EBSE

Evidence-Based Software Engineering

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Software Engineering Evidence Map

One of the goals of this website is to document secondary studies of software engineering topics. This page classifies SLRs and mapping studies using the knowledge areas defined by the SWEBOK.

CategoryStudiesStudy Details

[S7] A Review of Studies on Expert Estimation of Software Development Effort

2004, M. Jorgensen

Source: Systematic literature reviews in software engineering - A systematic literature review

This paper provides an extensive review of studies related to expert estimation of software development effort. The main goal and contribution of the review is to support the research on expert estimation, e.g., to ease other researchers' search for relevant expert estimation studies. In addition, we provide software practitioners with useful estimation guidelines, based on the research-based knowledge of expert estimation processes. The review results suggest that expert estimation is the most frequently applied estimation strategy for software projects, that there is no substantial evidence in favour of use of estimation models, and that there are situations where we can expect expert estimates to be more accurate than formal estimation models. The following twelve expert estimation "best practice" guidelines are evaluated through the review: 1) Evaluate estimation accuracy, but avoid high evaluation pressure, 2) Avoid conflicting estimation goals, 3) Ask the estimators to justify and criticize their estimates, 4) Avoid irrelevant and unreliable estimation information, 5) Use documented data from previous development tasks, 6) Find estimation experts with relevant domain background and good estimation records, 7) Estimate top-down and bottom-up, independently of each other, 8) Use estimation checklists, 9) Combine estimates from different experts and estimation strategies, 10) Assess the uncertainty of the estimate, 11) Provide feedback on estimation accuracy and development task relations, and, 12) Provide estimation training opportunities. We found supporting evidence for all twelve estimation principles, and provide suggestions on how to implement them in software organizations.
Software RequirementsS23, S26, S27, S63
Software DesignS1, S25, S31, S38
Software ConstructionS18, S43, S61
Software TestingS10, S17, S28, S62
Software MaintenanceS24, S30
Software Configuration Management -
Software Engineering ManagementM4, S5, S7, S8, S11, S12, S14, S21, S22, S29, S45, S46, S53, S66
Software Engineering ProcessesS3, S41, S47, S49, S50
Software Engineering Tools and MethodsS60, S64, S65
Software QualityM1, S15
Unclassified -