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| Content Provider | ACM Digital Library |
|---|---|
| Author | Kushwaha, Dharmender Singh Sharma, Ashish |
| Abstract | 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. |
| Starting Page | 1 |
| Ending Page | 7 |
| Page Count | 7 |
| File Format | |
| ISSN | 01635948 |
| DOI | 10.1145/1838687.1838708 |
| Journal | ACM SIGSOFT Software Engineering Notes (SOEN) |
| Volume Number | 35 |
| Issue Number | 5 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 1979-04-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Product complexity Requirement based complexity Interface complexity Requirement complexity User location complexity Personal complexity attributes Input output complexity |
| Content Type | Text |
| Resource Type | Article |
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