Software-as-a-Service is becoming popular in the software business, due to its rapid delivery and cost effectiveness in development and maintenance. Software-as-a-Service should be provided in single code base and operated as a single instance. To meet these constraints and requirements from various customers, Software-as-a-Service must be highly configurable. To develop configurable Software-as-a-Service, it is important to elicit and analyze configuration requirements in the early stages of development. Another issue is that on implementing configuration requirements, there are duplicated and untidy code segments. In our study, configuration requirements are identified and classified. This study introduces design patterns to remove duplicated codes for configuration.
On GitHub, one of the most successful services for software project hosting, labels have been used to represent various information and decisions about reported issues. However, previous studies on labels were limited to simple statistics or label recommendations for issue types. In this paper, we aim to provide a better understanding of labels and their usage in software development. We particularly focus on using multiple and custom labels on issues. To analyze label usage, we collected software project data and label usage information from GitHub. We then quantitatively investigated the performance of projects with multi-label features and qualitatively investigated the categories of multi-labels, and the usage of multilabels based on these categories. Our analysis results show that multi-labels are common in the majority of software projects and that projects using multi-label features manage their issues more effectively. In addition, our analysis results reveal different types of information represented by labels, which are related to features, development, and issues. This study finds several facts that can be used for studies on issue management and thus that help develop labeling techniques to mitigate the burden of issue management.
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