Figure 3
Source publication
The independent verification and validation (IV&V) process provides assessment to the project as to whether the developer’s artifacts have met a pre-determined “readiness” level. In practice, this is quantified using engineering judgment. We describe the application of Bayesian Belief networks (BBN) to analyze the readiness of software requirements...
Context in source publication
Context 1
... requirements for the non-volatile memory load component were expressed as use-cases and were supplemented with natural language descriptions. In addition to use cases, design stage models for the component were also available in terms unified modeling language (UML) constructs i.e. class diagrams, statechart diagrams, component diagrams, etc. Figure 3 shows the use case diagram of the module and figure 4 shows the natural language specifications corresponding to the module from the requirements specifications document. ...
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Citations
... This paper relies mainly on a previous work by the author and the co-researchers [12], on software assessment with a focus on Independent verification and validation (IV&V). However this paper broadens the scope of our work by proposing models and algorithms for the software development teams. ...
An important question for any project team is to assess if the project deliverables have met a pre-determined “readiness” level. This becomes even more important when a software development project gets close to a version release date. In practice, this is quantified using engineering judg- ment. We describe the application of Bayesian Belief networks (BBN) to analyze the readiness of software requirements speci- fications during software requirements review (SRR) mile- stone. The method proposed in this paper brings an additional level of rigor to the assessment process. Starting with a data- flow model of the Software requirements development model, we construct a BBN semi-automatically. Then, we provide a quantitative interpretation of the readiness level of software requirements in terms of artifact properties. The results of the preliminary assessment are used as evidence in the BBN to obtain a posterior distribution of readiness. We illustrate our approach by applying it to two example systems.
