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An Efficient Framework for Minimizing Project Complexity using Periodic Software Project Standard based Linear Ranking
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 104 - Number 8 |
| Year of Publication: 2014 |
| Authors: Nadanasundaram P V, K.iyakutti |
10.5120/18221-9324
|
Nadanasundaram P V, K.iyakutti . An Efficient Framework for Minimizing Project Complexity using Periodic Software Project Standard based Linear Ranking. International Journal of Computer Applications. 104, 8 ( October 2014), 8-14. DOI=10.5120/18221-9324
Abstract
Application knowledge, skills, and procedure related to software tools have to be examined in a regular basis to identify the complexity related to project management. An Integrated Framework for Risk Response Planning (IF-RRP) was developed for providing support in decision making during project response risk planning. The method, IF-RRP used sequential forward selection greedy algorithm and genetic algorithm and analyzed risk propagation behavior. However, IF-RRP using Structure Matrix though constructed the representative project risk but did not considered the project management on multiple related projects. Speculative Analysis Technique using Awareness Tools (SAT-AT) diagnosed important types of conflicts and risks in the early stage using a tool, Crystal between collaborating team members and classified the risks for maintaining software. Even though, SAT-AT failed in analyzing the complexity of the project in an earlier stage. To reduce the software project complexity on multiple related projects, Periodic Software Project Standard measure based Linear Ranking (PSPS-LR) framework is proposed in this work. Software project on each module is checked to detect the complexity of the software project at an earlier stage. Initially, Periodic Software Project Standard is measured based on the standard matrix and assigning the weight value to the standard matrix. A Deterministic Periodic Quantitative Model based on weighted mean is developed in PSPS-LR framework for the efficient ranking of software project module periodically. Secondly, PSPS-LR framework performs the effective ranking of software project using linear ranking. Linear ranking is performed using Linear algebra ?PS?^2-LR framework to assess larger software project with varying module size and therefore to easily measure the complexity ratio. The periodic weight value of the standard matrix together with linear transformation easily computes the project complexity of multiple related projects. Experiment is conducted on factors such as project complexity measure ratio, computational complexity and ranking effectiveness based on the project management level.
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