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软件工程学术速递[1.10]

格林先生MrGreen arXiv每日学术速递 2022-05-05

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cs.SE软件工程,共计3篇


【1】 Investigating Expectation Violations in Mobile Apps
标题:调查移动应用中的预期违规行为
链接:https://arxiv.org/abs/2201.02269

作者:Sherlock A. Licorish,Helen E. Owen,Bastin Tony Roy Savarimuthu,Priyanka Patel
备注:32 pages, 4 figures, 8 tables
摘要:Information technology and software services are pervasive, occupying the centre of most aspects of contemporary societies. This has given rise to commonly expected norms and expectations around how such systems should work, appropriate penalties for violating these expectations, and more importantly, indicators of how to reduce the consequences of violations and sanctions. Evidence for expectation violations and ensuing sanctions exists in a range of portals used by individuals and groups to start new friendships, explore new ideas, and provide feedback for products and services. Therein lies insights that could lead to functional socio-technical systems, and general awareness and anticipations of human actions (and interactions) when using information technology and software services. However, limited previous work has examined such artifacts to provide these understandings. To contribute to such understandings and theoretical advancement we study expectation violations in mobile apps, considered among the most engaging socio-technical systems. We used content analysis and expectancy violation theory (EVT) and expectation confirmation theory (ECT) to explore the evidence and nature of sanctions in app reviews for a specific domain of apps. Our outcomes show that users respond to expectation violation with sanctions when their app does not work as anticipated, developers seem to target specific market niches when providing services in an app domain, and users within an app domain respond with similar sanctions. We contribute to the advancement of expectation violation theories, and we provide practical insights for the mobile app community.

【2】 Source Code Anti-Plagiarism: a C# Implementation using the Routing Approach
标题:源代码反剽窃:使用路由方法的C#实现
链接:https://arxiv.org/abs/2201.02241

作者:Fabrizio d'Amore,Lorenzo Zarfati
摘要:Despite the approaches proposed so far, software plagiarism is still a problem which has not been solved entirely yet. The approach introduced throughout this paper is about a source code anti-plagiarism technique which aims at rendering the source code incomprehensible to a possible plagiarist and at the same time preventing source code modifications. The proposal is based on the concept of Router and makes use of both symmetric encryption and cryptographic hashing functions to provide such guarantees.

【3】 On the Prevalence, Impact, and Evolution of SQL Code Smells in Data-Intensive Systems
标题:SQL代码嗅觉在数据密集型系统中的流行、影响和演变
链接:https://arxiv.org/abs/2201.02215

作者:Biruk Asmare Muse,Mohammad Masudur Rahman,Csaba Nagy,Anthony Cleve,Foutse Khomh,Giuliano Antoniol
备注:None
摘要:Code smells indicate software design problems that harm software quality. Data-intensive systems that frequently access databases often suffer from SQL code smells besides the traditional smells. While there have been extensive studies on traditional code smells, recently, there has been a growing interest in SQL code smells. In this paper, we conduct an empirical study to investigate the prevalence and evolution of SQL code smells in open-source, data-intensive systems. We collected 150 projects and examined both traditional and SQL code smells in these projects. Our investigation delivers several important findings. First, SQL code smells are indeed prevalent in data-intensive software systems. Second, SQL code smells have a weak co-occurrence with traditional code smells. Third, SQL code smells have a weaker association with bugs than that of traditional code smells. Fourth, SQL code smells are more likely to be introduced at the beginning of the project lifetime and likely to be left in the code without a fix, compared to traditional code smells. Overall, our results show that SQL code smells are indeed prevalent and persistent in the studied data-intensive software systems. Developers should be aware of these smells and consider detecting and refactoring SQL code smells and traditional code smells separately, using dedicated tools.

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