Improving software development project team performance: a Web-based expert support system for project control

Dufner, Donna; Kwon, Ojoung; Doty, A.

doi:10.1109/hicss.1999.772622

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…The work of Dufner et al [26] discusses the PMA expert system (Project Management Advisor), which can improve control over the IT project by evaluating the proposed project plan, identifying anomalies, and providing guidance for correction.…”

Section: Expert System Research and Usage In It Project Managementmentioning

confidence: 99%

Application of Fuzzy Expert Systems in IT Project Management

Dudnyk¹,

Sokolovska²

2023

Project Management - New Trends and Applications

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The available statistics show the growing influence of the IT market on the world economy over the last decade. According to expert information, this situation will continue, despite the IT sector’s economic crises, uneven development, and periodic fluctuations. The need to involve fuzzy expert systems (ES) in the IT field is stated, based on the high uncertainty level due to specifics of IT project management. The hypothesis of embedding ES in an IT company’s business process management to increase the efficiency of operational and strategic decisions is tested. The structure of ES is offered, built on the basis of fuzzy logic using a combined model of the semantic network and implication rules. The operation of the system is demonstrated in the example of managing an IT company’s current business processes to maximize its profits. Comparing the conclusions of the ES with the historical decisions of a real company demonstrates the feasibility of implementing the ES. The operation of the developed ES, using the knowledge base formed on the basis of 30 Ukrainian IT companies, confirmed the effectiveness of its use as a tool to support management decisions and increase the IT sector’s financial performance.

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Section: Expert System Research and Usage In It Project Managementmentioning

confidence: 99%

Application of Fuzzy Expert Systems in IT Project Management

Dudnyk¹,

Sokolovska²

2023

Project Management - New Trends and Applications

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“…Some authors reported that developing and adhering a software project plan to deliver software project within the budget and on the schedule [22], [30]. In addition, he proposed application of software planning techniques to manage the multiple problems and the complexity associated with software planning [31].…”

Section: C5: Developing and Adhering A Software Project Planmentioning

confidence: 99%

Untitled

2015

Review of Computer Engineering Research

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Regardless how much effort we put for the success of software projects, many software projects have a very high failure risk rate. The failure risk is not always avoidable, but it could be controllable by using risk management technique through the software development Lifecycle. The aim of this study is to present the factor analysis techniques to classify and identify the risk management techniques in the software development project. The best thirty risk management techniques were presented to respondents and all risk management techniques are used most of the time, and often. We have chosen three components: Planning and requirement techniques, communication techniques, models and tools for thirty risk management techniques. The study has been conducted on a group of software project managers in software development companies. We will intend to apply these study results on a real-world software project to verify the effectiveness of the risk management techniques on a software project for mitigating risks. Successful identifying of risk management techniques will greatly improve the probability of mitigating software risk.

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“…Some authors reported that developing and adhering a software project plan to deliver software project within the budget and on the schedule (Addison and Vallabh, 2002;Dufner et al, 1999). Software project planning should be allocated to each of these sofwtare phases to manage and reduce potential occering failure (Cantor, 1998;Westfall, 2001).…”

Section: C5: Developing and Adhering A Software Project Planmentioning

confidence: 99%

A Comparison of Stepwise and Fuzzy Multiple Regression Analysis Techniques for Managing Software Project Risks: Analysis Phase

Elzamly

Hussin

2014

Journal of Computer Science

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Risk is not always avoidable, but it is controllable. The aim of this study is to identify whether those techniques are effective in reducing software failure. This motivates the authors to continue the effort to enrich the managing software project risks with consider mining and quantitative approach with large data set. In this study, two new techniques are introduced namely stepwise multiple regression analysis and fuzzy multiple regression to manage the software risks. Two evaluation procedures such as MMRE and Pred (25) is used to compare the accuracy of techniques. The model's accuracy slightly improves in stepwise multiple regression rather than fuzzy multiple regression. This study will guide software managers to apply software risk management practices with real world software development organizations and verify the effectiveness of the new techniques and approaches on a software project. The study has been conducted on a group of software project using survey questionnaire. It is hope that this will enable software managers improve their decision to increase the probability of software project success.

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Improving software development project team performance: a Web-based expert support system for project control

Cited by 6 publications

References 9 publications

Application of Fuzzy Expert Systems in IT Project Management

Application of Fuzzy Expert Systems in IT Project Management

Untitled

A Comparison of Stepwise and Fuzzy Multiple Regression Analysis Techniques for Managing Software Project Risks: Analysis Phase

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