Visible to the public An Empirical Study of Comparison of Code Metric Aggregation Methods–on Embedded Software

TitleAn Empirical Study of Comparison of Code Metric Aggregation Methods–on Embedded Software
Publication TypeConference Paper
Year of Publication2019
AuthorsSong, Zekun, Wang, Yichen, Zong, Pengyang, Ren, Zhiwei, Qi, Di
Conference Name2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C)
Date Publishedjul
ISBN Number978-1-7281-3925-8
KeywordsConferences, data aggregation, econometric methods, econometrics, embedded software projects, Embedded systems, metric distribution, metric distribution methods, project management, pubcrawl, reliability assessment model, security, security metrics, software code metric aggregation, software code metrics, software management, software metrics, software quality, software reliability, software reliability evaluation, statistical value methods

How to evaluate software reliability based on historical data of embedded software projects is one of the problems we have to face in practical engineering. Therefore, we establish a software reliability evaluation model based on code metrics. This evaluation technique requires the aggregation of software code metrics into project metrics. Statistical value methods, metric distribution methods, and econometric methods are commonly-used aggregation methods. What are the differences between these methods in the software reliability evaluation process, and which methods can improve the accuracy of the reliability assessment model we have established are our concerns. In view of these concerns, we conduct an empirical study on the application of software code metric aggregation methods based on actual projects. We find the distribution of code metrics for the projects under study. Using these distribution laws, we optimize the aggregation method of code metrics and improve the accuracy of the software reliability evaluation model.

Citation Keysong_empirical_2019