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An Improved SRS Document Based Software Complexity Estimation and Its Robustness Analysis

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Part of the Communications in Computer and Information Science book series (CCIS,volume 142)

Abstract

Complexity measures are used to predict critical information about reliability and maintainability of software systems from analysis of the source code. Complexity measures also provide continuous feedback during a software project to help control the development process. During testing and maintenance, it provides detailed information about software modules to help pinpoint areas of potential instability. The various complexity measures established so far are based on code and it is too late to perform this activity because a major part of investment has already taken place. Although it is established that a high quality SRS is pre requisite for high quality software, but software complexity estimation based on SRS document has not been properly researched and we find little proposals. Hence the work presented in this paper attempts to empirically demonstrate that the complexity of the code to be produced can be closely estimated based on IEEE software requirement specification document (IEEE 830-1998). Results obtained shows that the complexity values obtained from improved requirement based complexity (I-RBC) are comparable with other established measures and hence the complexity of the software to be produced could be computed from its SRS document. Its robustness is established by strictly evaluating and comparing proposed measure against Weyuker properties.

Keywords

  • Requirement Based Complexity
  • Input Output Complexity
  • Product Complexity
  • Personal Complexity Attributes
  • Interface Complexity
  • User Location Complexity
  • Requirement Complexity

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Ashish, S., Kushwaha, D.S. (2011). An Improved SRS Document Based Software Complexity Estimation and Its Robustness Analysis. In: Das, V.V., Stephen, J., Chaba, Y. (eds) Computer Networks and Information Technologies. CNC 2011. Communications in Computer and Information Science, vol 142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19542-6_18

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  • DOI: https://doi.org/10.1007/978-3-642-19542-6_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19541-9

  • Online ISBN: 978-3-642-19542-6

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