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Numerous academic research projects and industrial tasks related to software engineering require individual requirements as input. Unfortunately, according to our observation, several requirements may be packed in one paragraph without explicit boundaries in specification documents. To understand this problem's prevalence, we performed a preliminary study on the open requirement documents widely used in the academic community over the last 10 years, and found that 26% of them include this phenomenon. Several text segmentation approaches have been reported; however, they tend to identify topically coherent units which may contain more than one requirement. What is more, they do not take the constitutions of semantic units of requirements into consideration. Here we report a two‐phase learning‐based approach named DRIP to segment individual requirements from paragraphs. To be specific, we first propose a Requirement Segmentation Siamese framework, which models the similarity of sentences and their conjunction relations, and then detects the initial boundaries between individual requirements. Then, we optimize the boundaries heuristically based on the semantic completeness validation of the segments. Experiments with 1132 paragraphs and 6826 sentences show that DRIP outperforms the popular unsupervised and supervised text segmentation algorithms with respect to processing different documents (with accuracy gains of 57.65%–187.53%) and processing paragraphs of different complexity (with average accuracy gains of 54.46%–158.68%). We also show the importance of each component of DRIP to the segmentation. [ABSTRACT FROM AUTHOR]

Summary: Detecting missing requirements during software development is crucial to avoid unexpected consequences. However, this task is challenging due to limited domain knowledge of requirements analysts and the dynamic nature of software requirements. Previous studies have shown that requirement‐oriented domain models can help identify omissions in requirements, but they are often incomplete for many domains. Meanwhile, domain models constructed from other artifacts are available online. This raises the question: Can these domain models be useful in identifying missing functional information in requirement specifications? To address this question, we conducted a study to measure the overlap between entities in domain models and requirements. We analyzed the occurrence of overlapped entities, considering four distribution characteristics: the type of entities in the domain model, the distribution of mapped entities in the domain model, the family belonging of the mapped entities in the domain model, and the distribution of mapped entities in the requirements. Based on our findings, we proposed recommendations for missing requirements. Additionally, we performed experiments, including the use of the proposed metric "ancestors of the highest level with the most mapped entities" (AHME). The results showed significant improvements with F2$$ {F}_2 $$ gains of 146% and 223% in the two domains, highlighting the benefits of these distribution characteristics. [ABSTRACT FROM AUTHOR]

Context: The UML class diagram is commonly used to model functional structures and software code structures in both the preliminary and detailed design stages. And the abstraction level of UML class diagrams is usually higher than that of source code. Usually, there is a lack of trace links between these class diagrams and the source code, which may cause difficulties in understanding the source code, and affect the software evolution and maintenance. Objective: The main goal of this article is to establish the trace links between highly abstracted UML class diagrams in the design phase and source code, and eventually help practitioners better understand source code. Method: We propose an approach for the automated trace link establishment between UML class diagrams in the design phase and source code. To address the problem of abstraction level gap between them, we extend the UML class diagram by mining the synonymous phrases of class names and deducing the latent missing relationships between classes from multiple design documents. Then we build the trace links with a two‐phase approach including initial construction with fuzzy matching and further optimization by class relationship inference. Results: Experiments on five open‐source projects show that the recalls of our approach are over 94%, and the F2‐scores are over 88%, with the gains of 30% to 60% than the four baselines. Conclusion: Our work can be a reference for establishing the initial trace links between highly‐abstracted UML class diagrams and source code. Towards the higher abstraction of design diagrams, we extend UML class diagrams with the statistical analysis on multiple design documents. To guarantee the quality of trace links, we design a two‐phase approach by obtaining the "full but not good enough" trace links and filtering the "probably wrong" links. Experiments show that the main techniques of our approach behave as important role for tracing between high‐level class diagrams and source code. [ABSTRACT FROM AUTHOR]

This study aimed at evaluate the effects of different aperture-sized type I collagen/silk fibroin (CSF) scaffolds on the proliferation and differentiation of human dental pulp cells (HDPCs). The CSF scaffolds were designed with 3D mapping software Solidworks. Three different aperture-sized scaffolds (CSF1–CSF3) were prepared by low-temperature deposition 3D printing technology. The morphology was observed by scanning electron microscope (SEM) and optical coherence tomography. The porosity, hydrophilicity and mechanical capacity of the scaffold were detected, respectively. HDPCs (third passage, 1 × 105 cells) were seeded into each scaffold and investigated by SEM, CCK-8, alkaline phosphatase (ALP) activity and HE staining. The CSF scaffolds had porous structures with macropores and micropores. The macropore size of CSF1 to CSF3 was 421 ± 27 μm, 579 ± 36 μm and 707 ± 43 μm, respectively. The porosity was 69.8 ± 2.2%, 80.1 ± 2.8% and 86.5 ± 3.3%, respectively. All these scaffolds enhanced the adhesion and proliferation of HDPCs. The ALP activity in the CSF1 group was higher than that in the CSF3 groups (P  <   0.01). HE staining showed HDPCs grew in multilayer within the scaffolds. CSF scaffolds significantly improved the adhesion and ALP activity of HDPCs. CSF scaffolds were promising candidates in dentine-pulp complex regeneration. [ABSTRACT FROM AUTHOR]

The microservice application programming interface (API) becomes a growing concern in the IT industry, as a result of the increasing usage of microservice architecture style. There exist many successful practices among companies, communities, and so on. In contrast, the related academic research is still at an early stage, where lacks an overview of technologies for the design, implementation and operation of microservice APIs, as well as a general picture of concerns. In this article, we try to fill this gap by eliciting the technologies and concerns on microservice APIs and establishing a microservice API description model, with the intention of aiding researchers to gain an overview of this field and find possible research directions, and helping practitioners to better understand microservice APIs and be aware of the existing approaches for daily work. Twelve academic papers and 38 gray literatures are selected and analyzed following the systematic literature review approach. Besides, we give our observations from this study. For researchers, our findings show the most cared concerns of practitioners, and our description model can be used as a reference for new theories, experiments, and future research dimensions. For practitioners, our study can be used as a guideline for microservices experimentation and a starting point for practice. [ABSTRACT FROM AUTHOR]