Distributed cat modeling based agile framework for software development

被引:0
作者
B Prakash
V Viswanathan
机构
[1] Vellore Institute of Technology,
来源
Sādhanā | 2019年 / 44卷
关键词
Software development; catastrophic model; distributed computing; agile model; software quality;
D O I
暂无
中图分类号
学科分类号
摘要
Software development is a challenging process that requires in-depth understanding and an effective model such that the developed software inherits good quality and reliability, and attains customer satisfaction towards achieving the goals successfully. The effectiveness of the software is enabled by modifying the operating modules of the software through a model, like agility. In this paper, the catastrophic and distributed computing models are integrated into the software development process. The proposed model is termed as a distributed cat model that is developed with the aim to handle the risk factors engaged in various developing stages of the agile model. The risk factors that affect the communication, planning, release, design, coding and testing modules of the agile modules are deeply learned and executed such that the risk factors are tackled by various modules present in the proposed distributed cat model. The effectiveness of the proposed model is analysed based on the performance metrics such as Index of Integration (IoI) and Usability Goals Achievement Metric (UGAM), for which five products, including the hotel management system, Customer Relationship Management system (CRM), rainfall prediction system, temperature monitoring system and meta-search system, are employed. The analysis is performed using the parameters like mean difference, variance, standard deviation and correlation coefficient. The result proves that the proposed model offers a great positive deviation contributing to high degree of performance in software development.
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  • [1] Kulkarni RH(2017)Integration of artificial intelligence activities in software development processes and measuring the effectiveness of integration IET Softw. 11 18-26
  • [2] Padmanabham P(2014)Influences on regression testing strategies in agile software development environments Softw. Qual. J. 22 717-739
  • [3] Parsons D(2009)Research commentary—weighing the benefits and costs of flexibility in making software: toward a contingency theory of the determinants of development process design Inf. Syst. Res. 20 462-477
  • [4] Susnjak T(2017)Examining decision characteristics & challenges for agile software development J. Syst. Softw. 131 248-265
  • [5] Lange M(2018)Exploring software development at the very large-scale: a revelatory case study and research agenda for agile method adaptation Empir. Softw. Eng. 23 490-520
  • [6] Austin RD(2017)A risk management framework for distributed agile projects Inf. Softw. Technol. 85 1-15
  • [7] Devin L(2015)Categorization of risk factors for distributed agile projects Inf. Softw. Technol. 58 373-387
  • [8] Drury-Grogan ML(2017)An evidence-based risk-oriented V-model methodology to develop ambient intelligent medical software J. Reliab. Intell. Environ. 3 41-53
  • [9] Conboy K(2018)Agile risk management using software agents J. Ambient Intell. Humaniz. Comput. 9 1-19
  • [10] Acton T(2017)Managing the requirements flow from strategy to release in large-scale agile development: a case study at Ericsson Empir. Softw. Eng. 22 2892-2936