The document discusses software FMEA (Failure Mode and Effects Analysis) and FTA (Fault Tree Analysis) as effective tools for embedded software quality assurance. Software FTA involves identifying potential failures and their causes by logically connecting software components to undesired events. Software FMEA examines failures at the functional and variable levels. The analyses help identify weaknesses, critical variables, and protections needed. The results provide inputs for testing and help reduce risks for safety-critical systems.
This document provides an overview and introduction to a presentation on Software Failure Modes Effects Analysis (SFMEA). It discusses copyright restrictions on use of the presentation materials. It then provides brief biographies of the presenter Ann Marie Neufelder, who has extensive experience applying SFMEAs. The document outlines some common pitfalls to avoid in conducting SFMEAs and lists some example software failure modes and historical cases where failures occurred.
The software Common Defect Enumeration is a means to categorize the root causes of software defects that originate in the specifications, design, interfaces. Early defect enumerations focused on coding related issues.
We have analyzed almost 1 million software failures and less than half originate in the coding activity. Mitre's Common Weakness Enumeration provides for standardization and organization of vulnerabilities as well as a means to update that enumeration with new vulnerabilities. This CDE provides for the same goals except that it focuses on software defects.
The enumeration is categorized by the architectural level, type of failure and where it originates. Some defects apply to the entire software system. Peak loading related defects for example tend to apply to the whole application. Some defects apply at a capability or feature level. Sometimes the features may be inconsistent with each other or executed out of order. Some defects originate in a single specification. Some defects originate in the interfaces between the software/hardware.
The types of failure modes include faulty functionality, faulty error handlings, faulty state management, faulty sequencing, faulty timing, faulty data definition, faulty processing, faulty machine learning, faulty logic and faulty I/O.
The origination of the defect is either in the specifications (the whats), the design (the hows) or the coding. The defect is attributed to specification if the whats aren't fully identified, are ambiguous, conflicting, over engineered or underengineered. The defect is attributed to design if the software engineer knows what to develop but didn't consider the state design, data design, logic design, timing design, fault management design considerations prior to coding. A defect originates in coding if the software engineer knows what to code and how to code it but the code doesn't work correctly.
The CDE has descriptions of each defect, examples, how to mitigate them. It can be used during a requirements or design review and it can be used for software failure modes effects analysis and software fault tree analysis.
Software Failure Modes Effects Analysis is a method of identifying what can go wrong with the software. Software testing generally focuses on the positive test cases. The SFMEA focuses on analyzing what can go wrong.
An Introduction to Software Failure Modes Effects Analysis (SFMEA)Ann Marie Neufelder
Software Failure Modes Effects Analysis (SFMEA) is an effective tool for identifying what software applications should NOT do. Software testing is often focused on nominal conditions and often doesn't discover serious defects.
Five Common Mistakes made when Conducting a Software FMECAAnn Marie Neufelder
The software FMECA is a powerful tool for identifying software failure modes but there are 5 common mistakes that can derail the effectiveness of the analysis.
The document outlines the purpose and methodology for conducting a Design Failure Mode Effects Analysis (DFMEA). The goals of a DFMEA are to define the design process, identify and reduce design risks, provide traceability, and enable continuous improvement. It is a team activity that identifies potential failure modes, their causes and effects. Through assigning severity, occurrence, and detection ratings, the DFMEA calculates risk priority numbers to guide focus on high risk design issues. It produces outputs to reduce risk and meet customer requirements.
This document provides guidance on conducting a Design Failure Mode and Effects Analysis (DFMEA). It begins with defining the purpose of a FMEA and what it involves. It then discusses current DFMEA practices and concerns. The remainder of the document offers detailed instructions on performing a DFMEA, including how to construct a process flow diagram, interface matrix, evaluate potential failure modes and their effects/severity, occurrence, detection, and risk priority numbers. It provides examples and criteria for properly analyzing risk and prioritizing corrective actions. The overall summary is that the document aims to refine the approach to DFMEAs by outlining the full process and key considerations for effectively conducting a thorough design risk assessment.
This document provides an overview and introduction to a presentation on Software Failure Modes Effects Analysis (SFMEA). It discusses copyright restrictions on use of the presentation materials. It then provides brief biographies of the presenter Ann Marie Neufelder, who has extensive experience applying SFMEAs. The document outlines some common pitfalls to avoid in conducting SFMEAs and lists some example software failure modes and historical cases where failures occurred.
The software Common Defect Enumeration is a means to categorize the root causes of software defects that originate in the specifications, design, interfaces. Early defect enumerations focused on coding related issues.
We have analyzed almost 1 million software failures and less than half originate in the coding activity. Mitre's Common Weakness Enumeration provides for standardization and organization of vulnerabilities as well as a means to update that enumeration with new vulnerabilities. This CDE provides for the same goals except that it focuses on software defects.
The enumeration is categorized by the architectural level, type of failure and where it originates. Some defects apply to the entire software system. Peak loading related defects for example tend to apply to the whole application. Some defects apply at a capability or feature level. Sometimes the features may be inconsistent with each other or executed out of order. Some defects originate in a single specification. Some defects originate in the interfaces between the software/hardware.
The types of failure modes include faulty functionality, faulty error handlings, faulty state management, faulty sequencing, faulty timing, faulty data definition, faulty processing, faulty machine learning, faulty logic and faulty I/O.
The origination of the defect is either in the specifications (the whats), the design (the hows) or the coding. The defect is attributed to specification if the whats aren't fully identified, are ambiguous, conflicting, over engineered or underengineered. The defect is attributed to design if the software engineer knows what to develop but didn't consider the state design, data design, logic design, timing design, fault management design considerations prior to coding. A defect originates in coding if the software engineer knows what to code and how to code it but the code doesn't work correctly.
The CDE has descriptions of each defect, examples, how to mitigate them. It can be used during a requirements or design review and it can be used for software failure modes effects analysis and software fault tree analysis.
Software Failure Modes Effects Analysis is a method of identifying what can go wrong with the software. Software testing generally focuses on the positive test cases. The SFMEA focuses on analyzing what can go wrong.
An Introduction to Software Failure Modes Effects Analysis (SFMEA)Ann Marie Neufelder
Software Failure Modes Effects Analysis (SFMEA) is an effective tool for identifying what software applications should NOT do. Software testing is often focused on nominal conditions and often doesn't discover serious defects.
Five Common Mistakes made when Conducting a Software FMECAAnn Marie Neufelder
The software FMECA is a powerful tool for identifying software failure modes but there are 5 common mistakes that can derail the effectiveness of the analysis.
The document outlines the purpose and methodology for conducting a Design Failure Mode Effects Analysis (DFMEA). The goals of a DFMEA are to define the design process, identify and reduce design risks, provide traceability, and enable continuous improvement. It is a team activity that identifies potential failure modes, their causes and effects. Through assigning severity, occurrence, and detection ratings, the DFMEA calculates risk priority numbers to guide focus on high risk design issues. It produces outputs to reduce risk and meet customer requirements.
This document provides guidance on conducting a Design Failure Mode and Effects Analysis (DFMEA). It begins with defining the purpose of a FMEA and what it involves. It then discusses current DFMEA practices and concerns. The remainder of the document offers detailed instructions on performing a DFMEA, including how to construct a process flow diagram, interface matrix, evaluate potential failure modes and their effects/severity, occurrence, detection, and risk priority numbers. It provides examples and criteria for properly analyzing risk and prioritizing corrective actions. The overall summary is that the document aims to refine the approach to DFMEAs by outlining the full process and key considerations for effectively conducting a thorough design risk assessment.
ISO26262-6 Software development process (Ver 3.0)Hongseok Lee
ISO26262-6 Software Development Process in the automotive domain. Planning(Coding Guideline. MISRA guideline), Requirement, Design, Safety Analysis, Testing
The Top Ten things that have been proven to effect software reliabilityAnn Marie Neufelder
Ann Marie Neufelder has benchmarked over 150 software organizations and 523 development factors against actual defect data from 79 projects to determine the key factors that influence software reliability. The top factors associated with more defects include large projects, short term contractors without domain expertise, and a "throw over the wall" testing approach. All failed projects in the database started late and had more than three new elements like hardware, tools, processes or people. The findings were used to develop a model to predict defect density before coding begins.
Revised IEEE 1633 Recommended Practices for Software ReliabilityAnn Marie Neufelder
The IEEE 1633 document provides guidance on applying software reliability engineering practices during development. It outlines key tasks such as determining system reliability objectives, performing early software reliability predictions, integrating predictions into overall system models, determining total reliability needed from software, and planning reliability growth. The document aims to help reliability engineers and software engineers collaborate to establish objectives and metrics for individual software components.
Software Testing: History, Trends, Perspectives - a Brief OverviewSoftheme
In this presentation you can learn about different types of software testing, new technologies and methodologies. It contains an overview of software testing perspectives.
You can predict software reliability before the code is even finished. Predictions support planning, sensitivity analysis and also help to avoid distressed software projects and defect pile up.
The document describes different software development process models including the waterfall model, prototyping model, incremental development, spiral development, agile methods, and extreme programming. It explains each model and compares their advantages and disadvantages. The waterfall model is most appropriate when requirements are stable while agile methods are best for changing requirements but can be difficult to manage.
The document provides an overview of failure mode and effects analysis (FMEA). It discusses the history and evolution of FMEA from its origins in the aerospace industry in the 1960s to the current AIAG VDA FMEA Handbook published in 2019. The document outlines the seven step approach of the new handbook, including planning, structure analysis, function analysis, optimization, risk analysis, failure analysis, and documentation of results. It also summarizes some of the major changes between the previous AIAG 4th edition and new handbook, such as replacing RPN with action priority and revising the rating tables.
This document provides an overview of ISO 26262 and functional safety standards. It discusses key aspects of ISO 26262 including its structure, vocabulary, safety lifecycle, roles and responsibilities, and requirements for managing functional safety. ISO 26262 adapts IEC 61508 for automotive and aims to avoid faults and control failures through technical safety measures applied throughout the product lifecycle from concept to decommissioning. Management of functional safety is required to plan, coordinate, and track all safety activities.
This document summarizes a webinar on Failure Mode and Effects Analysis (FMEA) and risk management. The webinar will cover the history and scope of FMEA, different types of FMEA, hazard analysis and risk assessment, FMEA methodology including calculating a Risk Priority Number, and include a live demonstration. It will be presented by Adela Béres, a functional safety expert with over 10 years of experience, and be available on Intland Software's website. Intland focuses on automotive development and helping customers comply with ISO 26262 functional safety standards.
Failure mode and effects analysis (FMEA)—also "failure modes", plural, in many publications—was one of the first highly structured, systematic techniques for failure analysis. It was developed by reliability engineers in the late 1950s to study problems that might arise from malfunctions of military systems. An FMEA is often the first step of a system reliability study. It involves reviewing as many components, assemblies, and subsystems as possible to identify failure modes, and their causes and effects. For each component, the failure modes and their resulting effects on the rest of the system are recorded in a specific FMEA worksheet. There are numerous variations of such worksheets. An FMEA can be a qualitative analysis.
SIA Journée d'étude : NORME ISO 26262 Sécurité fonctionnelle électronique automobile , 04-03-2018
Cédric Heller, DQI/DSEE, French Delegate of TC22/SC32/WG8
Find out about the requirement for ISO 26262 unit testing for car item improvement. Our Functional Safety experts additionally share with you the unit testing techniques and suggestion table, as characterized by ISO 26262 standard.
https://www.embitel.com/blog/embedded-blog/iso-26262-compliant-unit-testing-strategies-achieving-functional-safety-in-automotive
The document discusses problems with the current failure mode and effects analysis (FMEA) process at a company called RPL. It notes that before 2010 there was no formal FMEA conducted during new model introductions, leading to inconsistent quality. In 2012 an FMEA template was introduced based on a 5-scale system, but this was found to have issues with accurately capturing severity, occurrence, and detection ratings. Compared to industry standards, the company's FMEA process differs in using a 5-scale instead of a more common 1-10 scale and in not requiring a cross-functional team approach. The document investigates these facts to develop an improved FMEA template and methodology to meet the company's robust manufacturing
This document provides an overview of Failure Mode and Effects Analysis (FMEA). FMEA is a systematic method to identify and prevent potential failures before production. It involves identifying all possible failures, their causes and effects. Teams then evaluate the severity, occurrence, and detection of each failure and prioritize issues to address based on their risk priority number. The document outlines the FMEA process and how to develop one to proactively address potential product and process failures.
The document discusses software testing, outlining key achievements in the field, dreams for the future of testing, and ongoing challenges. Some of the achievements mentioned include establishing testing as an essential software engineering activity, developing test process models, and advancing testing techniques for object-oriented and component-based systems. The dreams include developing a universal test theory, enabling fully automated testing, and maximizing the efficacy and cost-effectiveness of testing. Current challenges pertain to testing modern complex systems and evolving software.
Automotive SPICE® 3.0 - What is new and what has changed?Dominik Strube
With our presentation "Automotive SPICE® 3.0 - What is new and what has changed?" you will know the changes implemented in the new version of Automotive SPICE® v3.0. This is provided free of charge.
This presentation has been created by leading intacsTM SPICE principal assessors. Please feel free to share this documentation among your colleagues, as long as the content is not altered.
ASPICE – Automotive Software Process improvement and capability determination
This is a domain specific version of ISO / IEC 15504
Purpose: To evaluate the efficiency of development processes of ECU suppliers in the automotive industry.
This document provides an overview of Failure Mode and Effects Analysis (FMEA). FMEA is a systematic method for evaluating potential failure modes within a design, identifying their causes and effects, and prioritizing risks. The document outlines the history and purpose of FMEA, defines key terms, and describes how to conduct an FMEA, including establishing a team, documenting the process on a worksheet, scoring risks, and developing action plans. FMEA is a useful tool for proactively identifying and mitigating risks within a product or process design to improve quality and prevent failures.
This document discusses software engineering and software testing. Software engineering is concerned with developing large software through applying engineering principles. The challenge is to produce high quality software within budget and schedule constraints. Software testing is the process of finding errors in software and involves both manual and automated testing. Different types of testing include unit, integration, system, and acceptance testing. The goal of testing is to uncover defects early and reduce costs.
This document summarizes an article from the International Journal of Industrial Engineering and Development titled "Development and Application of SFMEA Model to Software Testing Environment". It discusses using Failure Mode and Effects Analysis (FMEA) to improve software quality assurance. Specifically, it proposes developing a Software FMEA (SFMEA) model to identify potential failures, their causes and effects, for three banking software projects. The document reviews literature on SFMEA and discusses implementing the model to analyze failures and recommend corrective actions. It describes calculating a Risk Priority Number to prioritize failures and validate that the SFMEA model reduces this number and improves software quality.
Common Cause Analysis - Zonal Safety AnalysisTom Jacyszyn
This document provides a common cause analysis and zonal safety analysis for the main landing gear bay of an S18 aircraft. It describes the systems installed in the main landing gear bay, including hydraulic systems, braking components, landing gear components, and an auxiliary power unit bleed duct. Guidelines for equipment installation and separation of redundant systems are discussed. Failure modes are analyzed to determine their effects on other systems. The analysis provides evidence that failures assumed to be independent are truly independent and that hazards from the systems in this zone will not cause a catastrophic failure condition.
ISO26262-6 Software development process (Ver 3.0)Hongseok Lee
ISO26262-6 Software Development Process in the automotive domain. Planning(Coding Guideline. MISRA guideline), Requirement, Design, Safety Analysis, Testing
The Top Ten things that have been proven to effect software reliabilityAnn Marie Neufelder
Ann Marie Neufelder has benchmarked over 150 software organizations and 523 development factors against actual defect data from 79 projects to determine the key factors that influence software reliability. The top factors associated with more defects include large projects, short term contractors without domain expertise, and a "throw over the wall" testing approach. All failed projects in the database started late and had more than three new elements like hardware, tools, processes or people. The findings were used to develop a model to predict defect density before coding begins.
Revised IEEE 1633 Recommended Practices for Software ReliabilityAnn Marie Neufelder
The IEEE 1633 document provides guidance on applying software reliability engineering practices during development. It outlines key tasks such as determining system reliability objectives, performing early software reliability predictions, integrating predictions into overall system models, determining total reliability needed from software, and planning reliability growth. The document aims to help reliability engineers and software engineers collaborate to establish objectives and metrics for individual software components.
Software Testing: History, Trends, Perspectives - a Brief OverviewSoftheme
In this presentation you can learn about different types of software testing, new technologies and methodologies. It contains an overview of software testing perspectives.
You can predict software reliability before the code is even finished. Predictions support planning, sensitivity analysis and also help to avoid distressed software projects and defect pile up.
The document describes different software development process models including the waterfall model, prototyping model, incremental development, spiral development, agile methods, and extreme programming. It explains each model and compares their advantages and disadvantages. The waterfall model is most appropriate when requirements are stable while agile methods are best for changing requirements but can be difficult to manage.
The document provides an overview of failure mode and effects analysis (FMEA). It discusses the history and evolution of FMEA from its origins in the aerospace industry in the 1960s to the current AIAG VDA FMEA Handbook published in 2019. The document outlines the seven step approach of the new handbook, including planning, structure analysis, function analysis, optimization, risk analysis, failure analysis, and documentation of results. It also summarizes some of the major changes between the previous AIAG 4th edition and new handbook, such as replacing RPN with action priority and revising the rating tables.
This document provides an overview of ISO 26262 and functional safety standards. It discusses key aspects of ISO 26262 including its structure, vocabulary, safety lifecycle, roles and responsibilities, and requirements for managing functional safety. ISO 26262 adapts IEC 61508 for automotive and aims to avoid faults and control failures through technical safety measures applied throughout the product lifecycle from concept to decommissioning. Management of functional safety is required to plan, coordinate, and track all safety activities.
This document summarizes a webinar on Failure Mode and Effects Analysis (FMEA) and risk management. The webinar will cover the history and scope of FMEA, different types of FMEA, hazard analysis and risk assessment, FMEA methodology including calculating a Risk Priority Number, and include a live demonstration. It will be presented by Adela Béres, a functional safety expert with over 10 years of experience, and be available on Intland Software's website. Intland focuses on automotive development and helping customers comply with ISO 26262 functional safety standards.
Failure mode and effects analysis (FMEA)—also "failure modes", plural, in many publications—was one of the first highly structured, systematic techniques for failure analysis. It was developed by reliability engineers in the late 1950s to study problems that might arise from malfunctions of military systems. An FMEA is often the first step of a system reliability study. It involves reviewing as many components, assemblies, and subsystems as possible to identify failure modes, and their causes and effects. For each component, the failure modes and their resulting effects on the rest of the system are recorded in a specific FMEA worksheet. There are numerous variations of such worksheets. An FMEA can be a qualitative analysis.
SIA Journée d'étude : NORME ISO 26262 Sécurité fonctionnelle électronique automobile , 04-03-2018
Cédric Heller, DQI/DSEE, French Delegate of TC22/SC32/WG8
Find out about the requirement for ISO 26262 unit testing for car item improvement. Our Functional Safety experts additionally share with you the unit testing techniques and suggestion table, as characterized by ISO 26262 standard.
https://www.embitel.com/blog/embedded-blog/iso-26262-compliant-unit-testing-strategies-achieving-functional-safety-in-automotive
The document discusses problems with the current failure mode and effects analysis (FMEA) process at a company called RPL. It notes that before 2010 there was no formal FMEA conducted during new model introductions, leading to inconsistent quality. In 2012 an FMEA template was introduced based on a 5-scale system, but this was found to have issues with accurately capturing severity, occurrence, and detection ratings. Compared to industry standards, the company's FMEA process differs in using a 5-scale instead of a more common 1-10 scale and in not requiring a cross-functional team approach. The document investigates these facts to develop an improved FMEA template and methodology to meet the company's robust manufacturing
This document provides an overview of Failure Mode and Effects Analysis (FMEA). FMEA is a systematic method to identify and prevent potential failures before production. It involves identifying all possible failures, their causes and effects. Teams then evaluate the severity, occurrence, and detection of each failure and prioritize issues to address based on their risk priority number. The document outlines the FMEA process and how to develop one to proactively address potential product and process failures.
The document discusses software testing, outlining key achievements in the field, dreams for the future of testing, and ongoing challenges. Some of the achievements mentioned include establishing testing as an essential software engineering activity, developing test process models, and advancing testing techniques for object-oriented and component-based systems. The dreams include developing a universal test theory, enabling fully automated testing, and maximizing the efficacy and cost-effectiveness of testing. Current challenges pertain to testing modern complex systems and evolving software.
Automotive SPICE® 3.0 - What is new and what has changed?Dominik Strube
With our presentation "Automotive SPICE® 3.0 - What is new and what has changed?" you will know the changes implemented in the new version of Automotive SPICE® v3.0. This is provided free of charge.
This presentation has been created by leading intacsTM SPICE principal assessors. Please feel free to share this documentation among your colleagues, as long as the content is not altered.
ASPICE – Automotive Software Process improvement and capability determination
This is a domain specific version of ISO / IEC 15504
Purpose: To evaluate the efficiency of development processes of ECU suppliers in the automotive industry.
This document provides an overview of Failure Mode and Effects Analysis (FMEA). FMEA is a systematic method for evaluating potential failure modes within a design, identifying their causes and effects, and prioritizing risks. The document outlines the history and purpose of FMEA, defines key terms, and describes how to conduct an FMEA, including establishing a team, documenting the process on a worksheet, scoring risks, and developing action plans. FMEA is a useful tool for proactively identifying and mitigating risks within a product or process design to improve quality and prevent failures.
This document discusses software engineering and software testing. Software engineering is concerned with developing large software through applying engineering principles. The challenge is to produce high quality software within budget and schedule constraints. Software testing is the process of finding errors in software and involves both manual and automated testing. Different types of testing include unit, integration, system, and acceptance testing. The goal of testing is to uncover defects early and reduce costs.
This document summarizes an article from the International Journal of Industrial Engineering and Development titled "Development and Application of SFMEA Model to Software Testing Environment". It discusses using Failure Mode and Effects Analysis (FMEA) to improve software quality assurance. Specifically, it proposes developing a Software FMEA (SFMEA) model to identify potential failures, their causes and effects, for three banking software projects. The document reviews literature on SFMEA and discusses implementing the model to analyze failures and recommend corrective actions. It describes calculating a Risk Priority Number to prioritize failures and validate that the SFMEA model reduces this number and improves software quality.
Common Cause Analysis - Zonal Safety AnalysisTom Jacyszyn
This document provides a common cause analysis and zonal safety analysis for the main landing gear bay of an S18 aircraft. It describes the systems installed in the main landing gear bay, including hydraulic systems, braking components, landing gear components, and an auxiliary power unit bleed duct. Guidelines for equipment installation and separation of redundant systems are discussed. Failure modes are analyzed to determine their effects on other systems. The analysis provides evidence that failures assumed to be independent are truly independent and that hazards from the systems in this zone will not cause a catastrophic failure condition.
Here is an example operations list for a medical enteral pump system:
1. Power on pump
2. Navigate main menu
1. Set patient details
2. Set feeding program
1. Select feeding mode (continuous, intermittent)
2. Set feeding rate
3. Set feeding duration
3. Start/stop feeding
4. View feeding history
5. Adjust alarm settings
3. Acknowledge/silence alarms
4. Power off pump
This list was developed by walking through the menu structure and identifying the key operations a user could perform with the pump system. The numbering indicates sub-operations under main operations.
The document provides an overview of design and process Failure Mode and Effects Analysis (FMEA). It discusses FMEA as a systematic approach to prioritize risks associated with specific causes of failure. The document outlines the key steps in conducting a design FMEA, including defining potential failure modes and their effects, identifying potential causes, assigning severity, occurrence, and detection ratings, and calculating a risk priority number. It also provides a hypothetical example of a design FMEA for an email response process.
This document provides an overview of Failure Mode and Effects Analysis (FMEA) as a tool for analyzing and managing risks in product design and processes. It discusses how FMEA is used to systematically prioritize risks, identify ways to reduce causes of failure, and document prevention plans. The key steps of an FMEA include determining potential failure modes and their effects, identifying causes, assessing current controls, and calculating risk priorities to inform action planning. FMEA should be conducted throughout the design process and involve cross-functional teams.
Four things that are almost guaranteed to reduce the reliability of a softwa...Ann Marie Neufelder
This presentation shows the four things that have been quantitatively associated with distressed software intensive systems. Identifying these 4 things early in the system life cycle is essential for avoiding or mitigating a failed software project.
Describes a model to analyze software systems and determine areas of risk. Discusses limitations of typical test design methods and provides an example of how to use the model to create high volume automated testing framework.
This document discusses software risk management. It defines risk as any unfavorable event that could hamper a project's completion and risk management as reducing the impact of risks. The importance of software risk management is outlined, noting it addresses complex systems, focuses on critical risks, and can reduce costs through less rework. Risk assessment involves rating risks based on their likelihood and severity to determine priority. Risk identification involves categorizing risks into project, technical, and business risks. Risk containment strategies include avoiding, transferring, and reducing risks. Methodologies discussed include software risk evaluation, continuous risk management, and team risk management.
A Combined Approach of Software Metrics and Software Fault Analysis to Estima...IOSR Journals
The document presents a software fault prediction model that uses reliability relevant software metrics and a fuzzy inference system. It proposes predicting fault density at each phase of development using relevant metrics for that phase. Requirements metrics like complexity, stability and reviews are used to predict fault density after requirements. Design, coding and testing metrics are similarly used to predict fault densities after their respective phases. The model aims to enable early identification of quality issues and optimal resource allocation to improve reliability. MATLAB is used to define fault parameters, categories, fuzzy rules and analyze results. The goal is a multistage fault prediction model for more reliable software delivery.
This document discusses smarter quality management approaches that can provide competitive advantages. It describes the complex nature of software development and increased competition facing organizations. Quality management is important but must balance factors like time to market, costs, and risks. The document introduces an iterative development approach that integrates testing earlier to find defects sooner. It explains that the optimal release time minimizes total risk from quality issues and competition when benefits of further improvements are outweighed. The timing depends on variables like a product's market and defect criticality.
A Survey of Software Reliability factorIOSR Journals
This document discusses factors that affect software reliability and approaches to improving software reliability. It first defines software reliability and lists some key factors that influence reliability, such as software defects, requirements analysis, cost, size estimation, and how reliability is measured. Requirements analysis factors include feasibility studies, surveys, interviews, and testing. Cost is affected by the programmer's knowledge, software architecture, and resource allocation. The document then outlines two approaches to enhancing software reliability: 1) incorporating fault removal efficiency into reliability growth models by accounting for imperfect debugging and new faults introduced during testing, and 2) analyzing software metrics from object-oriented programs to better measure reliability.
The document provides an overview of software engineering, discussing what it is, why it is important, and key concepts like the software development lifecycle, processes, and models. It introduces software engineering as a way to build software in a controlled, predictable manner by giving control over functionality, quality, and resources. It also summarizes several software development process models like waterfall, evolutionary development, and spiral.
The forrester wave™ endpoint security software as a service, q2 2021Andy Kwong
The document evaluates and compares 12 endpoint security software-as-a-service providers. It assesses each vendor based on 24 criteria including threat prevention, detection, controls, data security, mobile security, product performance, strategy, and market presence. The evaluation identifies CrowdStrike, Microsoft, and SentinelOne as Leaders based on having the strongest combinations of offerings, strategies, and market presence relative to their peers.
This document provides an introduction to software engineering. It defines software engineering as the systematic application of engineering principles to software development, maintenance, and operation. The document discusses key questions about software engineering, including what it is, how it differs from computer science and systems engineering, the "software crisis" involving cost overruns and defects, and attributes of good software like maintainability and dependability. It also covers software engineering processes, methods, costs, and challenges.
Information hiding based on optimization technique for Encrypted ImagesIRJET Journal
This document summarizes a research paper on reversible data hiding in encrypted images using an optimization technique. The paper proposes an algorithm that first identifies the area of interest in an encrypted image and then uses a Bat Algorithm to find noisy pixel coordinates for embedding text data. Any remaining data is embedded in the image border areas. The research aims to securely protect embedded data against attacks while maintaining efficiency. It discusses related work on separable reversible data hiding techniques and the need for reversible data hiding in encrypted images to maintain confidentiality while allowing lossless image recovery.
This document discusses challenges in software reliability and proposes approaches to improve reliability predictions and measurements. It addresses issues like:
1. The difficulty of modeling software reliability due to the complexity and interdependence of software failures, unlike independent hardware failures.
2. Challenges with software reliability growth models (SRGMs) due to unrealistic assumptions and lack of operational profile data.
3. The need for consistent, unified definitions of software metrics and measurements to better assess reliability.
4. Questions around how well testing effectiveness metrics like code coverage actually correlate with detecting defects and reliability. The relationship between code coverage and reliability is not clearly causal.
Improving software reliability predictions requires addressing these issues by developing more realistic
This document discusses software reliability engineering and proposes future directions for improving reliability prediction and assessment. It begins with an introduction to software reliability and complexity. It then discusses challenges with current reliability modeling approaches and issues with metrics/measurements. Testing effectiveness and code coverage are also examined. The document proposes methodologies for improving reliability assessment, including focusing on software architectures/components, linking testing and reliability metrics, and collecting industrial data. Overall, it argues that current techniques could be enhanced by incorporating additional factors like code coverage and collecting failure data earlier. Improved reliability prediction would benefit both industry and research.
Biomedical engineering work is subjected to stringent regulatory constraints that mandate a robust engineering process that conforms to all pertinent regulatory guidelines and imperatives.
Software development is an important component of any engineering project and as such, it should be equally addressed and properly integrated with the overall engineering process. To that effect, the following software development process is proposed. This process attempts to be well grounded in the nature of innovative Biomedical engineering work. There are inherent significant technology risks related to the development of innovative biomedical devices. These risks must be correctly identified, and mitigated throughout the entire engineering process. The main benefit of the software development process presented here is its explicit management of software risk factors as recommended by modern successful software development practices.
The document discusses various aspects of software quality assurance (SQA) such as the role of the SQA group in preparing an SQA plan and reviewing software engineering activities to ensure compliance. It also covers SQA goals like requirements, design, and code quality. Statistical SQA involves collecting defect information to identify causes and fixes. Six Sigma methodology aims for high quality through defining, measuring, analyzing, and improving processes. Software reliability, availability, and safety are also addressed.
Software is a collection of instructions that enable users to interact with computers and perform tasks. Without software, computers would be useless. There are different types of software like operating systems, applications, and embedded software. The reliability of software is measured by how well it provides the expected services and how it behaves unexpectedly or undesirably. Software failures occur due to faults in the system. Validation ensures the software meets requirements and functions as intended.
Driving Risks Out of Embedded Automotive SoftwareParasoft
Automobiles are becoming the ultimate mobile computer. Popular models have as many as 100 Electronic Control Units (ECUs), while high-end models push 200 ECUs. Those processors run hundreds of millions of lines of code written by the OEMs’ teams and external contractors—often for black-box assemblies. Modern cars also have increasingly sophisticated high-bandwidth internal networks and unprecedented external connectivity. Considering that no code is 100% error-free, these factors point to an unprecedented need to manage the risks of failure—including protecting life and property, avoiding costly recalls, and reducing the risk of ruinous lawsuits.
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Software FMEA and Software FTA – An Effective Tool for Embedded Software Quality Assurance
1. White Paper
Software FMEA and Software FTA –
An Effective Tool for Embedded
Software Quality Assurance
About the Author Abstract
One of the most important activities in the software development process is the
software quality assurance. The software quality assurance consists of activities
such as design walk throughs, testing and inspections. These activities are carried
out in the following phases: functional requirement specifications, software design,
detailed design and coding. Software FMEA (Failure Mode Effect Analysis) and
Software FTA (Fault Tree Analysis) serves as an effective tool in these activities in
Dr. T Chitra Rajan reducing component-level testing effort and also plan an effective integration and
Safety and Reliability Expert -
system testing. The functional-level software FMEA carried out during the detailed
Embedded Practice
Integrated Engineering Solutions design phase helps in identifying the structural weakness in the software design.
Chitra leads the Safety and Reliability team in
Once the coding phase is over, software FTA and variable level software FMEA can
embedded systems for various industry domains be carried out to study the effect of failures. Software FTA helps in identifying the
including automotive, aerospace, Medical and critical variables responsible for an undesired event. Software FMEA carried out at
E&U. With over 25 years of technical experience
with defense research organizations, Chitra’s variable level helps analyze the code in detail for the various failure modes of the
prime area of focus has been in the analysis of variables leading to critical events which are of concern from the functional
Safety and Reliability of indigenously designed
and developed defense systems for the armed
requirement of the system. These activities help in modifying the code at an early
forces. The author has also evaluated simulated stage so that the costly modifications at a later stage could be avoided.
weapon systems and analyzed statistical data for
over 10 years. This paper discusses the details of software FMEA and software FTA which are
With over 35 publications in National/ effective in the software quality assurance phase with an example.
International Conferences/ Seminars/ Journals,
Chitra holds a doctoral degree from Indian Introduction
Institute of Science Bangalore, India and a The electronic industry has transitioned from hardware stage to the embedded
Masters degree from University of Georgia, USA.
software stage to increase the flexibility within the product. Introduction of
She has also co-authored a book on Reliability
and Six Sigma published by Springer Verlag in embedded systems has helped meet the customer requirements with a few
Feb 2006. additional lines of code in the software. This in turn has helped in getting over the
obsolescence and keeping pace with the customer demands in the market. Right
from consumer electronics, we use in our daily life to any high-end system (e.g.,
air and railway traffic control, nuclear plant control, aircraft and car control),
embedded software plays the key role in all the applications. If we consider the
automotive industry, 90% of innovations are driven by embedded systems. The
vehicle costs are a function of the electronics and software used in the car and
Inside the issue
Abstract .................................................................................................................................................... 01
Introduction .............................................................................................................................................. 01
Software FTA and FMEA ............................................................................................................................ 02
Software FTA ............................................................................................................................................ 03
Software FMEA ......................................................................................................................................... 04
Detailed level FMEA .................................................................................................................................. 05
Conclusion ............................................................................................................................................... 05
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2. White Paper
nearly 50 to 70% of the development costs for ECUs are related to software. The
increasing complexity of software in all these applications calls for a high level
quality assurance before the product is rolled out. While we impose a tight quality
assurance activity, one has to take care of the time and cost involved in it to meet
the time-to-market goal as well.
The challenge with the embedded software is that it executes in real time. Safety-
critical and performance-critical applications require exact limits and measurements.
Statistics or averaging measurement methods are not suitable. Reviews, inspections
and testing are accepted as quality improvement techniques in the software at
every stage in software life cycle. Overall the safety critical and performance critical
nature of many embedded control applications is the paramount reason for
demanding a performance software quality tools. Antilock braking system,
instrument landing system, telecommunication network for spacecrafts, patient
monitoring systems and a host of other products on which we are now so heavily
dependent on embedded software must prove that they deserve our confidence in
their safety and reliability. In this context an embedded system is a little program
that carries an awful lot of responsibilities.
Safety-critical and
This paper describes the application of Software FTA (Fault Tree Analysis) and
performance-critical
Software FMEA (Failure Mode Effect Analysis) as one of the quality assurance tool.
applications require exact These analyses are discussed from the experience gained by application of these
limits and measurements. techniques extensively in the automotive industry. Software testing generally aids
in identifying the faults where as the Software FTA and FMEA addresses the failures..
These analyses aid in identifying potential failures at the system level that is to say
the failures with respect to the system functionality for which the system is designed
for. The FTA and FMEA analysis aids in identifying the single point failure causes
and the combination of conditions leading the undesired failure events. Once we
understand the conditions leading to the functional failure, decisions can be made
to mitigate the risks associated with the failures. Eliminating the risks or mitigating
the risks is a very important task for a safety critical and performance critical
applications.
Software FTA and FMEA
There are two techniques used by hardware which are adopted for software. They
are:
• Fault Tree Analysis (FTA)
• Failure Mode Effects Analysis (FMEA)
While these analyses are more predominant with hazard analysis, they are excellent
tools for determining the weak areas of the software system. These analyses help
identify the potential failures that may lead to potential system failures. The results
of the analyses helps in protecting against those potential failure modes
The FTA is a top-down approach and FMEA is a bottom-up approach. Both these
analyses provide input in testing, verification and validation. Both these methods
address the effect of failures at the system functionality-level . The outcome of the
analysis provides inputs for component testing, integration tests and system testing.
Software failures happen due to memory corruption, incomplete execution, timing
errors (early execution / late execution) etc. The FTA and FMEA analysis aids in
identifying the effects of these failures and look for the protection provided in the
code for some of the critical failures. The functions/ variables for which such
protection is not provided are identified before the product is rolled out.
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3. White Paper
Software FTA
In order to carry out the software FTA, we identify the undesired events with respect
to the system functionality for which the system is designed for. If it is a safety
critical system, these undesired events refer to hazards which are foreseen with
respect to the system functionality and also the environment and other operating
conditions in which the system is operating. Taking the undesired event as the top
most events, we logically connect the software components leading to the event.
Starting from the software functions leading to the event we come down logically to
the conditions triggering these functions and then the global variables responsible
for the triggering. The stopping criteria for the analysis in general are the global
variables leading to the event. The cut set analysis provides the single point variables
and the combination of several other variables leading to the event.
Taking the undesired event as
For each of the single point variable, we look for the protection provided in the
the topmost events we code. For example, the value may be copied in another location or a periodic RAM
logically connect the software check done in order to identify the memory corruption etc. Where the cause is due
components leading to the to failure of group of variables, the common cause is identified to look for the
simultaneous failure of the group of variables at the same instance. Thus when we
event. carry out the FTA, we go through the entire code and one could give a judgment
analysis as to whether the critical variables are protected. Depending on the role of
the variable in the code, additional tests can be suggested.
Thus Software FTA is used as one of the verification tools. Software FTA might be
applied to software design representations to locate problems early and the same
can be fixed before the design is frozen.
Example:
The following example gives the general layout in carrying out the software FTA
for an embedded system.
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4. White Paper
Software FMEA
Software FMEA is a detailed analysis of software components (functions and
variables). FMEA analyses component interaction, dependencies between data
related failures. Software FMEA is performed in two levels-functional level, and
variable level
Functional level FMEA is used in identifying structural weakness in the software
design. It also helps reveal weak or missing requirements and latent software. The
functions of the same are listed below. Here it is important to decide upto what
level each higher level functions are broken further into their constituent functions
in order to select the candidates for FMEA. There is no fixed rule on this. However
normally we go down up to three or four levels. One needs to make a decision on
the importance of those functions. Normally the failure modes considered are
Based on the criticality of
function fails to execute, incomplete execution, timing error (too early, too late),
these failure effects, the erroneous execution. For interrupt service routines the failures considered are failure
software design is examined to return thus blocking lower priority interrupts from executing and returns incorrect
for the protections priority. The effects of these failures are analysed for their system effects. Based on
the criticality of these failure effects, the software design is examined for the
mechanisms provided. protections mechanisms provided.
Example:
Consider an example of functional FMEA of the function written for speedometer
control. The function analysed is ‘read vehicle speed’. The failure modes considered
are fails to execute and erroneous execution of the function. The system effect due
to the failure leads to a severity of 10. (Severity numbers are assigned 1 to 10. 10
refers to the highest order of severity and one refers to least). With the implantation
of the monitor checks, the severity is expected to reduce to 7.
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5. White Paper
Detailed-level FMEA
Is carried out when the complete code is available. Based on the variable type, the
associated failure modes are analysed. The values of the analog variables may take
a higher or lower value than the prescribed value at a given instant of time due to
bit flips. The Boolean variable may take the value true when it has to be false and
vice versa. The enumerated variables have a set of values to take and the failure
mode considered will be the variable taking a different value than the one it has to
have at a particular instant of time. In addition to potential variable failure modes,
potential software processing logic failure modes may be considered. This involves
examining the operators such as addition, subtraction, comparison etc., to determine
the possible negative effects that must be addressed. By assigning severity (severity
values are assigned from 1 to 10 indicating 10 is most severe and 1 least severe) to
The analysis provides critical each failure mode with respect to system effect we can identify the critical variables.
variable list, unused variable Then these critical variables are analysed for the existing protection provided in
the code. If the protection is not provided, then the same is suggested for
lists along with the
implementation. The analysis provides critical variable list, unused variable lists
recommendations to avoid along with the recommendations to avoid failures leading to failure of the system
failures leading to failure of functionalities.
the system functionalities. Example :
Consider a variable level FMEA carried out on a variable calculating the vehicle
speed value. The system effect leads to a severity level of 10. With the
implementation of the fault monitor periodic memory check it is expected that the
severity will be reduced to 7.
Conclusion
The combined results of software FMEA and software FTA provide input for analysis
of interdependencies (causal/temporal) justification for prioritization of verification/
validation test systematic approach from system down to SW subsystems. Since the
software FMEA and FTA analyses require thorough understanding of the software
design, system functionality and the code, certain efforts on component level testing
can be reduced. Some of the findings can aid in better planning of integration and
system testing.
For further information please write to rfi@mahindrasatyam.com
www.mahindrasatyam.com
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