Network analysis has been successfully applied in software engineering to understand structural effects in the software. System software is represented as a network graph, and network metrics are used to analyse syste...
详细信息
Network analysis has been successfully applied in software engineering to understand structural effects in the software. System software is represented as a network graph, and network metrics are used to analyse system quality. This study is motivated by a previous study, which represents the softwarestructure as three-node subgraphs and empirically identifies that softwarestructure continuously evolves over system releases. Here, the authors extend the previous study to analyse the relation of structural evolution and the defectiveness of subgraphs in the software network graph. This study investigates the behaviour of subgraph defects through softwareevolution and their impact on system defectiveness. Statistical methods were used to study subgraph defectiveness across versions of the systems and across subgraph types. The authors conclude that software versions have similar behaviours in terms of average subgraph type defectiveness and subgraph frequency distributions. However, different subgraph types have different defectiveness distributions. Based on these conclusions, the authors motivate the use of subgraph-based software representation in defect predictions and software modelling. These promising findings contribute to the further development of the software engineering discipline and help software developers and quality management in terms of better modelling and focusing their testing efforts within the code structure represented by subgraphs.
As evolving complex systems have become the central part of almost every human activity, their reliability is the key property for their successful application, especially with the emerging Internet of Services concep...
详细信息
ISBN:
(纸本)9781450348997
As evolving complex systems have become the central part of almost every human activity, their reliability is the key property for their successful application, especially with the emerging Internet of Services concept. There are many quantitative mathematical models, the so called reliability growth models, aiming to predict and estimate reliability of software systems based on the failure count time series. This paper suggests a novel and still unexplored qualitative approach to understand failure time series studying its topological features and their influence on failure distributions, thus affecting mission critical system properties, among which is reliability. To illustrate the new ideas, we analyse here the time series failure data of evolving software systems across the system versions for two open source software systems and one mission critical industrial software system, and discuss their topological relations and behaviour. We conclude that topological analysis might be useful for characterising software system behaviour early enough and for early characterization of system reliability that may contribute to software reliability modeling.
暂无评论