Find defects
Training
Communications
Hostage taking
Individual:
Preparation, or
Detection
Initial:
Check criteria
Plan
Overview
Process
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 4
Group:
Detection, or
Collection
Inspection record
Data collection
Exit:
Change
Follow-up
Document & data
handling
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 1
Number of inspectors
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 5
Severity
Decision for entire document:
Number of hours
Classes of defects
Description
Pass with changes
Reinspect
Number of defects
Location
Data collection
Scribe
Inspector
Moderator
Author
Roles
Identification
Inspection record
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 2
testing in a tech-report 1985.
Graham and Gilb publish the book Software inspections 1993. This
describes the standard process of today.
Presentation of the Porter-Votta experiment in Sorrento 1994 starts a
boom for replications.
Sauer et al compare experimental data with behavioural research in a
tech-report 1996
Basili and Selby show the advantage of inspections compared to
IBM systems journal
Fagan publishes results from code and design inspections 1976 in
The best way of finding many defects in code and
other documents
Experimentally proven in replicated studies
Goals:
Development over the years
Systematic inspections
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 6
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 3
Id
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 8
Majority values:
up to 3.5 h preparation per document
up to 3 h inspection time
up to 4000 lines of code
2 to 6 people involved
90 percentile = 30
Median number of defects = 8
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 10
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 11
line (12 minutes per page)
Size of document have negative effect on DFR, max
recommendation 5000 lines
A certain project is better than two of the others
4 inspectors seems best (not significant)
Analysis performed by Henrik Berg, LiTH-MAT-Ex-199908
Preparation time per code line typically 0.005 hours per
Usage-based
Perspective-based
Scenario
Checklist
214 code inspections from 4 projects at Ericcson
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 7
Class.
Regression wrt defect detection
ratio
Description
Reading techniques
Practical investigation
Loc.
Our inspection record
inspector 3
defects, frequent defects, or
random defects
Popular mind map:
The Ishikawa diagram
Parameters:
Defect category
Visible consequences
Did-detect
Introduced
Main
Should-detect
cause
Reason
Performed regularly for severe
inspector 1
inspector 3
Main
cause
Main
cause
Main
cause
Problem
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 12
Main
cause
Main
cause
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 9
Fewer remaining defects
inspector 2
Root-cause analysis
Many remaining defects
inspector 2
inspector 1
Capture-recapture
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 13
False positivesKristian Sandahl, IDA krisa@ida.liu.se
Slide no 14
Inspection
data
Coding
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 16
Inspection
data
Test-cases
Inspection Inspection Inspection
data
data
data
Design
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 17
number of inspectors, compare with testing
Enthusiasts: Vary things, such as PI – DD,
you got from that
Record the result as we did, reflect on the value
Improvement: reduce variation, increase precision
Analysis
Be at least 3 inspectors
Control – adjust the process
formal document
Practice inspection on code from a lab, or a
Appraisal – defect detection
Assurance – prediction of defects
Home assignment no 9
Inspections in quality assurance
Defect list
Two experts
Audit
Review
Structured walk-through
Good data recording
Peer review
Repository
Desk check
Weaker methods
Good reading techniques
Inspectors
”Optimal” method
Calender time
Person-hours
Cost of quality
Kristian Sandahl, IDA krisa@ida.liu.se
Slide no 15