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At least 19 records

Measurement-based reliability/performability models

Measurement-based models based on real error-data collected on a multiprocessor system are described. Model development from the raw error-data to the estimation of cumulative reward is also described. A workload/reliability model is developed based on low-level error and resource usage data collected on an IBM 3081 system during its normal operation in order to evaluate the resource usage/error/recovery process in a large mainframe system. Thus, both normal and erroneous behavior of the system are modeled. The results provide an understanding of the different types of errors and recovery processes. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A sensitivity analysis is performed to investigate the significance of using a semi-Markov process, as opposed to a Markov process, to model the measured system.

Hsueh, Mei-Chen↗

A measurement-based model of software reliability in a production environment

In this paper, a semi-Markov model is built to describe the software error and recovery process in a large mainframe system. The model is based on low-level error data from the MVS operating system running on an IBM 3081 machine. The semi-Markov model developed provides a quantification of system error characteristics and the interaction between different types of errors. As an example, a detailed model is provided, and an analysis is made of multiple errors, which constitute approximately an 17 percent of all software errors and result in considerable recovery overhead.

Hsueh, M. C.↗

A measurement-based performability model for a multiprocessor system

A measurement-based performability model based on real error-data collected on a multiprocessor system is described. Model development from the raw errror-data to the estimation of cumulative reward is described. Both normal and failure behavior of the system are characterized. The measured data show that the holding times in key operational and failure states are not simple exponential and that semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different failure types and recovery procedures.

Ilsueh, M. C.↗

Performability modeling based on real data: A casestudy

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different types of errors.

Hsueh, M. C.↗

Performability modeling based on real data: A case study

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of apparent types of errors.

Hsueh, M. C.↗

A process improvement model for software verification and validation

We describe ongoing work at the NASA Independent Verification and Validation (IV&V) Facility to establish a process improvement model for software verification and validation (V&V) organizations. This model, similar to those used by some software development organizations, uses measurement-based techniques to identify problem areas and introduce incremental improvements. We seek to replicate this model for organizations involved in V&V on large-scale software development projects such as EOS and Space Station. At the IV&V Facility, a university research group and V&V contractors are working together to collect metrics across projects in order to determine the effectiveness of V&V and improve its application. Since V&V processes are intimately tied to development processes, this paper also examines the repercussions for development organizations in large-scale efforts.

Callahan, John↗

A process improvement model for software verification and validation

We describe ongoing work at the NASA Independent Verification and Validation (IV&V) Facility to establish a process improvement model for software verification and validation (V&V) organizations. This model, similar to those used by some software development organizations, uses measurement-based techniques to identify problem areas and introduce incremental improvements. We seek to replicate this model for organizations involved in V&V on large-scale software development projects such as EOS and space station. At the IV&V Facility, a university research group and V&V contractors are working together to collect metrics across projects in order to determine the effectiveness of V&V and improve its application. Since V&V processes are intimately tied to development processes, this paper also examines the repercussions for development organizations in large-scale efforts.

Callahan, John↗

The relationship between wind vector and normalized radar cross section used to derive Seasat-A Satellite Scatterometer winds

The Seasat-A Satellite Scatterometer (SASS) ocean normalized radar cross section (NRCS) dependence on the 19.5-m neutral stability wind vector may be specified as a function of radar incidence angle, the angle between wind direction and radar azimuth, and the neutral stability wind speed expressed in m/sec at a height of 19.5 m. An account is given of the development of models both expressing this relationship and providing the basis of inversion of NRCS to SASS winds, from initially aircraft scatterometer measurement-based forms to three Seasat field-validation experiments which furnish model NRCS versus surface windspeed data for comparison with SASS data.

Schroeder, L. C.↗

Failure analysis and modeling of a multicomputer system

This thesis describes the results of an extensive measurement-based analysis of real error data collected from a 7-machine DEC VaxCluster multicomputer system. In addition to evaluating basic system error and failure characteristics, we develop reward models to analyze the impact of failures and errors on the system. The results show that, although 98 percent of errors in the shared resources recover, they result in 48 percent of all system failures. The analysis of rewards shows that the expected reward rate for the VaxCluster decreases to 0.5 in 100 days for a 3 out of 7 model, which is well over a 100 times that for a 7-out-of-7 model. A comparison of the reward rates for a range of k-out-of-n models indicates that the maximum increase in reward rate (0.25) occurs in going from the 6-out-of-7 model to the 5-out-of-7 model. The analysis also shows that software errors have the lowest reward (0.2 vs. 0.91 for network errors). The large loss in reward rate for software errors is due to the fact that a large proportion (94 percent) of software errors lead to failure. In comparison, the high reward rate for network errors is due to fast recovery from a majority of these errors (median recovery duration is 0 seconds).

Subramani, Sujatha Srinivasan↗

Failure analysis and modeling of a VAXcluster system

This paper discusses the results of a measurement-based analysis of real error data collected from a DEC VAXcluster multicomputer system. In addition to evaluating basic system dependability characteristics such as error and failure distributions and hazard rates for both individual machines and for the VAXcluster, reward models were developed to analyze the impact of failures on the system as a whole. The results show that more than 46 percent of all failures were due to errors in shared resources. This is despite the fact that these errors have a recovery probability greater than 0.99. The hazard rate calculations show that not only errors, but also failures occur in bursts. Approximately 40 percent of all failures occur in bursts and involved multiple machines. This result indicates that correlated failures are significant. Analysis of rewards shows that software errors have the lowest reward (0.05 vs 0.74 for disk errors). The expected reward rate (reliability measure) of the VAXcluster drops to 0.5 in 18 hours for the 7-out-of-7 model and in 80 days for the 3-out-of-7 model.

Tang, Dong↗

Understanding and Predicting the Process of Software Maintenance Releases

One of the major concerns of any maintenance organization is to understand and estimate the cost of maintenance releases of software systems. Planning the next release so as to maximize the increase in functionality and the improvement in quality are vital to successful maintenance management. The objective of this paper is to present the results of a case study in which an incremental approach was used to better understand the effort distribution of releases and build a predictive effort model for software maintenance releases. This study was conducted in the Flight Dynamics Division (FDD) of NASA Goddard Space Flight Center(GSFC). This paper presents three main results: 1) a predictive effort model developed for the FDD's software maintenance release process; 2) measurement-based lessons learned about the maintenance process in the FDD; and 3) a set of lessons learned about the establishment of a measurement-based software maintenance improvement program. In addition, this study provides insights and guidelines for obtaining similar results in other maintenance organizations.

Basili, Victor↗

Software risk management through independent verification and validation

Software project managers need tools to estimate and track project goals in a continuous fashion before, during, and after development of a system. In addition, they need an ability to compare the current project status with past project profiles to validate management intuition, identify problems, and then direct appropriate resources to the sources of problems. This paper describes a measurement-based approach to calculating the risk inherent in meeting project goals that leverages past project metrics and existing estimation and tracking models. We introduce the IV&V Goal/Questions/Metrics model, explain its use in the software development life cycle, and describe our attempts to validate the model through the reverse engineering of existing projects.

Callahan, John R.↗

Performance seeking control excitation mode

Flight testing of the performance seeking control (PSC) excitation mode was successfully completed at NASA Dryden on the F-15 highly integrated digital electronic control (HIDEC) aircraft. Although the excitation mode was not one of the original objectives of the PSC program, it was rapidly prototyped and implemented into the architecture of the PSC algorithm, allowing valuable and timely research data to be gathered. The primary flight test objective was to investigate the feasibility of a future measurement-based performance optimization algorithm. This future algorithm, called AdAPT, which stands for adaptive aircraft performance technology, generates and applies excitation inputs to selected control effectors. Fourier transformations are used to convert measured response and control effector data into frequency domain models which are mapped into state space models using multiterm frequency matching. Formal optimization principles are applied to produce an integrated, performance optimal effector suite. The key technical challenge of the measurement-based approach is the identification of the gradient of the performance index to the selected control effector. This concern was addressed by the excitation mode flight test. The AdAPT feasibility study utilized the PSC excitation mode to apply separate sinusoidal excitation trims to the controls - one aircraft, inlet first ramp (cowl), and one engine, throat area. Aircraft control and response data were recorded using on-board instrumentation and analyzed post-flight. Sensor noise characteristics, axial acceleration performance gradients, and repeatability were determined. Results were compared to pilot comments to assess the ride quality. Flight test results indicate that performance gradients were identified at all flight conditions, sensor noise levels were acceptable at the frequencies of interest, and excitations were generally not sensed by the pilot.

Schkolnik, Gerard↗

File Usage Analysis and Resource Usage Prediction: a Measurement-Based Study

A probabilistic scheme was developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The coefficient of correlation between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.-S.↗

Predictability of process resource usage: A measurement-based study of UNIX

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.↗

Predictability of process resource usage - A measurement-based study on UNIX

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient betweeen the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82 percent of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Devarakonda, Murthy V.↗

A measurement-based study of concurrency in a multiprocessor

A systematic measurement-based methodology for characterizing the amount of concurrency present in a workload, and the effect of concurrency on system performance indices such as cache miss rate and bus activity are developed. Hardware and software instrumentation of an Alliant FX/8 was used to obtain data from a real workload environment. Results show that 35% of the workload is concurrent, with the concurrent periods typically using all available processors. Measurements of periods of change in concurrency show uneven usage of processors during these times. Other system measures, including cache miss rate and processor bus activity, are analyzed with respect to the concurrency measures. Probability of a cache miss is seen to increase with concurrency. The change in cache miss rate is much more sensitive to the fraction of concurrent code in the worklaod than the number of processors active during concurrency. Regression models are developed to quantify the relationships between cache miss rate, bus activity, and the concurrency measures. The model for cache miss rate predicts an increase in the median miss rate value as much as 300% for a 100% increase in concurrency in the workload.

Mcguire, Patrick John↗

Measurement-based reliability prediction methodology

In the past, analytical and measurement based models were developed to characterize computer system behavior. An open issue is how these models can be used, if at all, for system design improvement. The issue is addressed here. A combined statistical/analytical approach to use measurements from one environment to model the system failure behavior in a new environment is proposed. A comparison of the predicted results with the actual data from the new environment shows a close correspondence.

Linn, Linda Shen↗