Abstract
The management and estimation of agile projects are challenging tasks for software companies due to their high failure rates. This paper emphasizes how to improve management and estimation challenges in the context of scrum, which is an agile process widely used for the development of small to medium size software projects. The scrum emphasis on code results in spending inadequate time on the estimation process. Mostly, the scrum master, along with the scrum team, estimates the upcoming software projects based on experience or historical data. Many issues can arise in a case where expert judgment is not available or historical data are not properly organized. In this paper, an Intelligent Recommender and Decision Support System (IRDSS) is proposed that can help the scrum master to better estimate an upcoming software project in terms of cost, time, and recommendations of human resources. Formal specification of IRDSS is also performed using the formalism known as Z language. Furthermore, an experiment on fifteen web projects was performed to validate the proposed approach and compared it with Delphi and Planning Poker estimation methods. The overall results indicate that the proposed system can produce better estimation than Planning Poker and Delphi methods by applying MMRE and PRED evaluation. This research opens new directions for the scrum community for the development of software projects within the allocated time and cost.
Highlights
Estimation of time and cost plays an important role in the planning and management of software projects [1], [2]
The precision of estimation has a direct effect on the output of a software project; underestimation may lead to schedule or budget overruns while overestimation may have a negative influence on organizational competitiveness [3], [4]
2) How scrum master can take more good decisions through gaining experience and tacit knowledge through the lessons learned?. These problems arise because in most cases all the tacit knowledge of software companies is usually lost when the scrum master leaves the company. To handle such kind of problems, this paper proposes an Intelligent Recommender and Decision Support System that will help scrum masters during estimation and decision-making
Summary
Estimation of time and cost plays an important role in the planning and management of software projects [1], [2]. Research efforts on time and cost estimation are spanned over 30 years and are commonly divided into expert-based and model-based methods [5]–[7]. Expert-based methods rely on the expertise of human resources to predict new projects. Most of the research [7]–[14] in this domain has focused on traditional models such as waterfall. These traditional models estimate time and cost for complete software project at the beginning of the software life cycle
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