Process Improvement

CIS 376

Bruce R. Maxim

UM-Dearborn

Process Improvement Goals

• Understanding existing processes• Introduce process changes to improve quality,

reduce costs, or accelerate schedules• Industry is demanding increased attention to

quality in general• Most process improvement work focuses on defect

reduction and prevention• There are other process attributes that deserve our

attention

Process Improvement Attributes - part 1

• Understandability - degree to which a process is well defined and understood

• Visibility - process activities have results that are externally recognizable

• Supportability - process activities supported by CASE tools

• Acceptability - defined processes are used and accepted by software engineers

Process Improvement Attributes - part 2

• Reliability - process is defined so that errors are avoided or trapped before product errors result

• Robustness - process can continue despite unexpected problems

• Maintainability - process can evolve to reflect changing organizational requirements or identified process improvements

• Rapidity - the time required to complete a system from specification to delivery

Process Improvement Stages

• Process analysis– modeling and quantitative analysis of existing processes

• Improvement identification– quality, cost, and scheduling bottlenecks located

• Process change introduction– modify process to remove bottlenecks

• Process change training– train staff involved in process revision proposals

• Change tuning– process improvements are revised and allowed to evolve

Process Improvement Activities

Processmodel

Process changeplan

Trainingplan

Feedback onimprovements

Revised processmodel

Analyseprocess

Identifyimprovements

Tuneprocess changes

Introduceprocess change

Trainengineers

Process and Product Quality

• Closely related to one another

• Good processes are usually required to produce good products

• In manufacturing applications, process is principle determinant of quality

• For design-based activities, the capabilities of the designers are also important

Product Quality Factors

• Development technology– for large projects with average capability this is the main

determinant of product quality

• Quality of people involved– for small projects the developer capability is the main determinant

of product quality

• Process quality– significant for both small and large projects

• Cost, time, and schedule constraints– unrealistic schedules can doom the quality of most products

Process Analysis and Modeling

• Process analysis– study of existing processes to understand relationships among

process components

– allows comparisons with other processes

• Process modeling– documentation of process in which the tasks, roles, and entities

used are recorded

– best to represent models graphically

– several different perspectives may be used (e.g. activities, deliverables, etc.)

– model should be examined for weaknesses, this involves discussion with stakeholders

Process Model Elements - part 1

• Activity - (round edged rectangle)– has clearly defined objective, entry, and exit conditions

• Process - (round edged rectangle with shadow)– set of coherent activities with agreed upon objective

• Deliverable - (rectangle with shadow)– tangible output of an activity predicted by project plan

• Condition - (parallelogram)– process or activity pre- or post-conditions

Process Model Elements - part 2

• Role - (circle with shadow)– defined and bounded area of responsibility

• Exception - (double edged box))– description of how to modify the process if anticipated

or unanticipated events occur

• Communication - (arrow)– exchange of information between people and/or

machines

Process Model Example

Testmodule

Signed-of f testrecord

Module testdata

Modulespecification

Module compileswithout syntax

errors

All defined testsrun on module

Testengineer

Pre-condition

InputProcess

RôlePost-condition

OutputsResponsible

for

Process Exceptions

• Process models can’t represent how to handle exceptions– key people are lost prior to a critical review

– failure of e-mail server for several days

– organizational reorganization

– request to respond to change requests

• General procedure is to suspend the process model and follow RMMM plans augmented with the managers own initiatives

Process Measurement

• Wherever possible quantitative process data should be collected

• Organizations without process standards may have to be define processes before measurements can be made (since they won’t know what to measure)

• Process measurements should be used to assess process improvements

• Organization objectives drive process improvement, not measurements

Process Measurement Classes

• Time taken to complete process activities– e.g. calendar time to complete a milestone

• Resources required to complete processes or activities– e.g. person months

• Number of event occurrences – e.g. number of defects found

Goal Question Metric Paradigm

• Goals– What is the organization trying to achieve?

– Process improvement deals with goal satisfaction.

• Questions– Concerned with areas of uncertainty related to goals.

– You need process knowledge to derive questions.

• Metrics– Measurements collected to answer questions

SEI Process Maturity Model

• Level 1 - Initial– essentially uncontrolled

• Level 2 - Repeatable– project management procedures defined and used

• Level 3 - Defined– process management strategies defined and used

• Level 4 - Managed– quality management strategies defined and used

• Level 5 - Optimizing– process improvement strategies defined and used

SEI Process Model Problems• Focuses on project management rather than project

development• Ignores the use of strategies like rapid prototyping• Model is intended to represent organizational

capability and not practices used on particular projects

• There may be wide variation in the practices used in a single organization

• Capability assessment is questionnaire-based

Capability Assessment Process

Select projectsfor assessment

Distributequestionnaires

Analyseresponses

Clarifyresponses

Identify issuesfor discussion

Interviewproject managers

Interviewengineers

Interviewmanagers

Brief managersand engineers

Presentassessment

Write report

Process Classification

• Informal– No detailed process model, developers created their

own way of doing things

• Managed– defined model drive development process

• Methodical– processes supported by standard development method

• Supported– processes supported by automated CASE tools

Process Tool Support

Informalprocess

Managedprocess

Methodicalprocess

Improvingprocess

Specializedtools

Analysis anddesign

workbenches

Projectmanagement

tools

Configurationmanagement

tools

Generictools

Defect Removal Effectiveness

• Defect removal is central to software development

• One of the top expense items

• Affects project scheduling

• Improves product quality

PSP - Defect Density• This is the primary defect measure used in

PSP

• Dd = 1000 * D/N

• D = total number of defects found in all phases of the process

• N = number of new and changed lines of code in the program

Defect Density Example

• For a program with 96 new or changed lines of code and 14 defects

• Dd = 1000 * (14/96) = 145.83 defects/KLOC

Defect Metrics - part 1

• Error Detection Efficiency100%*(#errors found in 1 inspection)/(#errors in product before inspection)

• Defect Removal Efficiency100%*(#defects found now)/(#defects found now + #defects found later)

• Error Detection Percentage100%*(#inspection errors)/(#inspection errors + #valid discrepancy reports)

Defect Metrics - part 2

• Total Defect Containment Effectiveness (TDCE)(#prerelease defects)/(#prerelease defects + #post-release defects)

• Phase Containment Effectiveness (PCE)(#phase(i) defects)/(#phase(i) defects + #phase(i+x) defects)

• Effectiveness (E)100%*N/(N + S)

N = #defects found by an activity

S = #defects found in subsequent activities

Phase-based Defect Removal Model

• Defects present at exit of each development phase are estimated

• This allows us to set realistic targets and assess the costs of reducing error injection rates

• This is a quality management tool and not a device for estimation of software reliability

• How would this work in practice?

Assumptions

• Suppose we decide to create two broad defect removal classes– activities that handle defects before code is

integrated into the system library (design reviews, inspections, unit testing)

– formal machine tests after code integration

• Also assume the same defect removal effectiveness for each phase

Example - part 1

• MP = major problems found in before integration• PTR = errors found during formal machine tests• mu = MP/PTR

– the higher the value of mu the better• Q = defects found after release to customer• TD = (MP + PTR + Q)

– total defects for life of software

Example - part 2

• Phase 1 effectiveness

E1 = MP/TD

MP = E1 * TD• Phase 2 effectiveness

E2 = PTR/(TD - MP)

PTR = E2 * (TD - MP)

Example - part 3

• Some equations that can be useful in quality planning (assuming that E1 = E2)

Q = PTR /(mu - 1)

Q = MP / [mu * (mu - 1)]

Q = TD / (mu * mu)

• These equations work with either raw or normalized defect values

PSP – Phase Yield

Phase yield =

100 * (defects removed during phase)/

(defects in product at phase entry)

Note: cannot be computed until project is completed

Phase Yield - Example

• 5 defects found during code review• 3 defects found during compile• 2 defects found during unit testing• 2 defects found during integration testing

• Phase yield for compile =100 * 3 / (3 + 2 + 2) = 42.9 %

• Phase yield for code review =100 * 5 /(5 + 3 + 2 + 2) = 41.7 %

Seven Basic Software Quality Tools

• Checklists (paper forms)– used to gather data for later analysis– used to confirm that process tasks are complete– both simple yes/no and branching questions

Seven Basic Software Quality Tools

• Pareto Diagram– bar chart sorted in descending height order– vertical axis labeled with # defects– horizontal axis (nominal) labeled with defect

cause types– software defects tends cluster near related

causes

Seven Basic Software Quality Tools

• Histogram– frequency bar graph – vertical axis is # defects– horizontal axis has ordinal or interval type

labels

Seven Basic Software Quality Tools

• Flowchart– pictorial representation of a process– breaks down process into its constituent steps– can be useful in identifying were errors are

likely to be found in the system

Seven Basic Software Quality Tools

• Scatter diagram (point plots)– used with correlation, regression, or statistical

modeling – vertical axis is # defects– horizontal axis some metric (e.g. McCabe’s

index)

Seven Basic Software Quality Tools

• Run chart– line graph showing performance of dependent

variable (y) over time (x)– best used for trend analysis (e.g. arrival of

defects during formal machine testing)– can plot cumulative dependent variables (S

curves)

Seven Basic Software Quality Tools

• Control chart– advanced form of run chart where capability is defined

– upper and lower control limits (dashed lines) are drawn to alert the user when dependent measure is out of control

– can plot cumulative dependent variables (S curves)

– C chart based on # conforming or not

– R chart based on subgroup ranges (max – min)

– X bar chart based on subgroup means

Control Chart (C)

Seven Basic Software Quality Tools• Cause and effect (fish bone) diagram

– not widely used in software development, but can be useful

– shows effect between quality variable and the factors affecting it

Fishbone Diagram