A Survey of Dynamic Software Metrics <s> Munson and Khoshgoftar Metrics Suite <s> Revised and updated for professional software engineers, systems analysts and project managers, this highly acclaimed book provides key concepts of software reliability and practical solutions for measuring reliability. <s> BIB001 </s> A Survey of Dynamic Software Metrics <s> Munson and Khoshgoftar Metrics Suite <s> A relative complexity technique that combines the features of many complexity metrics to predict performance and reliability of a computer program is presented. Relative complexity aggregates many similar metrics into a linear compound metric that describes a program. Since relative complexity is a static measure, it is expanded by measuring relative complexity over time to find a program's functional complexity. It is shown that relative complexity gives feedback on the same complexity domains that many other metrics do. Thus, developers can save time by choosing one metric to do the work of many. > <s> BIB002 </s> A Survey of Dynamic Software Metrics <s> Munson and Khoshgoftar Metrics Suite <s> Both operational environment and source code complexity influence the reliability of software systems. The complex modules of software systems often contain a disproportionate number of faults. However, if in a given environment, the complex modules are rarely exercised, then few of these faults are likely to become expressed as failures. Different environments will exercise a system's modules differently. A system's dynamic complexity is high in an environment that exercises the system's complex modules with high probability. It is likely that one or more potential scenarios induce inordinately large dynamic complexity. Identifying these scenarios is the first step in assuring that they receive the testing time that they warrant. The paper presents two metrics which evaluate the dynamic complexity of systems and of subsystems in the intended operational environment. The authors' analyze two software systems using both dynamic metrics. > <s> BIB003
Munson and Khoshgoftar BIB003  estimate the dynamic complexity based on relative complexity of a module defined by them in BIB002 . The relative complexity of a module is obtained after classifying various complexity metrics in few independent complexity domains and then mapping these domains to a single metric, i.e., relative complexity, which characterizes the complexity of each module as a single value. Authors define dynamic complexity of a component as the product of the static relative complexity of the component and the probability of execution of that component. The probability of execution of components is based on actual traces of execution of the software obtained using profiling tools. Further, authors also present dynamic complexity metrics to quantify the dynamic complexity of sub-systems and systems. A system's dynamic complexity in a given environment is determined by its source code complexity and its operational profile in that environment. An operational profile characterizes a software system's environment in terms of the possible evaluations of input variables along with the probabilities of these inputs in that environment BIB001 . Let ρ ′ i be the relative complexity of module i. Then, the average complexity of the system having n modules is given by: However, in operation some modules would be referenced with greater probability than others. Thus, a system's dynamic complexity may be represented as follows: where p i is the probability of reference to module i in the operational environment and ρ ′ i is the relative complexity of module i. Thus, dynamic complexity of a system may be high in an environment that exercises complex functions having high probability of reference.