SUCCEED: Sharing Upcycling Cases with Context and Evaluation for Efficient Software Development †.
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| Název: | SUCCEED: Sharing Upcycling Cases with Context and Evaluation for Efficient Software Development †. |
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| Autoři: | Nakata, Takuya, Chen, Sinan, Saiki, Sachio, Nakamura, Masahide |
| Zdroj: | Information; Sep2023, Vol. 14 Issue 9, p518, 25p |
| Témata: | COMPUTER software development, SWARM intelligence, RESEARCH questions, SHARING |
| Abstrakt: | Software upcycling, a form of software reuse, is a concept that efficiently generates novel, innovative, and value-added development projects by utilizing knowledge extracted from past projects. However, how to integrate the materials derived from these projects for upcycling remains uncertain. This study defines a systematic model for upcycling cases and develops the Sharing Upcycling Cases with Context and Evaluation for Efficient Software Development (SUCCEED) system to support the implementation of new upcycling initiatives by effectively sharing cases within the organization. To ascertain the efficacy of upcycling within our proposed model and system, we formulated three research questions and conducted two distinct experiments. Through surveys, we identified motivations and characteristics of shared upcycling-relevant development cases. Development tasks were divided into groups, those that employed the SUCCEED system and those that did not, in order to discern the enhancements brought about by upcycling. As a result of this research, we accomplished a comprehensive structuring of both technical and experiential knowledge beneficial for development, a feat previously unrealizable through conventional software reuse, and successfully realized reuse in a proactive and closed environment through construction of the wisdom of crowds for upcycling cases. Consequently, it becomes possible to systematically perform software upcycling by leveraging knowledge from existing projects for streamlining of software development. [ABSTRACT FROM AUTHOR] |
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| Databáze: | Complementary Index |
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