Seven basic tools of quality
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Seven basic tools of quality

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Anna University, Final CSE, Software Quality Management

Anna University, Final CSE, Software Quality Management

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Seven basic tools of quality Seven basic tools of quality Presentation Transcript

  • SQM - Unit 3 - GRAASEVEN BASIC TOOLS OF QUALITY Software Quality Management Unit – III Roy Antony Arnold G Asst. Prof. / CSE
  • Seven Basic ToolsSeven Basic Tools "The Old Seven."  "The First Seven." "The Basic Seven."  The seven basic tools of quality are first emphasized  by Ishikawa, a professor of engineering at Tokyo  University. He called as father of “quality circles”. called as father of  quality circles . SQM - Unit 3 - GRAA
  • Why Seven Basic Tools Seven Basic Tools? The Seven Basic Tools of Quality is a designation given to a fixed  g p q , p set of graphical techniques, which are helpful to maintain  software quality.  They are called basic because they are suitable for people with  little formal training in statistics and because they can be used  to solve the vast majority of quality‐related issues. Good use of the seven basic tools can lead to positive long‐term  results for process improvement and quality management in  software development. SQM - Unit 3 - GRAA
  • What are Seven Basic ToolsWhat are Seven Basic Tools? The Check List or Check Sheet  The Pareto Diagram The Histogram  The Scatter Diagram  The Scatter Diagram The Run chart (alternately Flow Chart or  Stratification)  St tifi ti ) The Control Chart  The Cause‐and‐Effect Diagram or Ishikawa Diagram  or Fish‐Bone Diagram SQM - Unit 3 - GRAA
  • Contd... SQM - Unit 3 - GRAA
  • Check ListCheck ListIt is a simple document that is used for collecting data in real‐time and at the location where the data is generated.ItsI main purpose i to provide a structured way to collect i is id d llquality‐related data for assessing a process or as an input toother analyses analyses.Bernstein, 1992, observed that the checklists summarize thekey points of the process and they are much more effectivethan the lengthy process documents.Each phase in a software development has a set of tasks to p pcomplete. Checklists help developers and programmers toensure that all tasks are complete. SQM - Unit 3 - GRAA
  • Contd...Another type of checklist is the common error list,which is part of the stage kickoffs of the defectprevention process (DPP).DPP involves three key steps: (1) analysis of defects to trace the root causes, ( ) (2) action teams to implement suggested actions, and p gg , (3) stage kickoff meetings as the major feedback mechanismPTF (Program Temporary Fix) is the fix delivered to customers ( og a e po a y ) s t e de e ed custo e swhen they encounter defects in the software system. SQM - Unit 3 - GRAA
  • Example SQM - Unit 3 - GRAA
  • Example 2Example 2 SQM - Unit 3 - GRAA
  • Pareto Diagram Pareto DiagramIt is a frequency chart of bars in descending order; the frequency bars are usually associated with types of problems. It is named after a 19th CI i d f 19 Century Italian economist named Vilfredo I li i d Vilf dPareto (1848–1923), who expounded his principle in terms of the distribution of wealth that a large share of the wealth is owned distribution of wealth—that a large share of the wealth is ownedby a small percentage of the population. In 1950 Juran applied this principle to the identification of quality In 1950 Juran applied this principle to the identification of qualityproblems—that most of the quality problems are due to a small percentage of the possible causes. Pareto analysis is commonly referred to as the 80–20 principle (20% of the causes account for 80% of the defects) SQM - Unit 3 - GRAA
  • Contd...In software development, the X‐axis is usually the defect cause and the Y‐axis the defect count. It indicates which problems should be solved first in I i di hi h bl h ld b l d fi ieliminating defects and improving the operation. Grady and Caswell (1986) hG d dC ll (1986) shown a Pareto analysis of  P l i fsoftware defects by category for four Hewlett‐Packard software projectssoftware projectsThe top three types (new function or different processing required, existing data need to be organized/ presented required existing data need to be organized/ presenteddifferently, and user needs additional data fields) account for more than one‐third of the defects. SQM - Unit 3 - GRAA
  • Pareto Analysis for IBM Rochester product d INTF Interface Problems INIT Data Initialization Problems CPLX Complex Logical Problems NLS Translation related National Language Problems g g ADDR Address Problems DEFN Definition Problems SQM - Unit 3 - GRAA
  • SQM - Unit 3 - GRAA
  • HistogramIt is a graphic representation of frequency counts of a It i hi t ti ff t fsample or a population. The X‐axis lists the unit intervals of a parameter (e.g., Th X i li t th it i t l f t (severity level of software defects) ranked in ascending order from left to right, and the Y‐axis contains the order from left to right and the Y axis contains thefrequency counts. The purpose of the histogram is to show the distribution The purpose of the histogram is to show the distributioncharacteristics of a parameter such as overall shape, central tendency, dispersion, and skewness. central tendency dispersion and skewnessIt enhances understanding of the parameter of interest. SQM - Unit 3 - GRAA
  • SQM - Unit 3 - GRAA
  • Customer Satisfaction HistogramCustomer Satisfaction Histogram SQM - Unit 3 - GRAA
  • Scatter DiagramScatter Diagram A scatter diagram vividly portrays the relationship of two interval  variables.  Compared to other tools, the scatter diagram is more difficult to  Compared to other tools the scatter diagram is more difficult to apply.  It usually relates to investigative work and requires precise data. It  t usua y e ates to est gat e o a d equ es p ec se data t is often used with other techniques such as correlation analysis,  regression, and statistical modelling. Each point in a scatter diagram represents an observation of both  the dependent and independent variables.  Scatter diagrams aid data‐based decision making (e.g., if action is  S tt di id d t b d d i i ki ( if ti i planned on the X variable and some effect is expected on the Y  variable).  SQM - Unit 3 - GRAA
  • Contd... One should always look for a scatter diagram when the  correlation coefficient of two variables is presented. The method for calculating the correlation coefficient is  Th h df l l i h l i ffi i i highly sensitive to outliers, and a scatter diagram can clearly  expose any outliers in the relationship.  expose any outliers in the relationship The most common correlation coefficient is Pearsons  product moment correlation coefficient, which assumes a  product moment correlation coefficient, which assumes a linear relationship.  If the relationship is nonlinear, the Pearson correlation  p , coefficient may show no relationship; therefore, it may  convey incorrect or false information. SQM - Unit 3 - GRAA
  • Correlation of Defect Rates of Reused Components Between Two PlatformsB t T Pl tf SQM - Unit 3 - GRAA
  • Run ChartRun Chart A run chart tracks the performance of the  parameter of interest over time.  These charts serve as real‐time statements of  quality as well as workload. The X‐axis is time and the Y‐axis is the value of the  parameter.  parameter. A run chart is best used for trend analysis, especially  if historical data are available for comparisons with  if historical data are available for comparisons with the current trend.  SQM - Unit 3 - GRAA
  • Contd... Ishikawa (1989) includes various graphs such as the pie chart, bar graph, compound bar graph, and circle graph under the section that discusses run charts. An example of a run chart in software is the weekly number of open problems in the backlog; it shows the development teams workload of software fixes. SQM - Unit 3 - GRAA
  • Run Chart of Percentage of Delinquent Fixes l SQM - Unit 3 - GRAA
  • Control ChartControl Chart The control chart is a powerful tool for achieving  Th l h i f l lf hi i statistical process control (SPC).  However, in software development it is difficult to  H i f d l i i diffi l use control chart in the formal SPC manner.  It is a formidable task, if not impossible, to define  I i f id bl k if i ibl d fi the process capability of a software development  process.  process A control chart can be regarded as an advanced  form of a run chart for situations where the process  form of a run chart for situations where the process capability can be defined.  SQM - Unit 3 - GRAA
  • Contd... It consists of a central line, a pair of control limits (and  sometimes a pair of warning limits within the control limits),  and values of the parameter of interest plotted on the chart,  and values of the parameter of interest plotted on the chart which represent the state of a process.  The X axis is real time. If all values of the parameter are  The X‐axis is real time If all values of the parameter are within the control limits and show no particular tendency, the  process is regarded as being in a controlled state.  If they fall outside the control limits or indicate a trend, the  process is considered out of control. Such cases call for  causal analysis and corrective actions are to be taken. SQM - Unit 3 - GRAA
  • Contd... In statistical terms, process capability is defined: USL − LSL CP = 6 Sigma where USL and LSL are the upper and lower engineering specification limits, respectively, sigma is the standard deviation of the process, and 6 sigma represents the overall process variation. i i If a unilateral specification is affixed to some characteristics, the th capability i d may b d fi d bilit index be defined: ( (u‐process mean) ) USL − u u − LSL CP = CP = 3Sigma SQM - Unit 3 - GRAA 3Sigma
  • Pseudo‐Control Chart of Test Defect Rate—First IterationIt ti SQM - Unit 3 - GRAA
  • Example: 2Example: 2 SQM - Unit 3 - GRAA
  • Cause and Effect DiagramCause‐and‐Effect Diagram This was developed by Ishikawa and associates in the early  1950s in Japan.  It was first used to explain factors that affect the production  I fi d l i f h ff h d i of steel. It shows the relationship between a quality characteristic  It sho s the relationship bet een a quality characteristic and factors that affect that characteristic.  Its layout resembles a fishbone. Its layout resembles a fishbone While the scatter diagram describes a specific bivariate  relationship in detail, the cause‐and‐effect diagram identifies  relationship in detail the cause‐and‐effect diagram identifies all causal factors of a quality characteristic in one chart. SQM - Unit 3 - GRAA
  • Cause and Effect DiagramCause‐and‐Effect Diagram These are diagrams show the causes of a certain event  Th di h th f t i t Common uses of this diagram are product design and quality  defect prevention, to identify potential factors causing an  p , yp g overall effect.  Causes are usually grouped into major categories to identify  these sources of variation. The categories typically include: these sources of variation The categories typically include: People Methods Machines Materials Measurements Environment SQM - Unit 3 - GRAA
  • Cause and Effect DiagramCause‐and‐Effect Diagram SQM - Unit 3 - GRAA
  • Cause‐and‐Effect Diagram Contd. Typical categories of causes are: Typical categories of causes are: The 8 Ms (used in manufacturing) Machine (technology)  Method (process)  Method (process) Material (Includes Raw Material, Consumables and Information.)  Man Power (physical work)/Mind Power (brain work) Measurement (Inspection)  Milieu/Mother Nature (Environment)  Management/Money Power  Maintenance  The 8 Ps (used in service industry) The 8 Ps (used in service industry) Product=Service  ▪ Price  Place  ▪ Promotion/Entertainment  People (key person)  People (key person) ▪ Process Process  Physical Evidence  ▪ Productivity & Quality  The 4 Ss (used in service industry) Surroundings  g Suppliers  Systems  SQM - Unit 3 - GRAA Skills