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In the last decade, empirical studies on object-oriented design metrics have shown some of them to be useful for predicting the fault-proneness of classes in object-oriented software systems. This research did not, however, distinguish among faults according to the severity of impact. It would be valuable to know how object-oriented design metrics and class fault-proneness are related when fault severity is taken into account. In this paper, we use logistic regression and machine learning methods to empirically investigate the usefulness of object-oriented design metrics, specifically, a subset of the Chidamber and Kemerer suite, in predicting fault-proneness when taking fault severity into account. Our results, based on a public domain NASA data sat, indicate that 1 ) most of these design metrics are statistically related to fault-proneness of classes across fault severity, and 2) the prediction capabilities of the investigated metrics greatly depend on the severity of faults. More specifically, these design metrics are able to predict low severity faults in fault-prone classes better than high severity faults in fault-prone classes. [ABSTRACT FROM AUTHOR]

The Tropospheric Emission Spectrometer (TES) is one of four instruments onboard the Earth Observing System Aura satellite. The TES Science Investigator-led Processing System (SIPS) Facility performs production processing of all TES science data. When the TES project was proposed in 1988, its science algorithms were still evolving, but it was already understood to be at least two orders of magnitude more complex than its NASA predecessor, the Atmospheric Trace Molecule Spectroscopy (ATMOS) instrument. In addition, the expected data volume of the TES instrument would be more than 1000 times greater than that of ATMOS. Development of the TES SIPS faced a number of technical challenges. It also would have been impractical and prohibitively costly to develop the TES SIPS facility without carefully deploying the computing technologies that have recently become available. This paper describes how the challenges were met in the development of the facility by making use of evolving hardware technology and software refinement. The process revealed that the architecture of the hardware implemented was highly dependent upon the processing algorithm, and a stable algorithm was needed early in the hardware development process for performance analysis and benchmarking. [ABSTRACT FROM AUTHOR]

Software-driven hardware configurations account for the majority of modern safety-critical complex systems. The often costly failures of such systems can be attributed to software specific, hardware specific, or software/hardware interaction failures. The understanding of how failures propagate in such complex systems might provide critical information to designers, because, while a software component may not fail in terms of loss of function, a software operational state can cause an associated hardware failure. The least expensive phase of the product life cycle to address failures is during the design stage. This research presents a means to evaluate how a combined software/hardware system behaves and how such failures propagate to result in potential failures downstream, during the conceptual design stage. In particular, this paper proposes the use of high-level system modeling and model-based reasoning approaches to model failure propagation in combined software-hardware systems, introducing the Function-Failure Identification and Propagation (FFIP) analysis framework to help formalize the design of safety-critical systems. The fact that the hardware and software designers do not share the same background, knowledge, methods, or language contributes significantly to software/hardware interaction failures. A high-level systems analysis method, such as FFIP, is geared toward the unification of language and modeling concepts and may help to more seamlessly bridge such a gap. The technique is applied to the design of the Reaction Control System Jet Selection of the NASA space shuttle to evaluate failure propagation within the Reaction Control System Jet selection, specifically for the redundancy management system. The paper concludes with the extensions and mappings to the software domain that are required for a truly integrated methodology. [ABSTRACT FROM AUTHOR]