SEJun 25, 2021

Towards auto-completion on software requirements statements

arXiv:2106.13908v1
Originality Synthesis-oriented
AI Analysis

This addresses the issue of poor software development guidance for development teams, but it appears incremental as it builds on existing auto-completion ideas without demonstrated novelty.

The paper tackles the problem of incomplete or ambiguous software requirements by hypothesizing that text auto-completion can improve the quality of these artifacts, but it does not provide concrete results or numbers.

As software systems become more complex, modern software development requires more attention to human perspectives, and active participation of development teams in requirements elicitation tasks. In this context, incomplete or ambiguous requirements descriptions do not guide the development of good software products. We hypothesize that the text auto-completion feature improves the quality of the software requirements artifacts. We present the motivation for this study, related works, our approach and future research efforts.

Foundations

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