Software Usage Model Research Articles

Research on building software usage model based on UML model

Software usage model can be used as a guide when generate reliability test cases and it helps to evaluate the reliability of the software. Recent researches of deriving Markov Chain usage model from UML Model are mostly based on the UML sequence diagram and UML component diagram. But there are some problems with the existing methods: for some large software systems, there are many kinds of users who use the software in different ways, while a general usage model is not targeted and not suitable for all users. For this reason,this paper puts forward a new method to construct user-based software usage model. The method constructs usage model according to the UML activity diagram and UML use-case diagram, the model constructed by this method is user-based: the model describes, for every kind of users, the specific interacting process between the user and the system. What’s more, the model can be used to guide test cases generation.

A constraint-based approach to the representation of software usage models

Software usage models are the basis for statistical testing. They derive their structure from specifications and their probabilities from evolving knowledge about the intended use of the software product. The evolving knowledge comes from developers, customers and testers of the software system in the form of relationships that should hold among the parameters of a model. When software usage models are encoded as Markov chains, their structure can be represented by a system of linear constraints, and many of the evolving relationships among model parameters can be represented by convex constraints. Given a Markov chain usage model as a system of convex constraints, mathematical programming can be used to generate the Markov chain transition probabilities that represent a specific software usage model.

Representation and optimization of software usage models with non-Markovian state transitions

We extend Markov usage models by admitting non-Markovian transitions between states. The suggested description syntax preserves the visualization capacities of Markov models and, although it is kept simple, provides the computational power of a universal programming language. It is shown that a previously introduced optimization technique for computing optimal test transition probabilities can be generalized to the presented framework. A medium-size example from a real-world application illustrates the approach.

Generating transition probabilities to support model-based software testing

Markov chain usage models support test planning, test automation, and analysis of test results. In practice, transition probabilities for Markov chain usage models are often specified using a cycle of assigning, verifying, and revising specific values for individual transition probabilities. For large systems, such an approach can be difficult for a variety of reasons. We describe an improved approach that represents transition probabilities by explicitly preserving the information concerning test objectives and the relationships between transition probabilities in a format that is easy to maintain and easy to analyze. Using mathematical programming, transition probabilities are automatically generated to satisfy test management objectives and constraints. A more mathematical treatment of this approach is given in References [1] (Poore JH, Walton GH, Whittaker JA. A constraint-based approach to the representation of software usage models. Information and SoftwareTechnology 2000; at press) and [2] (Walton GH. Generating transition probabilities for Markov chain usage models. PhD Thesis, University of Tennessee, Knoxville, TN, May 1995.). In contrast, this paper is targeted at the software engineering practitioner, software development manager, and test manager. This paper also adds to the published literature on Markov chain usage modeling and model-based testing by describing and illustrating an iterative process for usage model development and optimization and by providing some recommendations for embedding model-based testing activities within an incremental development process. Copyright © 2000 John Wiley & Sons, Ltd.

Statistical testing of software based on a usage model

AbstractIn statistical testing, a model is developed to characterize the population of uses of the software, and the model is used to generate a statistically correct sample of all uses of the software. A software ‘usage model’ characterizes the population of intended uses of the software in the intended environment. Statistical testing based on a software usage model ensures that the failures that will occur most frequently in operational use will be found early in the testing cycle. The usage model is based on the software specification. The model can be developed in parallel with the software, thus shortening the elapsed time required to develop the deliver software.Usage modeling has been demonstrated to be an activity that improves the specification, gives an analytical description of the specification, quantifies the testing costs and, with statistical testing, provides a basis from which inferences of software reliability may be made. This paper describes the justification for statistical testing of software using a usage model, describes procedures for developing and using a usage model and discusses several usage modeling issues and recent advances in usage model applications.