Agile risk management using software agents

Odzaly, Edzreena Edza; Greer, Des; Stewart, Darryl

doi:10.1007/s12652-017-0488-2

Cited by 32 publications

(18 citation statements)

References 34 publications

(34 reference statements)

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“…It can be seen in this table that 4 primary studies carried out their evaluation by means of experiments, and 17 did so using case studies. amongst these studies, it was observed that articles [57,64], and [69] had a validation plan, which allows us to infer that this is a research field where various advances have been made, but where there needs to be greater rigour and adherence to formal guidelines; this would be achieved if correct evaluation were carried out to verify the contribution and suitability of each of the papers.…”

Section: Rq6: What Methods Of Scientific Validation Have Been Used Inmentioning

confidence: 99%

“…This is also the case with the model and prototype tool for software risk management, designed by Keshlaf y Hashim, and known as SoftRisk [97]. For agile projects, a lightweight approach supported by a prototype tool was discovered, in the work of Odzaly et al [69]; its aim is to reduce human effort in risk management tasks by using software agents to carry out the identification, assessment and monitoring of risk. Elzamly et al [65] propose a methodological framework for the software life cycle; it is based on statistical techniques and on extracting information that offers support in software risk management.…”

Section: Rq1: What Strategies Have Been Defined For Risk Management Imentioning

confidence: 99%

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Risk management in the software life cycle: A systematic literature review

Masso

Pino

Pardo

et al. 2020

Computer Standards & Interfaces

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Risk management (RM) plays a key role in project management, as it allows identification and prompt management of threats that may arise during project execution. Furthermore, project management within the software industry is evolving rapidly nowadays, a fact that implies new challenges, because the emergence and use of fresh approaches has brought a greater degree of complexity to the RM process. The objective of this paper is to carry out a systematic literature review (SLR) in the field of software risk, in an attempt to characterize and present the state of the art of this field, identifying gaps and opportunities for further research. From the analysis of the results of this SLR it could be observed that interest on the part of the scientific community has turned away from the definition of research work that addressed an integrated risk management process, to pay attention to work that concentrates on specific activities of this process. It was also possible to see that there is a clear lack of scientific rigour as regards the process of validation in the different studies, and a deficiency in the use of standards or of de facto models to define these.

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Section: Rq6: What Methods Of Scientific Validation Have Been Used Inmentioning

confidence: 99%

Section: Rq1: What Strategies Have Been Defined For Risk Management Imentioning

confidence: 99%

Risk management in the software life cycle: A systematic literature review

Masso

Pino

Pardo

et al. 2020

Computer Standards & Interfaces

View full text Add to dashboard Cite

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“…The clarity regarding the establishment and evaluation of the myriad of decisions from software feature inception to product delivery and refinement is lacking [5]. • The standard or common method of risk management process and tool are not available in software development situations [12].…”

Section: Challengesmentioning

confidence: 99%

“…There are five categories of the risks -'Project Management,' 'Software Development Life Cycle (SDLC),' 'External Stakeholder Collaboration,' 'Group Awareness' and 'Technology Set-up,' -which are mapped to the Leavitt model for betterment of organizational changes. The idea behind mapping is that it facilitates us to identify the organizational aspects that manage the risks buried in DAD projects [8,11,12]. In contrast, ASD makes use of an iterative approach for constructing the software and intends to minimize the time taken for development, prioritizing value.…”

Section: Introductionmentioning

confidence: 99%

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Distributed cat modeling based agile framework for software development

Prakash

Viswanathan

2019

Sādhanā

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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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