Proceedings of the 16th Innovations in Software Engineering Conference最新文献

A Report on the Fifth Workshop on Emerging Software Engineering Education (WESEE 2023) 第五届新兴软件工程教育研讨会(WESEE 2023)报告

Proceedings of the 16th Innovations in Software Engineering Conference Pub Date : 2023-02-23 DOI: 10.1145/3578527.3581749

S. Tiwari, Sheikh Umar Farooq, S. Rathore

引用次数: 0

Digital Twin Engineering 数字孪生工程

Proceedings of the 16th Innovations in Software Engineering Conference Pub Date : 2023-02-23 DOI: 10.1145/3578527.3581747

Souvik Barat, Aditya A. Paranjape

引用次数: 1

Proof-oriented programming for high-assurance systems 面向证明的高保证系统编程

Proceedings of the 16th Innovations in Software Engineering Conference Pub Date : 2023-02-23 DOI: 10.1145/3578527.3581769

Aseem Rastogi

{"title":"Proof-oriented programming for high-assurance systems","authors":"Aseem Rastogi","doi":"10.1145/3578527.3581769","DOIUrl":"https://doi.org/10.1145/3578527.3581769","url":null,"abstract":"Proof-oriented programming is a paradigm where programs are designed and developed along with mathematical proofs of their correctness and security. In recent years, proof-oriented programming has reached a point where not only several high-assurance software components have been developed using it, but these components have also been deployed in production systems. In this talk, I will provide an overview of this paradigm in the context of F*, a proof-oriented programming language developed at Microsoft Research. I will briefly discuss several critical software components, developed from scratch in F*. These components are already deployed in production systems such as Windows Hyper-V, the Linux kernel, Firefox, and mbedTLS. As a complementary methodology for retrofitting strong, formal guarantees on existing legacy services, I will present the Zeta framework. Zeta works by running a small, proven correct monitor in a trusted execution environment validating responses from the service. The key idea is that we only need to develop the monitor using proof-oriented programming once-and-for-all, while the large legacy service remains untrusted. I will illustrate Zeta by sketching an example of how we can make a concurrent, high-performance, key-value store \"zero trust\" and argue that this step incurs modest software engineering effort and modest runtime overheads.","PeriodicalId":326318,"journal":{"name":"Proceedings of the 16th Innovations in Software Engineering Conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125088371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Proceedings of the 16th Innovations in Software Engineering Conference Pub Date : 2023-02-23 DOI: 10.1145/3578527.3578539

Nidhi Pandya, S. Tiwari

{"title":"Similarities in Challenges faced by Developers: Investigations on Stack Overflow and GitHub","authors":"Nidhi Pandya, S. Tiwari","doi":"10.1145/3578527.3578539","DOIUrl":"https://doi.org/10.1145/3578527.3578539","url":null,"abstract":"A large amount of rich data available in today’s world encounters a lot of opportunities to analyze the data and identify some valuable patterns from them. However, dealing with such data requires automated frameworks and knowledge of programming languages. The most common and widely used programming languages among developers are Java and Python, as evident from the queries and issues posted on Stack Overflow and GitHub. Despite the popularity of both Java and Python, the challenges in transitioning from one technology to another technology are hard for individuals and industries. In this paper, we aim to investigate similarities in the challenges faced by developers while dealing with both programming languages. To achieve this goal, we formulated two research questions (RQs) for understanding the topics and issues asked and faced by developers. We have also identified the temporal trend of asking new questions on Stack Overflow for Java and Python programming languages (PLs). Our results revealed the changing trend, from 2015 onwards, from Java to Python and inclined towards Python from the number of new posts on Stack Overflow. We analyzed 18,892 Stack Overflow questions related to Java and Python PLs and 42,674 issues from 22 different GitHub repositories, 11 for each PL. Our results indicate that questions asked on Stack Overflow are co-related to issues posted by developers on GitHub during real-time development for a respective PL.","PeriodicalId":326318,"journal":{"name":"Proceedings of the 16th Innovations in Software Engineering Conference","volume":"8 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116834105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SOCluster - Towards Answering Unanswered Questions on Stack Overflow via Answered Questions SOCluster -通过回答问题来回答关于堆栈溢出的未回答问题

Proceedings of the 16th Innovations in Software Engineering Conference Pub Date : 2023-02-23 DOI: 10.1145/3578527.3578544

Abhishek Kumar, Deep Ghadiyali, S. Chimalakonda, Akhila Sri Manasa Venigalla

{"title":"SOCluster - Towards Answering Unanswered Questions on Stack Overflow via Answered Questions","authors":"Abhishek Kumar, Deep Ghadiyali, S. Chimalakonda, Akhila Sri Manasa Venigalla","doi":"10.1145/3578527.3578544","DOIUrl":"https://doi.org/10.1145/3578527.3578544","url":null,"abstract":"Stack Overflow (SO) platform has a huge dataset of questions and answers driven by interactions between users. But the count of unanswered questions is continuously rising, which is observed in various similar community Question & Answering platforms (Q&A) such as Yahoo, Quora and so on. To address this issue, these communities have explored clustering mechanisms to answer unanswered questions using other answered questions in the same cluster, which could also improve the response time for new questions. It is here, we propose SOCluster, an approach and a tool to cluster SO questions using a graph-based clustering approach. We selected four datasets of 10k, 20k, 30k & 40k SO questions without code-snippets or images involved, and performed clustering on them. We have done a preliminary evaluation of our tool by analyzing the resultant clusters using the commonly used metrics of Silhouette coefficient, Calinkski-Harabasz Index, & Davies-Bouldin Index. We performed clustering for 8 different threshold similarity values and analyzed the intriguing trends reflected by the output clusters through the three evaluation metrics. At 90% threshold similarity, it shows the best improvement for the three evaluation metrics on all four datasets. We further manually assessed the content in the clusters to confirm the similarity of elements in clusters. This revealed clusters to correspond to topics such as mouse over effect, speed optimisation, how to perform ‘some’ action in JavaScript, and so on. The source code and tool are available for download on Github at: https://github.com/rishalab/SOCluster, and the demo can be found here: https://youtu.be/Ewm-M_rg_x8.","PeriodicalId":326318,"journal":{"name":"Proceedings of the 16th Innovations in Software Engineering Conference","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129621212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Advances in Automated Pedagogical Compile-time Error Repair 自动化教学编译时错误修复的研究进展

Proceedings of the 16th Innovations in Software Engineering Conference Pub Date : 2023-02-23 DOI: 10.1145/3578527.3578535

Sharath H. Padmanabha, Fahad Shaikh, Mayank Bansal, Debanjan Chatterjee, Preeti Singh, Amey Karkare, Purushottam Kar

{"title":"Advances in Automated Pedagogical Compile-time Error Repair","authors":"Sharath H. Padmanabha, Fahad Shaikh, Mayank Bansal, Debanjan Chatterjee, Preeti Singh, Amey Karkare, Purushottam Kar","doi":"10.1145/3578527.3578535","DOIUrl":"https://doi.org/10.1145/3578527.3578535","url":null,"abstract":"Automated pedagogical error repair (APER) is the task of suggesting fixes to buggy programs written by beginner or novice programmers. APER tools have been shown to greatly improve the learning experience for students for whom error messages offered by compilers or runtime environments are either unhelpful and often misleading. Consequently, several APER tools have been proposed in literature using a variety of powerful machine learning techniques including sequence-to-sequence modelling (TRACER), reinforcement learning (RLAssist), graph attention (DrRepair) and decision trees (MACER). Despite offering high repair rates, these tools are often bulky, requiring several days of training and extensive GPU resources. This paper describes CAPER, a novel APER tool for the C programming language that offers 4-5% higher repair accuracy than existing APER tools on multiple benchmark error repair datasets. CAPER has the added advantage of being significantly lighter and faster than most existing tools, being able to train on a CPU and yet offering training speedups of 2 × over TRACER, 600 × over RLAssist and 700 × over DrRepair. The paper also describes PyPER, an extension of CAPER to the Python programming language. Code for CAPER is available at https://github.com/purushottamkar/caper/","PeriodicalId":326318,"journal":{"name":"Proceedings of the 16th Innovations in Software Engineering Conference","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129080460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Comparative Analysis on the Detection of Web Service Anti-Patterns Using Various Metrics 使用不同度量方法检测Web服务反模式的比较分析

Proceedings of the 16th Innovations in Software Engineering Conference Pub Date : 2023-02-23 DOI: 10.1145/3578527.3578534

Sahithi Tummalapalli, L. Kumar, Lalita Bhanu Murthy Neti, A. Krishna

引用次数: 0

A modeling language for novice engineers to design well at SaaS product companies 一种建模语言，供新手工程师在SaaS产品公司进行良好的设计

Proceedings of the 16th Innovations in Software Engineering Conference Pub Date : 2023-02-23 DOI: 10.1145/3578527.3578548

Mrityunjay Kumar, Venkatesh Choppella

{"title":"A modeling language for novice engineers to design well at SaaS product companies","authors":"Mrityunjay Kumar, Venkatesh Choppella","doi":"10.1145/3578527.3578548","DOIUrl":"https://doi.org/10.1145/3578527.3578548","url":null,"abstract":"Software-as-a-Service (SaaS) product companies have brought in significant changes in how we build software from architecture and engineering process perspective. SaaS products are large, distributed software systems hosted in cloud and built using collaborating services (or micro-services). The software releases happen in days and weeks, necessitating an agile development process. Novice engineers (those who join the company fresh from college) need to become comfortable with complex systems and proficient in agile delivery with high quality, otherwise they fall behind in productivity. The paper posits that, to be successful at these SaaS product companies, the novice engineers need good modeling and design skills. While this has been for all software development, the changes driven by SaaS products have made this need more acute. Such skills will allow them to capture their feature behaviors (in context of their understanding of the larger product) in an implementation-independent manner and any knowledge gaps can be identified and bridged by their collaborators. We propose a modeling language that is easy for them to learn and use, and which has characteristics suitable for the kind of engineering work they need to do in their early years in a SaaS product company. This modeling language is based on the notion of Transition Systems. The paper demonstrates the usage and value of this language by creating a model for a real feature. The modeling language is quite general and transcends abstraction boundaries. We also present a modeling process that should be used with this language for better results. This is a short position paper that presents an idea about a new modeling language for a specific purpose (helping novice engineers design well at SaaS product companies). Validation studies for the language and the design process is a work in progress and the results will be shared in a full paper later.","PeriodicalId":326318,"journal":{"name":"Proceedings of the 16th Innovations in Software Engineering Conference","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133979401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Process Line Diagrams (PLDs): An Approach for Modular Process Modeling 过程线图:模块化过程建模的一种方法

Proceedings of the 16th Innovations in Software Engineering Conference Pub Date : 2023-02-23 DOI: 10.1145/3578527.3578537

Karnika Shivhare, R. Joshi

引用次数: 1

Teachers Perspectives on Transition to Online Teaching Deaf and Hard-of-Hearing Students during the COVID-19 Pandemic: A Case Study 新冠肺炎疫情期间教师对聋哑和听力障碍学生网络教学转型的看法:个案研究

Proceedings of the 16th Innovations in Software Engineering Conference Pub Date : 2023-02-23 DOI: 10.1145/3578527.3578531

Wajdi Aljedaani, Mona Aljedaani, Mohamed Wiem Mkaouer, S. Ludi

引用次数: 2