Software Engineering
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Anna K Rolleston ◽  
Judy Bowen ◽  
Annika Hinze ◽  
Erina Korohina ◽  
Rangi Matamua

We describe a collaboration between Māori (Indigenous people of Aotearoa/New Zealand) and Tauiwi (non-Māori) researchers on a software engineering project. Te Tiriti o Waitangi (The Treaty of Waitangi) provides the basis for Māori to lead research that involves Māori as participants or intends to impact Māori outcomes. Through collaboration, an extension of the traditional four-step software design process was created, culminating in a nine-step integrated process that included Kaupapa Māori (Māori ideology) principles. The collaboration experience for both Māori and Tauiwi highlighted areas of misunderstanding within the research context based on differing worldviews and our ability to navigate and work through this. This article provides context, guiding principles, and recommended research processes where Māori and Tauiwi aim to collaborate.

2021 ◽  
Vol 26 (6) ◽  
Camila Costa Silva ◽  
Matthias Galster ◽  
Fabian Gilson

AbstractTopic modeling using models such as Latent Dirichlet Allocation (LDA) is a text mining technique to extract human-readable semantic “topics” (i.e., word clusters) from a corpus of textual documents. In software engineering, topic modeling has been used to analyze textual data in empirical studies (e.g., to find out what developers talk about online), but also to build new techniques to support software engineering tasks (e.g., to support source code comprehension). Topic modeling needs to be applied carefully (e.g., depending on the type of textual data analyzed and modeling parameters). Our study aims at describing how topic modeling has been applied in software engineering research with a focus on four aspects: (1) which topic models and modeling techniques have been applied, (2) which textual inputs have been used for topic modeling, (3) how textual data was “prepared” (i.e., pre-processed) for topic modeling, and (4) how generated topics (i.e., word clusters) were named to give them a human-understandable meaning. We analyzed topic modeling as applied in 111 papers from ten highly-ranked software engineering venues (five journals and five conferences) published between 2009 and 2020. We found that (1) LDA and LDA-based techniques are the most frequent topic modeling techniques, (2) developer communication and bug reports have been modelled most, (3) data pre-processing and modeling parameters vary quite a bit and are often vaguely reported, and (4) manual topic naming (such as deducting names based on frequent words in a topic) is common.

2021 ◽  
Vol 53 (10) ◽  
Michael Haider ◽  
Michael Riesch ◽  
Christian Jirauschek

AbstractEfforts in providing high-quality scientific software are hardly rewarded, as scientific output is typically measured in terms of publications in high ranking journals. As a result, scientific software is often developed without proper documentation and support of modern software design patterns. Ready-to-use project skeletons can be employed to accelerate the development process, while at the same time taking care of the implementation of best practices in software engineering. In this work, we revisit best practices in software engineering and review existing project skeletons. Special emphasis is given on the realization of best practices. Finally, we present a new project skeleton for scientific writing in "Image missing", which takes care of the attainment of best practices, adapted for being used in academic publications.

2021 ◽  
Vol 13 (17) ◽  
pp. 9849
Yen-Ting Lin

Software engineering education plays an important role in keeping students educated with software technologies, processes, and practices that are needed by industries. Nevertheless, the nature of software engineering learning activities in traditional classrooms is limited in scope and time, making it more difficult to achieve a proper balance between theory and practice and address industrial demands. This makes scant provision for assisting students in keeping their software engineering knowledge current. To support software engineering education, flipped learning is a suitable strategy. Prior studies have shown that students’ perceptions in flipped learning environments are better than those in traditional learning environments. Nevertheless, in flipped learning, students may not have sufficient ability to conduct learning out of class. Therefore, the flipped learning strategy should aim to meet the needs of students to ensure that they get the appropriate support or feedback during the learning process before the class. The aim of this study was to propose a flipped learning diagnosis approach to promote students’ learning out of class in the flipped classroom. To explore students’ learning performance in software engineering courses, three classes of students were invited to learn with three different learning approaches (traditional learning approach, flipped learning approach, and flipped learning diagnosis approach). The results showed that the students who learned with the flipped learning diagnosis approach outperformed those students who learned with the flipped learning approach or the traditional learning approach.

Joelma Choma ◽  
Eduardo M. Guerra ◽  
Tiago S. da Silva ◽  
Luciana M. Zaina

Varisha Alam* ◽  
Dr. Mohammad Arif ◽  

"Biometrics" is got from the Greek word 'life' and 'measure' which implies living and evaluation take apart. It simply converts into "life estimation". Biometrics uses computerized acknowledgment of people, dependent on their social and natural attributes. Biometric character are data separated from biometric tests, which can use for examination with a biometric orientation. Biometrics involves techniques to unusually recognize people dependent on at least one inherent physical or behavior attribute. In software engineering, specifically, biometric is used as a form of character retrieve the Committee and retrieve command. Biometric identically utilized to recognize people in bunches that are in observation. Biometric has quickly risen like a auspicious innovation for validation and has effectively discovered a spot in most of the scientific safety regions. An effective bunching method suggest for dividing enormous biometrics data set through recognizable proof. This method depends on the changed B+ tree is decreasing the discs get to. It diminishes the information recovery time and also possible error rates. Hence, for bigger applications, the need to reduce the data set to a more adequate portion emerges to accomplish both higher paces and further developed precision. The main motivation behind ordering is to recover a small data set for looking through the inquiry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Yudith Cardinale ◽  
Maria Alejandra Cornejo-Lupa ◽  
Alexander Pinto-De la Gala ◽  
Regina Ticona-Herrera

Purpose This study aims to the OQuaRE quality model to the developed methodology. Design/methodology/approach Ontologies are formal, well-defined and flexible representations of knowledge related to a specific domain. They provide the base to develop efficient and interoperable solutions. Hence, a proliferation of ontologies in many domains is unleashed. Then, it is necessary to define how to compare such ontologies to decide which one is the most suitable for the specific needs of users/developers. As the emerging development of ontologies, several studies have proposed criteria to evaluate them. Findings In a previous study, the authors propose a methodological process to qualitatively and quantitatively compare ontologies at Lexical, Structural and Domain Knowledge levels, considering correctness and quality perspectives. As the evaluation methods of the proposal are based on a golden-standard, it can be customized to compare ontologies in any domain. Practical implications To show the suitability of the proposal, the authors apply the methodological approach to conduct comparative studies of ontologies in two different domains, one in the robotic area, in particular for the simultaneous localization and mapping (SLAM) problem; and the other one, in the cultural heritage domain. With these cases of study, the authors demonstrate that with this methodological comparative process, we are able to identify the strengths and weaknesses of ontologies, as well as the gaps still needed to fill in the target domains. Originality/value Using these metrics and the quality model from OQuaRE, the authors are incorporating a standard of software engineering at the quality validation into the Semantic Web.

2021 ◽  
Pramod Pandurang Jadhav

Abstract Model transformation is the conspicuous research statement in the area of software engineering. Model transformation (MT) is playing the measure role in the Model driven engineering (MDE), which is helpful to transfer the model from one set of databases to another set of databases by considering the simulation and also support to various language. Propose work elaborate the Bat inspired optimize solution for model transformation using Adaptive Dragonfly Algorithm (BADF), and transform Class diagram (CLD) in to the relational schema (RS), accompanied by fitness function. Further performance of the proposed algorithm is appraised using Automatic Correctness (AC) and fitness measure, by comparing existing algorithm.

Archit Gupta

Abstract: Software Engineering has grown and developed from the 1960’s till now a lot as our knowledge and understanding of software is increasing day-by-day due to which software is becoming increasingly reliable and cost effective. Previous research was not able to express clearly how software engineering transitioned, how new technologies and services for software came to be known and were started using in the world of software engineering, decade or year wise. I use data from different websites and research papers to tell how software engineering has evolved along with the years with details about what happened in particular years, with respect to the corresponding decades. There are also details about manifestos and the developers of computer languages. The findings indicate that the software engineering field is vast and is still far from being fully developed, in a world where we have hands on every technology possible and hence new software’s and services are coming out on a regular basis now.

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