14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference)最新文献_第2页

Open Information Extraction Using Dependency Parser for Business Rule Mining in SBVR Format 基于依赖解析器的SBVR格式业务规则挖掘开放信息提取

14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2021-02-25 DOI: 10.1145/3452383.3452396

Chandan Prakash, Pavan Kumar Chittimalli, Ravindra Naik

{"title":"Open Information Extraction Using Dependency Parser for Business Rule Mining in SBVR Format","authors":"Chandan Prakash, Pavan Kumar Chittimalli, Ravindra Naik","doi":"10.1145/3452383.3452396","DOIUrl":"https://doi.org/10.1145/3452383.3452396","url":null,"abstract":"Business Rules exists at the core of any Business Organization. For efficient execution of the business system, all the business rules must be in machine-interpretable format. There is an absence of such a system that can convert the business rule sentences into corresponding structured format automatically. We present BRMiner, a system which automatically converts business rules represented as Natural Language sentences to the corresponding SBVR format which is a structured representation that can be further converted to the machine-interpretable format. BRMiner is based on the idea of Open Information Extraction (OIE). We have shown that existing OIE systems are not suitable for SBVR rule formation that leads to the development of a new OIE system BRMiner, with more accurate prediction and additional capabilities. BRMiner uses the state of the art dependency parser to convert an unstructured business rule to the corresponding structured format. We have used internal as well as publically available datasets for our system evaluation and the results are encouraging which we have shown in the paper.","PeriodicalId":378352,"journal":{"name":"14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126869327","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: 3

A design methodology for web-based services to detect fraudulent transactions in credit card 一种基于web的服务检测信用卡欺诈交易的设计方法

14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2021-02-25 DOI: 10.1145/3452383.3452397

Debachudamani Prusti, Abhishek Kumar, Ingole Shubham Purusottam, S. K. Rath

{"title":"A design methodology for web-based services to detect fraudulent transactions in credit card","authors":"Debachudamani Prusti, Abhishek Kumar, Ingole Shubham Purusottam, S. K. Rath","doi":"10.1145/3452383.3452397","DOIUrl":"https://doi.org/10.1145/3452383.3452397","url":null,"abstract":"Financial fraud associated with the transactions of credit card leads to unauthorized access of performing credit card transactions in different platforms by intercepting important card credentials. In order to curb this problem, an effective fraud detection system is of primary importance for any financial institution. In the proposed methodology, a web-based fraud detection system has been designed considering two different protocols for the web-based services such as simple object access protocol (SOAP) and representational state transfer (REST). Further, for detecting the fraudulent transactions, these services are associated with five different machine learning techniques such as support vector machine (SVM), multilayer perceptron (MLP), random forest regression, autoencoder and isolation forest. The performance analysis of each machine learning algorithm associated with SOAP and REST services are critically assessed. The web services have been designed based on concepts of service oriented architecture (SOA) by considering a middleware family of software products i.e., Oracle SOA suite which is very often used by the software architects.","PeriodicalId":378352,"journal":{"name":"14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114622833","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: 2

Using Paragraph Vectors to improve our existing code review assisting tool-CRUSO 使用段落向量来改进我们现有的代码审查辅助工具——cruso

14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2021-02-25 DOI: 10.1145/3452383.3452393

Ritu Kapur, B. Sodhi, P. U. Rao, Shipra Sharma

{"title":"Using Paragraph Vectors to improve our existing code review assisting tool-CRUSO","authors":"Ritu Kapur, B. Sodhi, P. U. Rao, Shipra Sharma","doi":"10.1145/3452383.3452393","DOIUrl":"https://doi.org/10.1145/3452383.3452393","url":null,"abstract":"Code reviews are one of the effective methods to estimate defectiveness in source code. However, the existing methods are dependent on experts or inefficient. In this paper, we improve the performance (in terms of speed and memory usage) of our existing code review assisting tool–CRUSO. The central idea of the approach is to estimate the defectiveness for an input source code by using the defectiveness score of similar code fragments present in various StackOverflow (SO) posts. The significant contributions of our paper are i) SOpostsDB: a dataset containing the PVA vectors and the SO posts information, ii) CRUSO-P: a code review assisting system based on PVA models trained on SOpostsDB. For a given input source code, CRUSO-P labels it as {Likely to be defective, Unlikely to be defective, Unpredictable}. To develop CRUSO-P, we processed >3 million SO posts and 188200+ GitHub source files. CRUSO-P is designed to work with source code written in the popular programming languages {C, C#, Java, JavaScript, and Python}. CRUSO-P outperforms CRUSO with an improvement of 97.82% in response time and a storage reduction of 99.15%. CRUSO-P achieves the highest mean accuracy score of 99.6% when tested with the C programming language, thus achieving an improvement of 5.6% over the existing method.","PeriodicalId":378352,"journal":{"name":"14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131871056","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: 2

Using project-based approach to teach design patterns: An Experience Report 使用基于项目的方法教授设计模式:一份经验报告

14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2021-02-25 DOI: 10.1145/3452383.3452399

Sai Anirudh Karre, L. Sanagavarapu, Y. R. Reddy

引用次数: 1

Association of Defect Log Suitability for Machine Learning with Performance: An Experience Report 机器学习缺陷日志适用性与性能的关联:一份经验报告

14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2021-02-25 DOI: 10.1145/3452383.3452400

Janardan Misra, Sanjay Podder

引用次数: 0

Why does the experiment fail with students? An Experience 为什么这个实验在学生中失败了?一种体验

14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2021-02-25 DOI: 10.1145/3452383.3452398

Deepti Ameta, S. Tiwari

引用次数: 0

AI and its Applications in the Cloud strategy 人工智能及其云应用战略

14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2021-02-25 DOI: 10.1145/3452383.3452385

Gargi Dasgupta

{"title":"AI and its Applications in the Cloud strategy","authors":"Gargi Dasgupta","doi":"10.1145/3452383.3452385","DOIUrl":"https://doi.org/10.1145/3452383.3452385","url":null,"abstract":"The fourth industrial revolution identifies cloud computing, data, and artificial intelligence (AI) as opportunity clusters with double digit growth in the next couple of years. As part of the cloud and digital transformation, the role of AI is crucial in enabling that transformation as well as creating the new breed of applications on top. AI mechanisms can help accelerate the modernization of applications, their management, and the testing on cloud architectures. I will focus on two sub-problems: 1) Refactoring of massive monolith applications using AI techniques. This problem statement is particularly relevant in understanding legacy un-optimized code and transforming them to be more cloud-ready. Microservices are indeed becoming the de-facto design choice for software architecture. It involves partitioning the software components into finer modules such that the development can happen independently [2]. It also provides natural benefits when deployed on the cloud since resources can be allocated dynamically to necessary components based on demand. We are exploring how AI can help accelerate the transformation of existing applications to microservices. 2) Detecting faults in application behavior at runtime from operational data. This problem statement is particularly relevant in understanding how to manage this new architecture of multiple microservices across the cloud stack [1], [3]. Operational data artifacts span across logs, metrics, tickets, and traces. Looking at signals across the artifacts and across the stack presents a challenging data correlation problem. AI mechanisms can help accelerate problem determination in these complex environments. I will also share my thoughts on how fundamental breakthroughs in AI Research will be needed as we address some of the core problems of cloud computing.","PeriodicalId":378352,"journal":{"name":"14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121447799","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: 2

Automating Key Phrase Extraction from Fault Logs to Support Post-Inspection Repair of Software Requirements 从故障日志中自动提取关键短语以支持软件需求的巡检后修复

14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2021-02-25 DOI: 10.1145/3452383.3452386

Maninder Singh, G. Walia

{"title":"Automating Key Phrase Extraction from Fault Logs to Support Post-Inspection Repair of Software Requirements","authors":"Maninder Singh, G. Walia","doi":"10.1145/3452383.3452386","DOIUrl":"https://doi.org/10.1145/3452383.3452386","url":null,"abstract":"This research paper aims at developing an automated approach to identify fault prone requirements in a software requirement specification (SRS) document to mitigate the fault propagation to later phases where the same faults are harder to find and fix. This research work proposes an automated approach (i.e., KESRI) for the identification of “problematic areas” (i.e., faulty requirements) from fault logs generated during inspections. Our automated approach uses machine learning-based key phrase extraction (KPE) algorithms (both supervised and unsupervised) that can extract key phrases from fault logs and map them to an SRS document (using semantic analysis) to locate faulty requirements. To validate our proposed approach, an inspection study conducted at North Dakota State University (NDSU) with 41 inspectors using an industrial-strength SRS document that resulted in fault logs. When compared against human experts, our approach achieved F-measure of up to 83% in extracting the relevant key phrases using supervised KPE algorithms. In conclusion, our automated KPE and mapping approach has the potential to reduce manual overhead and assist authors during the fault-fixation post-inspection.","PeriodicalId":378352,"journal":{"name":"14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128125251","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: 2

Model-Based Testing in Practice: An Industrial Case Study using GraphWalker 基于模型的测试实践:使用GraphWalker的工业案例研究

14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2021-02-25 DOI: 10.1145/3452383.3452388

M. Zafar, W. Afzal, Eduard Paul Enoiu, A. Stratis, Aitor Arrieta, Goiuria Sagardui Mendieta

{"title":"Model-Based Testing in Practice: An Industrial Case Study using GraphWalker","authors":"M. Zafar, W. Afzal, Eduard Paul Enoiu, A. Stratis, Aitor Arrieta, Goiuria Sagardui Mendieta","doi":"10.1145/3452383.3452388","DOIUrl":"https://doi.org/10.1145/3452383.3452388","url":null,"abstract":"Model-based testing (MBT) is a test design technique that supports the automation of software testing processes and generates test artefacts based on a system model representing behavioural aspects of the system under test (SUT). Previous research has shown some positive aspects of MBT such as low-cost test case generation and fault detection effectiveness. However, it is still a challenge for both practitioners and researchers to evaluate MBT tools and techniques in real, industrial settings. Consequently, the empirical evidence regarding the mainstream use, including the modelling and test case generation using MBT tools, is limited. In this paper, we report the results of a case study on applying GraphWalker, an open-source tool for MBT, on an industrial cyber-physical system (i.e., a Train Control Management System developed by Bombardier Transportation in Sweden), from modelling of real-world requirements and test specifications to test case generation. We evaluate the models of the SUT for completeness and representativeness, compare MBT with manual test cases written by practitioners using multiple attributes as well as share our experiences of selecting and using GraphWalker for industrial application. The results show that a model of the SUT created using both requirements and test specifications provides better understanding of the SUT from testers’ perspective, making it more complete and representative than the model created based only on the requirements specification alone. The generated model-based test cases are longer in terms of the number of test steps, achieve better edge coverage and can cover requirements more frequently in different orders while achieving the same level of requirements coverage as manually created test cases.","PeriodicalId":378352,"journal":{"name":"14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129545363","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: 8

Understanding Software Quality Metrics for Virtual Reality Products - A Mapping Study 理解虚拟现实产品的软件质量度量-一个映射研究

14th Innovations in Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2021-02-25 DOI: 10.1145/3452383.3452391

Mohit Kuri, Sai Anirudh Karre, Y. R. Reddy

引用次数: 1