Conceptual scheduling model and optimized release scheduling for agile environments

Release scheduling deals with the selection and assignment of deliverable features to a sequence of consecutive product deliveries while several constraints are fulfilled. Although agile software development represents a major approach to software engineering, there is no well-established conceptual...

Full description

Saved in:
Bibliographic Details
Published in:Information and software technology Vol. 53; no. 6; pp. 574 - 591
Main Author: SzAke, Akos
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.06.2011
Elsevier Science Ltd
Subjects:
Agile software development
Algorithms
Branch & bound algorithms
Computer programs
Delivery scheduling
Mathematical models
Optimization
Optimization algorithms
Planning metamodel
Release planning
Schedules
Scheduling
Scheduling algorithms
Software development
Software engineering
Studies
Systems development
Planning metamodel
Agile software development
Release planning
ISSN:0950-5849, 1873-6025
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Release scheduling deals with the selection and assignment of deliverable features to a sequence of consecutive product deliveries while several constraints are fulfilled. Although agile software development represents a major approach to software engineering, there is no well-established conceptual definition and sound methodological support of agile release scheduling. To propose a solution, we present, (1) a conceptual model for agile scheduling, and (2) a novel multiple knapsack-based optimization model with (3) a branch-and-bound optimization algorithm for agile release scheduling. To evaluate our model simulations were carried out seven real life and several generated data sets. The developed algorithm strives to prevent resource overload and resource underload, and mitigates risks of delivery slippage. The results of the experiment suggest that this approach can provide optimized semi-automatic release schedule generations and more informed and established decisions utilizing what-if-analysis on the fly to tailor the best schedule for the specific project context.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:0950-5849
1873-6025
DOI:10.1016/j.infsof.2011.01.008