scenarios by checking or unchecking causal scenarios in the project settings menu.
This presentation discusses applying STPA (Systems-Theoretic Process Analysis) and formal verification techniques to software verification. It provides an overview of STPA and how it can be used to derive safety requirements and identify unsafe control actions. It also discusses formal specification and model checking methods that can be used to verify software meets STPA-derived requirements. The presentation demonstrates applying STPA to a train door controller example and generating an SMV model and LTL properties to model check in NuSMV. Finally, it discusses how STPA results can be used to generate safety-based test cases for software verification.
This document discusses three aspects of software evaluation: fit for purpose, use of computational constructs, and robustness. It evaluates whether the software meets client requirements and specifications, makes efficient use of constructs like loops and arrays, and can handle unexpected or incorrect input through testing a wide range of normal, exceptional, and extreme data values.
This document provides an overview of calibration, validation, and uncertainty analysis for environmental and hydrological modeling. It defines key concepts like calibration, validation, and uncertainty analysis. For calibration, it discusses finding parameter sets that minimize error between model outputs and observations while avoiding overfitting. Validation assesses model performance on new data. Uncertainty analysis quantifies uncertainty in model predictions. It also discusses sources of error and challenges in applying Bayesian methods due to non-normal errors and computational complexity. Simpler methods like GLUE (Generalized Likelihood Uncertainty Estimation) are also covered.
This tutorial provides you a step-by-step guide on how to create and manage your STPA safety analysis project in XSTAMPP tool support, edit the STPA project data, export it in different formats, save and delete.
www.xstampp.de
The document discusses how to edit causal factors and scenarios in an STPA project. It explains that the control structure diagram parts will appear in the first column of the causal factors table, and that causal factors can be written generally or individually for each unsafe control action. It also notes that the latest version of the software allows safety analysts to edit causal scenarios by checking or unchecking causal scenarios in the project settings menu.
This presentation discusses applying STPA (Systems-Theoretic Process Analysis) and formal verification techniques to software verification. It provides an overview of STPA and how it can be used to derive safety requirements and identify unsafe control actions. It also discusses formal specification and model checking methods that can be used to verify software meets STPA-derived requirements. The presentation demonstrates applying STPA to a train door controller example and generating an SMV model and LTL properties to model check in NuSMV. Finally, it discusses how STPA results can be used to generate safety-based test cases for software verification.
This document discusses three aspects of software evaluation: fit for purpose, use of computational constructs, and robustness. It evaluates whether the software meets client requirements and specifications, makes efficient use of constructs like loops and arrays, and can handle unexpected or incorrect input through testing a wide range of normal, exceptional, and extreme data values.
This document provides an overview of calibration, validation, and uncertainty analysis for environmental and hydrological modeling. It defines key concepts like calibration, validation, and uncertainty analysis. For calibration, it discusses finding parameter sets that minimize error between model outputs and observations while avoiding overfitting. Validation assesses model performance on new data. Uncertainty analysis quantifies uncertainty in model predictions. It also discusses sources of error and challenges in applying Bayesian methods due to non-normal errors and computational complexity. Simpler methods like GLUE (Generalized Likelihood Uncertainty Estimation) are also covered.
Model-based testing is an increasingly popular trend in the world of quality assurance. The aim of such an approach is to focus on a working system model and automatically generate test cases. However, how can it become useful in the work of a business or system analyst? The essence is in the model. It is called an executable specification. In this approach, it can take the form of code, gherkin syntax or UML graphs and diagrams. The latter is something that analysts use every day. In my presentation, I would therefore like to show how model-based testing can be used in the work of analysts. And how this approach can improve the work of the project team.
- A run chart is a line graph that displays observed data over time and can show how a process is running, revealing important early information before large amounts of data are collected, though it cannot determine process stability.
- Run charts can detect "special causes" or outliers if 3 or more consecutive points fall on one side of the center line, indicating something beyond normal variability is influencing the process.
- The document includes an example run chart tracking the number of test cases executed by individual employees in a week, with dots distinguishing test case complexity.
Test Status Reporting: Focus Your Message for ExecutivesTechWell
Test status reporting is a key factor in the success of test projects. Stephan Obbeck shares some ideas on how to communicate more than just a red-yellow-green status report to executive management and discusses how the right information can influence their decisions. Testers often create reports that are too technical, losing crucial information in a mountain of detailed data. Management needs to make decisions—based on data they do understand—that support the test project. Stephan explains how stakeholder and risk analysis helps you identify recipients of a report and what information is of interest to them. Learn different ways of presenting data to support your message and to get the most possible attention from the executive level. Discover how to avoid pitfalls when generating reports from test automation. Produce a summary of statistics that provides insight into a test project.
A simulation is a representation of a system that can be manipulated to study the system's behavior. A model is created that portrays the key aspects of the system. The model's operation provides insights into the actual system. Simulations can be continuous, discrete, or combined. They are used to predict outcomes, understand processes, identify issues, evaluate alternatives, and gain insights without experimenting on the real system, which may be impossible, too expensive, or impractical.
Requirements and diagrams are important for project completion. Requirements include functional requirements of what the system should do and non-functional requirements like performance. Use case diagrams show how users will interact with the system through 5-10 use cases per diagram and should cover the requirements. Activity diagrams show the flow of the system from start to end through steps, decisions, and messages.
This document describes the methodology for a timetable management system project using the Analytic Hierarchy Process technique. It discusses rapid prototyping, AHP concepts, algorithms, and provides context, data flow, and entity relationship diagrams. Prototypes of the homepage, admin, lecturer, and student homepages are also included.
Visual Programming Lectures using Visual Studio 2015 C# Windows Form Application
Lecturer: Saman M. Almufti / Kurdistan Region, Nawroz University
facebook: https://www.facebook.com/saman.malmufti
Science has proven that the human mind recalls information best when the information is in a graphical format.
http://www.hoquality.com/software/fmea-innovator.php
This document discusses verification and validation of simulation models. It presents four approaches to determining model validity: 1) the model development team decides validity, 2) users are heavily involved in deciding validity, 3) an independent third party decides validity through independent verification and validation (IV&V), and 4) using a scoring model. It also presents two paradigms relating verification and validation to the modeling process - a simple view and a more complex view. Key aspects of validation discussed include conceptual model validity, model verification, operational validity, and data validity. A recommended validation procedure and brief discussion of accreditation are also provided.
Cross validation is a method to estimate the true error of a model by building models from subsets of the training data and testing them on the remaining subsets. It provides a better estimate of how the model will generalize to new, unseen data compared to just using the error on the training data. Cross validation can also help evaluate which learning algorithm or parameters work best. Nested sub-processes in RapidMiner allow operators to contain additional processes that can be viewed by double clicking the operator icon.
This document provides an introduction to LabVIEW, a graphical programming environment for data acquisition, analysis, and instrument control. It outlines some key features of LabVIEW including design, control, and measurement capabilities. It then demonstrates creating a simple virtual instrument in LabVIEW with input and output controls, and describes how to fix mistakes like using the wrong control type. Finally, it shows how to perform basic math operations in LabVIEW using addition and multiplication blocks, as well as numeric constants.
IBM SPSS allows users to customize existing toolbars and create new toolbars. Toolbars can contain tools for menu actions and custom tools to launch other applications or run syntax/script files. To customize a toolbar, users select the toolbar in the Show Toolbars dialog box and click Edit to add, remove, or arrange tools by dragging them. Custom tools can be created to open files or run commands by selecting the action and associated file. More tips are available online at the provided link.
This document provides instructions for counting the occurrences of values within variables in an IBM SPSS dataset. It demonstrates counting the number of "Strongly Positive" responses across six satisfaction survey questions to calculate a total for each respondent. The steps shown include using the "Transform > Count Values within cases" procedure to create a new variable called "Count_Strongly_Positive" that contains the count. It also notes that cases can be conditionally selected for counting using an "If cases" dialog box.
This document provides instructions for making graphs transparent in IBM SPSS Statistics. It explains that by default, SPSS charts have a gray chart area and white background. It then describes how to make the chart area or entire graph transparent by selecting the data frame or outer frame and choosing the transparent color option. This allows graphs to fit better into PowerPoint presentations. The document concludes by advising readers to copy transparent graphs from SPSS as metafiles and paste them into PowerPoint using Paste Special.
Manual testing is still important for certain types of testing like unit testing, system testing, regression testing, and user acceptance testing. It is performed by professional testers, subject matter experts, business analysts, and end-users. While manual testing is slow, automation can provide faster feedback, consistency, empower testers, and increase confidence through documentation. However, test automation requires extensive upfront time and maintenance. The best approach is to use manual testing to develop test assets like requirements, risk assessments, and defect records that can then be used to develop automated test cases. This hybrid approach allows organizations to take advantage of both manual and automated testing.
This document discusses nonlinear curve fitting in Matlab. It describes how the Curve Fitting Toolbox uses nonlinear least squares to fit nonlinear models to data, such as Gaussians, ratios of polynomials, and power functions. The process of fitting a surface to data involves opening the fitting tool, selecting and importing data, refining the fit, removing outliers, selecting validation data, and exploring and customizing plots. Different fits can be applied and viewed in the residuals plot to analyze the quality of the fit. More tutorials on nonlinear methods can be found on the provided website.
This document provides instructions on how to prepare a flow chart. It explains that a flow chart is a graphical representation of a process that uses symbols to show the steps in a process or solution to a problem. It discusses the main symbols used in flow charts, including their meanings and usages. The document also covers the advantages of using flow charts, such as better communication of logic and aiding in problem analysis, and limitations, such as complexity and reproduction issues. Sources for creating flow charts using software and mobile apps are also provided.
Yates’ algorithm for 2n factorial experiment - Dr. Manu Melwin Joy - School o...manumelwin
In statistics, a Yates analysis is an approach to analyzing data obtained from a designed experiment, where a factorial design has been used. This algorithm was named after the English statistician Frank Yates and is called Yates' algorithm.
The document provides a tutorial on how to query contoured results from a finite element analysis using the HV-4000 software. It describes how to:
1) Load a model file and results file, contour the model for von Mises stresses, and animate the results
2) Access the Query panel to view element properties and contour values for selected elements
3) Change the averaging method to simple, re-query to view nodal contour values, and export the query results to a CSV file for further analysis.
This presentation provided an overview of Ishikawa's seven basic quality tools: histograms, Pareto charts, cause-and-effect diagrams, run charts, scatter diagrams, flow charts, and control charts. For each tool, the presentation defined the tool, explained how to construct it, and provided an example of how the tool can be used. The tools are designed to be simple visual aids to help analyze data, identify relationships and causes, improve processes, and monitor quality.
Seven Quality Tools - Presentation Material Sample 1.pptssusere6db8e
This presentation provided an overview of Ishikawa's seven basic quality tools: histograms, Pareto charts, cause-and-effect diagrams, run charts, scatter diagrams, flow charts, and control charts. For each tool, the presentation defined the tool, explained how to construct it, and provided an example of how the tool can be used. The tools are designed to be simple visual aids to help analyze data, identify relationships and causes, improve processes, and monitor quality.
Model-based testing is an increasingly popular trend in the world of quality assurance. The aim of such an approach is to focus on a working system model and automatically generate test cases. However, how can it become useful in the work of a business or system analyst? The essence is in the model. It is called an executable specification. In this approach, it can take the form of code, gherkin syntax or UML graphs and diagrams. The latter is something that analysts use every day. In my presentation, I would therefore like to show how model-based testing can be used in the work of analysts. And how this approach can improve the work of the project team.
- A run chart is a line graph that displays observed data over time and can show how a process is running, revealing important early information before large amounts of data are collected, though it cannot determine process stability.
- Run charts can detect "special causes" or outliers if 3 or more consecutive points fall on one side of the center line, indicating something beyond normal variability is influencing the process.
- The document includes an example run chart tracking the number of test cases executed by individual employees in a week, with dots distinguishing test case complexity.
Test Status Reporting: Focus Your Message for ExecutivesTechWell
Test status reporting is a key factor in the success of test projects. Stephan Obbeck shares some ideas on how to communicate more than just a red-yellow-green status report to executive management and discusses how the right information can influence their decisions. Testers often create reports that are too technical, losing crucial information in a mountain of detailed data. Management needs to make decisions—based on data they do understand—that support the test project. Stephan explains how stakeholder and risk analysis helps you identify recipients of a report and what information is of interest to them. Learn different ways of presenting data to support your message and to get the most possible attention from the executive level. Discover how to avoid pitfalls when generating reports from test automation. Produce a summary of statistics that provides insight into a test project.
A simulation is a representation of a system that can be manipulated to study the system's behavior. A model is created that portrays the key aspects of the system. The model's operation provides insights into the actual system. Simulations can be continuous, discrete, or combined. They are used to predict outcomes, understand processes, identify issues, evaluate alternatives, and gain insights without experimenting on the real system, which may be impossible, too expensive, or impractical.
Requirements and diagrams are important for project completion. Requirements include functional requirements of what the system should do and non-functional requirements like performance. Use case diagrams show how users will interact with the system through 5-10 use cases per diagram and should cover the requirements. Activity diagrams show the flow of the system from start to end through steps, decisions, and messages.
This document describes the methodology for a timetable management system project using the Analytic Hierarchy Process technique. It discusses rapid prototyping, AHP concepts, algorithms, and provides context, data flow, and entity relationship diagrams. Prototypes of the homepage, admin, lecturer, and student homepages are also included.
Visual Programming Lectures using Visual Studio 2015 C# Windows Form Application
Lecturer: Saman M. Almufti / Kurdistan Region, Nawroz University
facebook: https://www.facebook.com/saman.malmufti
Science has proven that the human mind recalls information best when the information is in a graphical format.
http://www.hoquality.com/software/fmea-innovator.php
This document discusses verification and validation of simulation models. It presents four approaches to determining model validity: 1) the model development team decides validity, 2) users are heavily involved in deciding validity, 3) an independent third party decides validity through independent verification and validation (IV&V), and 4) using a scoring model. It also presents two paradigms relating verification and validation to the modeling process - a simple view and a more complex view. Key aspects of validation discussed include conceptual model validity, model verification, operational validity, and data validity. A recommended validation procedure and brief discussion of accreditation are also provided.
Cross validation is a method to estimate the true error of a model by building models from subsets of the training data and testing them on the remaining subsets. It provides a better estimate of how the model will generalize to new, unseen data compared to just using the error on the training data. Cross validation can also help evaluate which learning algorithm or parameters work best. Nested sub-processes in RapidMiner allow operators to contain additional processes that can be viewed by double clicking the operator icon.
This document provides an introduction to LabVIEW, a graphical programming environment for data acquisition, analysis, and instrument control. It outlines some key features of LabVIEW including design, control, and measurement capabilities. It then demonstrates creating a simple virtual instrument in LabVIEW with input and output controls, and describes how to fix mistakes like using the wrong control type. Finally, it shows how to perform basic math operations in LabVIEW using addition and multiplication blocks, as well as numeric constants.
IBM SPSS allows users to customize existing toolbars and create new toolbars. Toolbars can contain tools for menu actions and custom tools to launch other applications or run syntax/script files. To customize a toolbar, users select the toolbar in the Show Toolbars dialog box and click Edit to add, remove, or arrange tools by dragging them. Custom tools can be created to open files or run commands by selecting the action and associated file. More tips are available online at the provided link.
This document provides instructions for counting the occurrences of values within variables in an IBM SPSS dataset. It demonstrates counting the number of "Strongly Positive" responses across six satisfaction survey questions to calculate a total for each respondent. The steps shown include using the "Transform > Count Values within cases" procedure to create a new variable called "Count_Strongly_Positive" that contains the count. It also notes that cases can be conditionally selected for counting using an "If cases" dialog box.
This document provides instructions for making graphs transparent in IBM SPSS Statistics. It explains that by default, SPSS charts have a gray chart area and white background. It then describes how to make the chart area or entire graph transparent by selecting the data frame or outer frame and choosing the transparent color option. This allows graphs to fit better into PowerPoint presentations. The document concludes by advising readers to copy transparent graphs from SPSS as metafiles and paste them into PowerPoint using Paste Special.
Manual testing is still important for certain types of testing like unit testing, system testing, regression testing, and user acceptance testing. It is performed by professional testers, subject matter experts, business analysts, and end-users. While manual testing is slow, automation can provide faster feedback, consistency, empower testers, and increase confidence through documentation. However, test automation requires extensive upfront time and maintenance. The best approach is to use manual testing to develop test assets like requirements, risk assessments, and defect records that can then be used to develop automated test cases. This hybrid approach allows organizations to take advantage of both manual and automated testing.
This document discusses nonlinear curve fitting in Matlab. It describes how the Curve Fitting Toolbox uses nonlinear least squares to fit nonlinear models to data, such as Gaussians, ratios of polynomials, and power functions. The process of fitting a surface to data involves opening the fitting tool, selecting and importing data, refining the fit, removing outliers, selecting validation data, and exploring and customizing plots. Different fits can be applied and viewed in the residuals plot to analyze the quality of the fit. More tutorials on nonlinear methods can be found on the provided website.
This document provides instructions on how to prepare a flow chart. It explains that a flow chart is a graphical representation of a process that uses symbols to show the steps in a process or solution to a problem. It discusses the main symbols used in flow charts, including their meanings and usages. The document also covers the advantages of using flow charts, such as better communication of logic and aiding in problem analysis, and limitations, such as complexity and reproduction issues. Sources for creating flow charts using software and mobile apps are also provided.
Yates’ algorithm for 2n factorial experiment - Dr. Manu Melwin Joy - School o...manumelwin
In statistics, a Yates analysis is an approach to analyzing data obtained from a designed experiment, where a factorial design has been used. This algorithm was named after the English statistician Frank Yates and is called Yates' algorithm.
The document provides a tutorial on how to query contoured results from a finite element analysis using the HV-4000 software. It describes how to:
1) Load a model file and results file, contour the model for von Mises stresses, and animate the results
2) Access the Query panel to view element properties and contour values for selected elements
3) Change the averaging method to simple, re-query to view nodal contour values, and export the query results to a CSV file for further analysis.
This presentation provided an overview of Ishikawa's seven basic quality tools: histograms, Pareto charts, cause-and-effect diagrams, run charts, scatter diagrams, flow charts, and control charts. For each tool, the presentation defined the tool, explained how to construct it, and provided an example of how the tool can be used. The tools are designed to be simple visual aids to help analyze data, identify relationships and causes, improve processes, and monitor quality.
Seven Quality Tools - Presentation Material Sample 1.pptssusere6db8e
This presentation provided an overview of Ishikawa's seven basic quality tools: histograms, Pareto charts, cause-and-effect diagrams, run charts, scatter diagrams, flow charts, and control charts. For each tool, the presentation defined the tool, explained how to construct it, and provided an example of how the tool can be used. The tools are designed to be simple visual aids to help analyze data, identify relationships and causes, improve processes, and monitor quality.
Seven quality-tools-1233776598291857-2Mahmood Alam
This presentation provided learning material on Ishikawa's seven basic quality tools: histograms, Pareto charts, cause-and-effect diagrams, run charts, scatter diagrams, flow charts, and control charts. For each tool, definitions were given along with step-by-step processes for constructing them and examples of how each could be used. The tools were shown to be rather simple and effective for analyzing and interpreting data to identify and solve quality-related problems.
From this power point you can get the details about Advanced Filter, Use of Macros with Advanced Filter, Data Validation, Creation of data validation Drop-Down List, Handling of External Data, Goal Seek, What-if analysis,
failure modes and effects analysis (fmea)palanivendhan
This document outlines the steps for conducting a Failure Modes and Effects Analysis (FMEA). An FMEA is a systematic process for identifying potential failures in a design, manufacturing process, or product. The key steps include: describing the product or process, creating a block diagram, identifying potential failure modes and their causes and effects, assigning severity, occurrence, and detection ratings, calculating a risk priority number, and determining recommended actions to address high-risk failures. The overall goal of an FMEA is to improve reliability and quality by being proactive in evaluating and preventing potential failures.
The document provides an overview of quality tools and concepts. It defines quality, processes, systems, variation and different quality tools including flowcharts, histograms, Pareto charts, scatter plots, control charts. It explains how to create and interpret these tools. Control charts are discussed in more detail with examples of mean and range control charts showing how to establish control limits and monitor process performance over time. The document serves as an introduction to statistical process control tools for quality improvement.
Aliaa delivered a session in the topic of “Test planning” using a new technique of delivering content through games and knowledge sharing instead of instructive technique. The session covered all test planning activities including defining test items, risk assessment techniques, testing strategies, planning for testing resources, testing scheduling, and test deliverables and the final test plan documents.
The session introduced to quality team at ITWorx (June , 2013)
The 7 basic quality tools through minitab 18RAMAR BOSE
The document provides an overview of creating and customizing control charts in Minitab. It explains how to create an I-MR chart and Xbar-R chart from sample data files, including how to select test criteria, format scales and axes, and add reference lines. The document also provides general information about when to use control charts and considerations for the type of data needed to create these charts.
The document discusses various software testing strategies and techniques. It begins by explaining the importance of testing software before customers use it in order to reduce errors. It then describes different testing techniques including white-box testing, which tests the internal logic and paths of a program, and black-box testing, which tests the inputs and outputs against requirements without considering internal logic. The document provides examples of specific strategies like branch coverage, basis path testing, and boundary value analysis. It also discusses test case documentation and different testing phases from unit to integration to system testing.
T Jull - Product Development for Point-of-Care Testing SystemsThomas Jull
The document provides tips for developing point-of-care testing systems which have two main components: a test kit or consumable and an instrument. It recommends developing the two components in parallel while keeping designs flexible, having a risk management plan, and starting with a "soft launch" version 1 product to gather feedback before releasing a final version 2. The key challenges are that small changes to the consumable often require instrument changes, and developing the components simultaneously can result in redesigns throughout the process.
The document discusses HP Quality Center, a test management tool. It covers the different modules in HP Quality Center including Release Management, Test Plan, Test Lab, and Defect Management. The document provides information on setting up releases and cycles in the Release Management module, designing test plans and test cases in the Test Plan module, creating and executing test sets in the Test Lab module, and tracking defects in the Defect Management module. It also discusses linking requirements to tests and generating reports.
Blockly for PICAXE is a visual programming tool that allows users to generate programs for PICAXE microcontrollers by dragging and dropping colored blocks. It can be used online, within the PICAXE Editor software, or as a standalone Chrome app. The document provides an overview of Blockly and instructions for building, testing, and downloading programs to a PICAXE microcontroller.
This document provides an overview of statistical process control (SPC) tools and techniques. It discusses prevention versus detection approaches and compares mistake-proofing, 100% inspection, and SPC. SPC is described as the most economical option. Key aspects of SPC covered include common versus special causes of variation, control charts, process stability, capability, and over-adjustment. Guidelines are provided for identifying assignable causes using cause analysis tables and a why-why analysis. The goal of SPC is to have a predictable process free from assignable causes and with a capable level of inherent variation.
For more classes visit
www.snaptutorial.com
Project 1
Step 1: Conduct a Security Analysis Baseline
In the first step of the project, you will conduct a security analysis baseline of the IT systems, which will include a data-flow diagram of connections and endpoints, and all types of access points, including wireless. The baseline report will be part of the overall security assessment report (SAR).
You will get your information from a data-flow diagram and report from the Microsoft Threat Modeling Tool
Programming aids- Algorithm, Flowchart, Pseudocodes and Decision tableAnjali Technosoft
The document discusses algorithms and different ways to represent them, including through flowcharts, pseudocode, and decision tables. It provides examples of each representation type and explains the key components and steps in constructing a flowchart, pseudocode, and decision table to model an algorithm for determining a student's final grade.
FOR MORE CLASSES VISIT
www.cst630rank.com
Project 1 Step 1: Conduct a Security Analysis Baseline In the first step of the project, you will conduct a security analysis baseline of the IT systems, which will include a data-flow diagram of connections and endpoints, and all types of access points, including wireless. The baseline report will be part of the overall security assessment report (SAR). You
This document outlines the steps for a security assessment report (SAR) project. It involves conducting a security baseline analysis, determining a network defense strategy through testing plans, planning a penetration test with rules of engagement, performing the penetration test using tools to find vulnerabilities, and compiling the SAR with an executive briefing. Key activities include creating a network diagram, assessing security requirements, typical attacks, infrastructure security, conducting black box testing to find security issues and NIST control violations, and providing remediation suggestions. A risk management cost-benefit analysis is also required. The project utilizes a virtual lab workspace to analyze pre-captured wireless traffic.
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Control
Actions TableControl Actions Table
• When you dragged and dropped a control action into the control
structure diagram, XSTAMPP will automatically save them into the
control actions table with information of source and destination
components.
You can here add a description of each
control action
3. Unsafe
control
actions Table
Unsafe Control Actions Table
• The control actions will also be appeared in the first column of the
unsafe control actions.
• Each control action should be evaluated within four hazardous types:
• Not Providing causes hazard
• Providing causes hazard
• Wrong timing or order causes hazards
• Stopped too soon or Applied too long
• If an item in the table is hazardous, then you have to assign which
hazards from the hazards table can cause this unsafe control actions,
otherwise, it will be considered as not hazardous
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4. Unsafe
control
actions Table
Editing Unsafe Control Actions
• You can edit an unsafe control action by clicking on the add button
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• To link hazard to the unsafe control action, click on the button and select from the
context menu a hazard. The code number of the UCA will be appeared.
You can choose from here a hazard.
To add more hazards, you have to click on the link
button again
5. Unsafe
control
actions Table
Delete an Unsafe Control Action
• You can delete an unsafe control action by clicking on the button
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• You have to confirm the deleting command by clicking on OK button, then all
information of this unsafe control action will be deleted
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Create a new
STPA project
Searching for An Unsafe Control Action
• You can search for an unsafe control action by using different search
filters such as control action, or unsafe control action or the UCD
ID.
• You have to type the text in the search text box e.g. Accelerate
7. University of Stuttgart
Exporting
Unsafe
Control Actio
Table
Exporting the unsafe Control Actions Table
• You can export the control action table as image or CSV sheet or
PDF by click on the Export button in main toolbar.
• Next, you have to select the type of exporting: STPA DATA Sheets,
or Images or PDF. Then click on Next button.
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Exporting
Unsafe
Control
Actions Table
Exporting Unsafe Control Action Table as
an CVS Sheet
• As default, the name of current project will be appeared at the top
of the list.
• Then, you have to select the type of separators of CVS sheets and
location of exporting the file.
Choose the project name which you want to export its data
Choose one type of separators of CVS sheets
Choose the destination path to export the data in.
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An IssueAn Issue in Editing of Unsafe Control Actions
Table
• In the version of Mac OS X, some of users faced a problem when
they typed a text in a cell of the table, then the text will not save it.
• This issue did not appear on Windows or Linux.
• Solution:
• You have to type your text and does not move the mouse over
the current cell or the unsafe control action table. Then, press
Enter button to save the content.
• You can also contact with me if you need more information
10. Thank you!
e-mail
phone +49 (0) 711 685-
fax +49 (0) 711 685-
Universität Stuttgart
Asim Abdulkhaleq, Ph.D Candidate
88 458
88 380
Institute of Software Technology, Software Engineering Group
asim.abdulkhaleq@informatik.uni-stuttgart.de
The slides will be also available at the website www.xstampp.de