Reliability Growth Enhancing Defense System Reliability (2015) / Chapter Skim
Currently Skimming:
9 Software Reliability Growth
9 Software Reliability Growth
Pages 117-134
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 117... ...
This separate treatment is particularly relevant to software failures given the different nature of software and hardware reliability. Chapter 4 on hardware reliability growth is primarily relevant to growth that occurs during full-system testing, which is relevant to the 117
|
From page 118... ...
SOFTWARE RELIABILITY GROWTH MODELING Classic Design Models Software reliability growth models have, at best, limited use for making predictions as to the future reliability of a software system in development for several reasons. Most important, the pattern of reliability growth evident during the development of software systems is often not monotonic because corrections to address defects will at times introduce additional defects.
|
From page 119... ...
Finally, a large group of software reliability growth models are described by nonhomogenous Poisson processes (for a description, see Yamada and Osaki, 1985) : this group includes Musa (e.g., Musa et al., 1987)
|
From page 120... ...
Performance Metrics and Prediction Models An alternative approach to reliability growth modeling for determining whether a software design is likely to lead to a reliable software system is to rely on performance metrics. Such metrics can be used in tracking software development and as input into decision rules on actions such as accepting subsystems or systems for delivery.
|
From page 121... ...
The testing effort is evaluated on the basis of how many of these injected defects are found during testing. Using the number of injected defects remaining, an estimate of the reliability based on the quality of the testing effort is computed using capture-recapture methods.
|
From page 122... ...
. Basic Execution Time Model In this model, the failure rate function at time t is given by: l(t)
|
From page 123... ...
This is a nonhomogeneous Poisson process model with mean function β t m (t )
|
From page 124... ...
These factors are all straightforward to measure, and they can be supplied by the contractor throughout development. METRICS-BASED MODELS Metrics-based models are a special type of software reliability growth model that have not been widely used in defense acquisition.
|
From page 125... ...
code churn measures, (2) code complexity measures, (3)
|
From page 126... ...
demonstrated the use of relative code churn measures (normalized values of the various measures obtained during the evolution of the system) to predict defect density at statistically significant levels.
|
From page 127... ...
For Eclipse, the open source integrated development environment, they found that using compiler packages resulted in a significantly higher failure- roneness (71 percent) than using graphical user interface packages p
|
From page 128... ...
In the case of metrics-based reliability models, the independent variables can be any of the (combination of) measures ranging from code churn and code complexity to people and social network measures.
|
From page 129... ...
In this case, support vector machines transform the input data into a higher dimensional space using a nonlinear mapping. In this new space, the data are then linearly separated (for details, see Han and Kamber, 2006)
|
From page 130... ...
The concern is that if insufficient software testing is carried out during the early stages of developmental testing, then addressing software problems discovered in later stages of developmental testing or in operational testing will be much more expensive.1 As discussed in National Research Council (2006) , to adequately test software, given the combinatorial complexity of the sequence of statements activated as a function of possible inputs, one is obligated to use some form of automated test generation, with high code coverage assessed using one of the various coverage metrics proposed in the research literature.
|
From page 131... ...
. However, operational testing of a software system can raise an issue known as fault masking, whereby the occurrence of a fault prevents the software system from continuing and therefore misses faults that are conditional on the previous code functioning properly.
|
From page 132... ...
132 FIGURE 9-2 Analytics dashboards. SOURCE: Selby (2009, p.
|
From page 133... ...
FIGURE 9-3 Example of a specific context of an analytics dashboard. SOURCE: Selby (2009)
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.