Cyclomatic Complexity Density and Software Maintenance Productivity
IEEE Transactions on Software Engineering
Handbook of software reliability engineering
Using Simplicity to Control Complexity
IEEE Software
Quantitative Analysis of Faults and Failures in a Complex Software System
IEEE Transactions on Software Engineering
Revisiting Measurement of Software Complexity
APSEC '96 Proceedings of the Third Asia-Pacific Software Engineering Conference
METRICS '96 Proceedings of the 3rd International Symposium on Software Metrics: From Measurement to Empirical Results
Breeding Software Test Cases for Complex Systems
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 9 - Volume 9
Software Information Leaks: A Complexity Perspective
ICECCS '04 Proceedings of the Ninth IEEE International Conference on Engineering Complex Computer Systems Navigating Complexity in the e-Engineering Age
Spatial Complexity Metrics: An Investigation of Utility
IEEE Transactions on Software Engineering
Designing and managing evolving systems using a MAS product line approach
Science of Computer Programming
A Replicated Quantitative Analysis of Fault Distributions in Complex Software Systems
IEEE Transactions on Software Engineering
An Era of Change-Tolerant Systems
Computer
IEEE Transactions on Software Engineering
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A model of software complexity and reliability is developed. It uses an evolutionary process to transition from one software system to the next, while complexity metrics are used to predict the reliability for each system. Our approach is experimental, using data pertinent to the NASA satellite systems application environment. We do not use sophisticated mathematical models that may have little relevance for the application environment. Rather, we tailor our approach to the software characteristics of the software to yield important defect-related predictors of quality. Systems are tested until the software passes defect presence criteria and is released. Testing criteria are based on defect count, defect density, and testing efficiency predictions exceeding specified thresholds. In addition, another type of testing efficiency--a directed graph representing the complexity of the software and defects embedded in the code--is used to evaluate the efficiency of defect detection in NASA satellite system software. Complexity metrics were found to be good predictors of defects and testing efficiency in this evolutionary process.