Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference)最新文献_第2页

A knowledge centric approach to conceptualizing robotic solutions 以知识为中心的机器人解决方案概念化方法

Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2019-02-14 DOI: 10.1145/3299771.3299782

S. Chaudhuri, Amar Banerjee, N. Swaminathan, Venkatesh Choppella, A. Pal, P. Balamurali

{"title":"A knowledge centric approach to conceptualizing robotic solutions","authors":"S. Chaudhuri, Amar Banerjee, N. Swaminathan, Venkatesh Choppella, A. Pal, P. Balamurali","doi":"10.1145/3299771.3299782","DOIUrl":"https://doi.org/10.1145/3299771.3299782","url":null,"abstract":"The focus of the ongoing Digital and Industry 4.0 revolution is on re-engineering business operations to take advantage of various technologies, including robotics. Conceptualizing, say, a robotics solution to automate aspects of warehouse operations involves multiple activities: understanding the problem space in sufficient detail to identify the right automation opportunities; working through the space of possible solution options and developing the solution design; and building a prototype solution with sufficient functional detail to enable customer experts to assess its suitability with respect to multiple concerns, and its impact on the business processes and environment. Only after that can a project be initiated to engineer and deploy the production solution, while making the necessary changes to the business system. With current practice, conceptualization and prototyping typically takes several months and considerable manual effort. In this paper, we present an environment for rapid prototyping of robotics solutions that facilitates a knowledge-centric approach based on capability composition. The environment enables systematic capture of functional domain knowledge, modular composition of solution space capabilities, and expression of the solution concept using a constrained natural language. Detailed functional simulators are generated automatically from the resulting design. This results in high customer confidence in the solution, substantial reductions in cycle time, and productivity gains due to modular reusability of solution knowledge and components.","PeriodicalId":366188,"journal":{"name":"Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127221855","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: 4

Change-Proneness of Object-Oriented Software Using Combination of Feature Selection Techniques and Ensemble Learning Techniques 结合特征选择技术和集成学习技术的面向对象软件易变性研究

Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2019-02-14 DOI: 10.1145/3299771.3299778

L. Kumar, Sangeeta Lal, Anjali Goyal, N. B. Murthy

{"title":"Change-Proneness of Object-Oriented Software Using Combination of Feature Selection Techniques and Ensemble Learning Techniques","authors":"L. Kumar, Sangeeta Lal, Anjali Goyal, N. B. Murthy","doi":"10.1145/3299771.3299778","DOIUrl":"https://doi.org/10.1145/3299771.3299778","url":null,"abstract":"Change-prone modules are characterized as the programming parts in the source code which have high probability to alter in the future. Change-proneness prediction helps software testers to streamline and concentrate their testing assets on the modules which have a higher probability of alteration. In this work, we perform an empirical study of 11 feature selection techniques to identify the suitable set of source code metrics, out of 21 metrics, for change-proneness prediction. We first proposed a source code validation framework that includes Wilcoxon signed rank test, univariate logistic regression analysis, cross correlation analysis, multivariate linear regression stepwise forward selection. We then compared the results of proposed software metrics validation framework (PFST) with 10 feature selection techniques. The selected features are then used for predicting change-proneness using 18 machine learning algorithms. Experimental results show that the prediction model built using source code metrics obtained from PFST outperforms other techniques.","PeriodicalId":366188,"journal":{"name":"Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127414924","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: 6

A Threat Intelligence Tool for the Security Development Lifecycle 安全开发生命周期的威胁情报工具

Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2019-02-14 DOI: 10.1145/3299771.3299789

R. Kannavara, Jacob Vangore, William Roberts, M. Lindholm, Priti Shrivastav

引用次数: 2

Formal Verification of Optimizing Transformations during High-level Synthesis 高级综合过程中优化转换的形式化验证

Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2019-02-14 DOI: 10.1145/3299771.3299797

Ramanuj Chouksey, C. Karfa, Purandar Bhaduri

引用次数: 1

Software Engineering for Smart Cyber-Physical Systems: Challenges and Opportunities 智能信息物理系统的软件工程:挑战与机遇

Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2019-02-14 DOI: 10.1145/3299771.3301650

H. Giese

{"title":"Software Engineering for Smart Cyber-Physical Systems: Challenges and Opportunities","authors":"H. Giese","doi":"10.1145/3299771.3301650","DOIUrl":"https://doi.org/10.1145/3299771.3301650","url":null,"abstract":"Currently, a transformation of our technical world into a networked technical world where besides the embedded systems with their interaction with the physical world the interconnection of these nodes in the cyber world becomes a reality can be observed. In parallel nowadays there is a strong trend to employ artificial intelligence techniques and in particular machine learning to make software behave smart. Often cyber-physical systems must be self-adaptive at the level of the individual systems to operate as elements in open, dynamic, and deviating overall structures and to adapt to open and dynamic contexts while being developed, operated, evolved, and governed independently. In this presentation, we will first discuss the envisioned future scenarios for cyber-physical systems with an emphasis on the synergies networking can offer and then characterize which challenges for the design, production, and operation of these systems result. We will then discuss to what extent our current capabilities, in particular concerning software engineering match these challenges and where substantial improvements for the software engineering are crucial. In today's software engineering for embedded systems models are used to plan systems upfront to maximize envisioned properties on the one hand and minimize cost on the other hand. When applying the same ideas to software for smart cyber-physical systems, it soon turned out that for these systems often somehow more subtle links between the involved models and the requirements, users, and environment exist. Self-adaptation and runtime models have been advocated as concepts to covers the demands that result from these subtler links. Lately, both trends have been brought together more thoroughly by the notion of self-aware computing systems. We will review the underlying causes, discuss some our work in this direction, and outline related open challenges and potential for future approaches to software engineering for smart cyber-physical systems.","PeriodicalId":366188,"journal":{"name":"Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133033682","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

A RFP System for Generating Response to a Request for Proposal 用于生成对提案请求的响应的RFP系统

Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2019-02-14 DOI: 10.1145/3299771.3299779

Asha Rajbhoj, Padmalata V. Nistala, V. Kulkarni, Gomathi Ganesan

{"title":"A RFP System for Generating Response to a Request for Proposal","authors":"Asha Rajbhoj, Padmalata V. Nistala, V. Kulkarni, Gomathi Ganesan","doi":"10.1145/3299771.3299779","DOIUrl":"https://doi.org/10.1145/3299771.3299779","url":null,"abstract":"Responding to Request for Proposal (RFP) with comprehensive solutions is central to IT Services business. Typically, an RFP comprises a set of questions spanning across various domain areas. Current industry practices largely rely on Subject Matter Experts to analyze questions and search multiple information sources to come up with the best possible response for a question keeping in view the customer context. With expertise typically in short supply, it becomes increasingly difficult to manage growing RFP volumes. To address this problem we propose a generic solution meta-model and a system that can generate a draft response to an RFP to be augmented manually later. The generation step uses NLP, modelling and search techniques augmented with a knowledge base to generate knowledge search queries to retrieve suitable answers to a set of RFP questions and compose RFP response. In this paper, we share a RFP response generation approach, its implementation, results and lessons learnt from deployment with one of the business units having high volumes of proposal turnover. Initial results show that RFP system is effective in enabling response generation with ~76% mean query precision and 86% mean query recall.","PeriodicalId":366188,"journal":{"name":"Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114368739","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

Enhancing Test Cases generated by Concolic Testing 增强由Concolic测试生成的测试用例

Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2019-02-14 DOI: 10.1145/3299771.3299781

Arpita Dutta, Shubham Kumar, Sangharatna Godboley

引用次数: 4

Making Sense of Actor Behaviour: An Algebraic Filmstrip Pattern and its Implementation 演员行为的理解:一种代数胶片模式及其实现

Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2019-02-14 DOI: 10.1145/3299771.3299783

T. Clark, B. Barn, V. Kulkarni, Souvik Barat

引用次数: 2

Evolutionary Trends in the Collaborative Review Process of a Large Software System 大型软件系统协同评审过程的演化趋势

Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2019-02-14 DOI: 10.1145/3299771.3299792

Subhajit Datta, Poulami Sarkar

引用次数: 0

ThrustHetero ThrustHetero

Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference) Pub Date : 2019-02-14 DOI: 10.1145/3299771.3299773

Ajai V. George, Sankar Manoj, S. Sarkar

{"title":"ThrustHetero","authors":"Ajai V. George, Sankar Manoj, S. Sarkar","doi":"10.1145/3299771.3299773","DOIUrl":"https://doi.org/10.1145/3299771.3299773","url":null,"abstract":"Heterogeneous compute architectures like Multi-Core CPUs, CUDA GPUs, and Intel Xeon Phis have become prevalent over the years. While heterogeneity makes architecture specific features available to the programmer, it also makes application development difficult, as one needs to plan for optimal usage of architectural features, suitable partitioning of the workload, communication and data transfer among the participating devices. A suitable design abstraction that hides such variabilities of the underlying devices and at the same time exploits their computing capabilities, can improve developer productivity. In this work, we present \"ThrustHetero\", a lightweight framework based on NVIDIA's Thrust, that provides an abstraction over several devices such as GPUs, Xeon Phis and multicore, yet allows developers to easily leverage the full compute capability of these devices. We also demonstrate a novel method for workload distribution in two stages - micro-benchmarking during framework installations to find good proportions and then using this information during application execution. We consider four classes of applications based on how they would perform on various computing architectures on the basis of the amount of branching present in the application. We show that the framework produces a good workload distribution proportions for each class of application and also show that the framework is scalable and portable. Further, we compare the performance and ease of development when using the framework with the native versions of various benchmarks and obtain favorable results.","PeriodicalId":366188,"journal":{"name":"Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115161505","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