Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Software Engineering: A Practitioner's Approach
Software Engineering: A Practitioner's Approach
Function Point Analysis: Difficulties and Improvements
IEEE Transactions on Software Engineering
Measurement of the Cognitive Functional Complexity of Software
ICCI '03 Proceedings of the 2nd IEEE International Conference on Cognitive Informatics
A Cognitive Complexity Metric Based on Category Learning
ICCI '03 Proceedings of the 2nd IEEE International Conference on Cognitive Informatics
A modified cognitive information complexity measure of software
ACM SIGSOFT Software Engineering Notes
Evaluating Cognitive Information Complexity Measure
ECBS '06 Proceedings of the 13th Annual IEEE International Symposium and Workshop on Engineering of Computer Based Systems
ACM SIGSOFT Software Engineering Notes
IEEE Transactions on Software Engineering
A complexity measure based on information contained in the software
SEPADS'06 Proceedings of the 5th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems
The Research on Software Metrics and Software Complexity Metrics
IFCSTA '09 Proceedings of the 2009 International Forum on Computer Science-Technology and Applications - Volume 01
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There has been a continuous effort to estimate software complexity but very little established methods exist that can estimate the complexity of the software before it is written. Since a high quality Software Requirement Specification (SRS) is a pre requisite for high quality software, this work attempts to empirically demonstrate that the complexity of the code can be determined based on its IEEE software requirement specification document (IEEE 830-1998). Existing complexity measures established are based on the code and the cognitive metrics value of the software. This may require recodingleading to loss of time and cost. Considering the shortcoming of code-based approaches, our proposed approach is able to compute the complexity of yet-to-be-written software immediately after freezing the requirement in the Software development Lifecycle (SDLC) process. The proposedcomplexity measure compares well with established complexity measures like Halstead, Mc Cabe, KLCID, CFS and CICM. Results obtained show that the complexity values are comparable with other established measures. The robustness of our complexity measure is established by evaluating our measure against Weyuker properties.