Paper Info
Title
Determining the cost impact of SCM system errors
Abstract
Software Configuration Management (SCM) auditing is the fourth of four sub processes recommended by the IEEE and the ACM in this area. This research is the continuation of ongoing experiments in the use of heuristics for predicting fault rates in systems that support SCM. This paper allocates financial indicators to the business model for a hypothetical Telecommunications company and predicts the potential financial error impact due to Configuration Management errors in the SCM system. This paper focuses on sampling first Use Cases in order to determine the error rates by Operating Profile and then using that knowledge in drawing samples of Test Cases. The 5,388 Test Cases were generated from sources available in open forums and they were injected with 4% of faults; 2.1% carried from Use Cases and 2% added. A total sampling of 492 items was conducted and was able to approximate the financial error rate in 6,006 items at an acceptable level with a 92% reduction in effort. The two stage sampling technique performed better than straight random sampling. When applied to the contribution from each Test Case, random sampling produced above a 6.87% error in the value chain estimate while two stage sampling produced under a 2.72% error in the same estimate.
Year
DOI
Venue
2014
10.1109/CIPLS.2014.7007173
Computational Intelligence in Production and Logistics Systems
Keywords
DocType
Citations 
IEEE standards,configuration management,program testing,sampling methods,ACM,IEEE,SCM auditing,SCM system errors,business model,fault rate prediction,financial error impact,financial indicators,hypothetical Telecommunications company,random sampling,software configuration management auditing,test cases,two stage sampling technique,use cases,Adaptive Sampling,Business Model Value Chain,Configuration Auditing,Error Rates,Financial Risk Management,Random Sampling,Software Configuration Management,Stratified Sampling,Systematic Sampling,Test Cases,Use Cases
Conference
0
PageRank 
References 
Authors
0.34
4
1
Name
Order
Citations
PageRank
John M. Medellin100.34