A field study on root cause analysis of defects in space software

Using Orthogonal Defect Classification to characterize NoSQL database defects

“…The works belonging to Group II also perform empirical analyses, but the work has an additional goal, a second application, which is, most of the times, to use the ODC data for process improvement (in lato sensu). In this latter group of works, it is frequent to see the authors using the field data to perform root-cause analyses [12] or apply it within the scope of another proposal (e.g., fault injection) [9]. Our work fits directly in the former group.…”

“…Thus, the authors propose an adaptation of the taxonomy that is particularly suitable for critical systems, allowing for a more effective classification. Silva et al [12] carried out a root cause analysis on 1070 software defects belonging to the subsystems of four safety-critical space systems. The authors applied a version of ODC particularly tailored for the context and examined types of defects, impacts, and triggers.…”

“…Silva et al [31] use ODC as basis to classify critical systems engineering issues and propose an adaptation of the taxonomy. Silva et al [12] performed a root cause analysis on defects from safety-critical software systems. Morrisson et al [25] use ODC to characterize and understand the differences between the discovery and resolution of defects compared to vulnerabilities and Sotiropoulos et al [32] characterize bugs in robot middleware to understand which can be detected through simulation.…”

“…Understanding the nature of software defects (e.g., by using structured methods for defect classification [6]- [8]) can provide extremely useful information for developers, who can better focus their software verification efforts or, for instance, concentrate their development efforts in certain components or code areas known to be prone to a particular software defect type [6]. This kind of effort has been undertaken for many and very different types of software that operate in distinct domains, including browsers, games, operating systems, satellite software, business-critical applications, build systems, or machine learning software, just to name a few [9]- [12]. Many times, the general hypothesis placed is that the specificities involving the system (e.g., programming language, project nature and requirements, type and experience of the application development team) make it necessary for such specific analysis to take place.…”

A Bayesian Network Approach to Estimating Software Reliability of RSG-GAS Reactor Protection System

“…1 (2019) 43 -49 Atom Indonesia Journal homepage: http://aij.batan.go.id hardware faults occur due to aging or wearing out, but software faults causing a digital system failure are design fault introduced during the software development or maintenance phase [5]. A root cause analysis of the software defects based on the orthogonal defects classification in software development has been proposed [6]. It also has been identified that most of software failures are due to a design error and system loop holes which are not independent to human performance shaping factor [7,8].…”