Nagesh Muralidhar and Praveen Shivaswamy, Siemens
Every project captures defects which are classified based on attributes like Severity, Type, Injection & Detection Phase, & are used for Root Cause Analysis (RCA),on which Actions are derived to improve defect occurrence. However, we do not explore to see if different developers have same understanding. If different across developers, classified data used for RCA may provide a different picture & actions planned will not lead to improvement making it an ineffective RCA.
Measurement System Analysis (MSA) is Scientific & objective method of analyzing validity of measurement system. It is a “tool” which quantifies:
- Equipment Variation
- Appraiser (Developer/Tester) Variation
- The Total Variation of a Measurement System Gage Repeatability & Reproducibility (Gage R&R) is a MSA methodology that is widely used for Attribute data.
Gage R&R was piloted in a project with following sample:
- 14 defects across Code Review, IT & ST classified by Subject Matter Expert
- 6 Developers with varying experiences from project selected to classify the defects in 2 trials
- The data was analyzed using Minitab in following steps:
- Attribute Agreement Analysis o Comparing Appraisers against themselves
- Comparing Appraisers against a known Standard o Comparing between Appraisers
- Agreement between all Appraisers together and the Standard Gage R&R Result needs be drawn based on overall Kappa values from above 5 analysis steps.
Result from sample study was that we need to improve ability of Developers to make better decision in Categorizing Defects by providing training & bringing in more clarity on attributes. Attribute Gage R&R was successfully implemented for first time in one of Software development Business Unit of Siemens. The study helped us to devise training’s specific to individuals & teams. Intention is to spread this across other Business Units of Siemens.
Target Audience: Expert/Advanced
2016 Technical Paper, Nagesh Muralidhar and Praveen Shivaswamy,, Paper, Slides, Notes, Video.
