Description
A well-defined Software Complexity Theory which captures the Cognitive means of algorithmic information comprehension is needed in the domain of cognitive informatics & computing. The existing complexity heuristics are vague and empirical. Industrial software is a combination of algorithms implemented. However, it would be wrong to conclude that algorithmic space and time complexity is software complexity. An algorithm with multiple lines of pseudocode might sometimes be simpler to understand that the one with fewer lines. So, it is crucial to determine the Algorithmic Understandability for an algorithm, in order to better understand Software Complexity. This work deals with understanding Software Complexity from a cognitive angle. Also, it is vital to compute the effect of reducing cognitive complexity. The work aims to prove three important statements. The first being, that, while algorithmic complexity is a part of software complexity, software complexity does not solely and entirely mean algorithmic Complexity. Second, the work intends to bring to light the importance of cognitive understandability of algorithms. Third, is about the impact, reducing Cognitive Complexity, would have on Software Design and Development.
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Details
Title
- Cognitive software complexity analysis
Contributors
- Mannava, Manasa Priyamvada (Author)
- Ghazarian, Arbi (Thesis advisor)
- Gaffar, Ashraf (Committee member)
- Bansal, Ajay (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2016
Subjects
Resource Type
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Note
- thesisPartial requirement for: M.S., Arizona State University, 2016
- bibliographyIncludes bibliographical references (page 32)
- Field of study: Computer science
Citation and reuse
Statement of Responsibility
by Manasa Priyamvada Mannava