Relations diagram
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This document discusses different types of diagrams used for quality management including affinity diagrams, tree diagrams, matrix charts, process decision program charts, and arrow diagrams. It explains that a relations diagram is useful for analyzing relationships and fits well with how people naturally think about connections between ideas. The relations diagram is formed through brainstorming sessions, interviews, analysis, and verification and can be supplemented with additional tools.
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Six Sigma is a business management strategy originally developed by Bill Smith at Motorola in 1986 to improve processes and minimize defects. It aims for near perfect processes, with 99.99966% defect-free products or 3.4 defects per million opportunities. Six Sigma identifies roles like Champions, Master Black Belts, Black Belts, and Green Belts to lead projects using DMAIC or DMADV methodologies. While effective for process improvement, critics argue Six Sigma may lack originality, oversell consulting services, and focus narrowly on existing processes rather than innovation. Some also question its arbitrary standards and assumptions about normal distributions.
Complexity metrics and models
This document discusses various software quality metrics including lines of code count, defect rates based on lines of code, cyclomatic complexity, fan-in and fan-out, and structural and data complexity metrics. It explains that while lines of code is commonly used, it does not fully capture complexity. Other metrics like cyclomatic complexity, fan-in/fan-out, and data/structural complexity provide additional insight into a program's quality and maintainability. The optimal size of a program may depend on factors like language, project, and environment.
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Six Sigma is a data-driven approach to process improvement originally developed by Motorola. It aims to reduce process variation and defects through the DMAIC methodology of define, measure, analyze, improve, and control. Key roles include Champions, Master Black Belts, Black Belts and Green Belts who work on projects to close the gap between current and six sigma performance of 3.4 defects per million opportunities. While an effective quality improvement strategy, some criticize Six Sigma for overselling by consultants and an overemphasis on short-term goals over disruptive innovation.
Seven basic tools of quality
The document discusses the seven basic tools of quality that were emphasized by Ishikawa:
1. Checklist - Used to collect quality data systematically.
2. Pareto chart - Bar graph used to identify the most important causes of defects.
3. Histogram - Graph of frequency distribution used to understand parameters.
4. Scatter diagram - Relates two variables to investigate relationships.
5. Run chart - Tracks a parameter over time for trend analysis.
6. Control chart - Advanced run chart to monitor a stable process.
7. Cause-and-effect diagram - Links quality problems to their root causes.
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Case tools
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Run chart
A run chart, or run sequence plot, is a graph that displays observed data over time to identify patterns or anomalies. It plots the observed variable on the y-axis and time on the x-axis. A central reference line, like the median, is often included. Run charts are used to detect shifts or outliers in processes over time that could indicate factors influencing variability. They provide a simple way to visualize univariate time series data and identify changes without the control limits of statistical process control charts.
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Complexity metrics and models
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Seven basic tools of quality
The document discusses the seven basic tools of quality that were emphasized by Ishikawa:
1. Checklist - Used to collect quality data systematically.
2. Pareto chart - Bar graph used to identify the most important causes of defects.
3. Histogram - Graph of frequency distribution used to understand parameters.
4. Scatter diagram - Relates two variables to investigate relationships.
5. Run chart - Tracks a parameter over time for trend analysis.
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Case tools
The document discusses Computer-Aided Software Engineering (CASE) tools and their benefits. It describes that CASE tools automate methods for designing, documenting, and producing structured computer code. They can enhance productivity, increase software quality, and support activities across the software development lifecycle. CASE tools are classified as upper, lower, or integrated based on which lifecycle phases they support. Upper CASE tools focus on requirements and design, lower CASE tools on implementation and testing, and integrated CASE tools aim to support the entire development cycle.
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Run chart
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Quality management models
1. Software quality management models can help set defect removal targets and guide quality improvement strategies.
2. The Rayleigh model illustrates how earlier and lower defect removal can be achieved by reducing the error injection rate and increasing front-end defect removal.
3. Tracking actual defect removal against the model targets does not clearly indicate whether variance is due to differences in error injection rates or review/inspection effectiveness, so additional indicators are needed for proper interpretation.
Pareto diagram
A Pareto chart is a type of chart that contains both bars and a line graph used to assess the most frequently occurring defects by category. It arranges issues in descending order of frequency so the cumulative line shows how much of the total frequency is covered by each category. This allows identification of the most important issues to address to maximize impact on reducing the total frequency. Pareto charts are one of the seven basic tools of quality control and can be created in spreadsheet programs or statistical software.
Ishikawa diagram
The document describes Kaoru Ishikawa and the Ishikawa diagram, also known as a fishbone diagram or cause-and-effect diagram. It was developed by Ishikawa to help teams visualize and analyze the potential causes of a particular problem or effect. The diagram structures causes into main categories, typically including methods, machines, materials, measurements, management, manpower, and environment. It then maps potential causes in each category that could contribute to the problem or effect. The document provides examples of using the diagram to analyze the causes of increased productivity in a company and excessive paper drop in a printing process.
Histogram
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Customer satisfaction
1. Customer satisfaction surveys are used to ensure customers have positive experiences and to understand future purchasing patterns.
2. There are various ways to obtain customer feedback, such as telephone calls, complaints, visits, and advisory councils.
3. The three most common survey methods are face-to-face interviews, telephone interviews, and mailed questionnaires, each with their own advantages and limitations.
Control chart
Control charts are statistical tools used to determine whether a manufacturing or business process is stable and predictable or experiencing unpredictable variation. Walter Shewhart invented control charts in the 1920s at Bell Labs to monitor telephony processes. Control charts plot process data over time along with an average line and upper and lower control limits set at 3 standard deviations from the average. As long as data points remain within the control limits, the process is considered in a state of statistical control and predictable. Points outside the limits suggest an unpredictable special cause of variation that requires investigation. Control charts allow detection of changes in a process's natural variation that may require adjusting process parameters.
Complexity metrics and models
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Seven new tools
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2) Dynamic models like the Rayleigh and Weibull distributions use statistical analysis of defect patterns over time to project future reliability. Finding and removing defects earlier in the development process leads to better quality in later stages.
3) Accuracy of estimates from reliability models depends on the input data and how well the model fits the specific organization. No single model works for all situations.
Defect removal effectiveness
1. Defect removal effectiveness measures the percentage of defects found by a particular development activity compared to the total defects present.
2. Several metrics have been proposed to measure defect removal effectiveness, including error detection efficiency, removal efficiency, early detection percentage, and phase containment effectiveness.
3. Studies have shown that defect removal effectiveness tends to increase with higher levels of software process maturity based on the CMM, with level 1 organizations having around 85% effectiveness and level 5 organizations around 95% effectiveness.
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Reliability growth models
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2) The Littlewood models are similar but assume bigger faults are found first.
3) The Goel-Okumoto imperfect debugging model allows for imperfect fixes, where new defects may be introduced when fixing others.
It also briefly discusses other models like the Non-Homogeneous Poisson Process model and Delayed S and Inflection S models.
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3. Tracking actual defect removal against the model targets does not clearly indicate whether variance is due to differences in error injection rates or review/inspection effectiveness, so additional indicators are needed for proper interpretation.
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A Pareto chart is a type of chart that contains both bars and a line graph used to assess the most frequently occurring defects by category. It arranges issues in descending order of frequency so the cumulative line shows how much of the total frequency is covered by each category. This allows identification of the most important issues to address to maximize impact on reducing the total frequency. Pareto charts are one of the seven basic tools of quality control and can be created in spreadsheet programs or statistical software.
Ishikawa diagram
The document describes Kaoru Ishikawa and the Ishikawa diagram, also known as a fishbone diagram or cause-and-effect diagram. It was developed by Ishikawa to help teams visualize and analyze the potential causes of a particular problem or effect. The diagram structures causes into main categories, typically including methods, machines, materials, measurements, management, manpower, and environment. It then maps potential causes in each category that could contribute to the problem or effect. The document provides examples of using the diagram to analyze the causes of increased productivity in a company and excessive paper drop in a printing process.
Histogram
The document discusses histograms, which are graphical representations used to assess the probability distribution of a variable. Histograms consist of bars representing frequency or probability distributions in intervals. They were first introduced by Karl Pearson in 1895 to estimate the probability distribution of a continuous variable. Histograms provide a visual impression of the distribution of data and are one of the seven basic tools of quality control.
Customer satisfaction
1. Customer satisfaction surveys are used to ensure customers have positive experiences and to understand future purchasing patterns.
2. There are various ways to obtain customer feedback, such as telephone calls, complaints, visits, and advisory councils.
3. The three most common survey methods are face-to-face interviews, telephone interviews, and mailed questionnaires, each with their own advantages and limitations.
Control chart
Control charts are statistical tools used to determine whether a manufacturing or business process is stable and predictable or experiencing unpredictable variation. Walter Shewhart invented control charts in the 1920s at Bell Labs to monitor telephony processes. Control charts plot process data over time along with an average line and upper and lower control limits set at 3 standard deviations from the average. As long as data points remain within the control limits, the process is considered in a state of statistical control and predictable. Points outside the limits suggest an unpredictable special cause of variation that requires investigation. Control charts allow detection of changes in a process's natural variation that may require adjusting process parameters.
Complexity metrics and models
This document discusses various software quality metrics including lines of code count, defect density as it relates to size, cyclomatic complexity, fan-in/fan-out, and other structural and data complexity metrics. It provides empirical data on the relationship between size and defects, defines key metrics like cyclomatic complexity, and discusses how these metrics can help evaluate software quality and estimate testing effort.
Check lists
The check sheet is a simple document used to collect quality-related data in real-time. It is designed for quickly and efficiently recording desired quantitative or qualitative information through checks or marks. Common types include classification, location, frequency, and measurement scale check sheets. The check sheet is one of the seven basic tools of quality control.
Capability maturity model
The Capability Maturity Model Integration (CMMI) provides organizations with guidelines for improving their processes. It defines key process areas and maturity levels for activities like project planning, risk management, and configuration management. An organization is appraised against CMMI practices rather than certified. The appraisal determines their maturity level or capability level to identify improvement areas. CMMI uses both staged and continuous appraisal approaches.
Structure chart
A structure chart is a top-down diagram that shows the breakdown of a system into manageable sub-modules. It represents each module as a box with lines connecting them to show relationships. Structure charts are used in software engineering to plan program structure and divide a problem into smaller tasks. They provide a hierarchical visualization of how a program or system is decomposed.
Seven new tools
The document describes seven management and planning tools that were developed from operations research after World War II and Japanese quality control methods. The seven tools are affinity diagram, interrelationship diagraph, tree diagram, prioritization matrix, matrix diagram, process decision program chart, and activity network diagram. Each tool is used for organizing information, analyzing relationships, breaking concepts into finer levels of detail, prioritizing items, showing relationships between items, planning tasks and identifying risks, and planning task sequences.
Scatter diagram
A scatter plot displays values for two variables from a data set as a collection of points, with one variable determining the horizontal position and the other determining the vertical position. Scatter plots can reveal correlations between variables, such as positive, negative, or no correlation. They are useful for visualizing nonlinear relationships and comparing two data sets. An example shows lung capacity on the x-axis and breath holding time on the y-axis for a study of individuals.
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The document discusses software quality management and quality management systems. It defines a quality management system as having an organizational structure, procedures, processes, and resources to implement quality management. A quality management system should include quality assurance and quality improvement functions. There are five key components of a quality management system: organizational structure, procedures, processes, resources, and responsibilities. The goal is to assign responsibility for quality and ensure each employee is responsible for quality.
Rayleigh model
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2) Dynamic models like the Rayleigh and Weibull distributions use statistical analysis of defect patterns over time to project future reliability. Finding and removing defects earlier in the development process leads to better quality in later stages.
3) Accuracy of estimates from reliability models depends on the input data and how well the model fits the specific organization. No single model works for all situations.
Defect removal effectiveness
1. Defect removal effectiveness measures the percentage of defects found by a particular development activity compared to the total defects present.
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3. Studies have shown that defect removal effectiveness tends to increase with higher levels of software process maturity based on the CMM, with level 1 organizations having around 85% effectiveness and level 5 organizations around 95% effectiveness.
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3) The Goel-Okumoto imperfect debugging model allows for imperfect fixes, where new defects may be introduced when fixing others.
It also briefly discusses other models like the Non-Homogeneous Poisson Process model and Delayed S and Inflection S models.
Rayleigh model
This document discusses software reliability models and the Rayleigh model in particular. It explains that reliability models can be static or dynamic, and the Rayleigh model is a dynamic model based on a Weibull distribution. The Rayleigh model uses parameters estimated from project data to project defect rates. Higher defect rates during development generally correlate with higher field defect rates. More defects found and removed earlier in the process yields better quality. Accuracy of models depends on valid input data and establishing predictive validity for different organizations.
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Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
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Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
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Relations diagram
- 1. Software Quality Management Unit -3 Roy Antony Arnold G Asst. Prof Asst Prof. / CSE SQM - Unit 3 - Relations Diagram - GRAA
- 2. Affinity Diagram Tree Diagram Matrix Chart Matrix Data Analysis Chart Process Decision P P D i i Program Ch t (PDPC) Chart Arrow Diagram. SQM - Unit 3 - Relations Diagram - GRAA
- 3. It displays and . It organizes information from specific to general and surfaces and . It di l displays , whereas the cause-and-effect diagram shows only one effect and its cause structure. SQM - Unit 3 - Relations Diagram - GRAA
- 4. SQM - Unit 3 - Relations Diagram - GRAA
- 6. Relations Di R l i Diagram i is for f . It is flexible and it fits naturally with the in and . The final form was the cumulative result of subsequent b brainstorming b i i sessions, i interviews, further analysis, and verifications. verifications The relations diagram can also be supported by pp y . SQM - Unit 3 - Relations Diagram - GRAA