Pub Date : 2021-11-01DOI: 10.1109/ase51524.2021.9678878
R. Krishna, A. Kalia, S. Sinha, Rachel Tzoref-Brill, J. Rofrano, Jin Xiao
Enterprises are increasingly moving their production workloads to the cloud to take advantage of capabilities, such as streamlined provisioning of infrastructure and services, elasticity, scalability, reliability, and security. To leverage such capabilities, monolithic applications typically have to be decomposed to cloud-native architectures, such as microservices. A microservice encapsulates a small and well-defined set of business functionalities and interacts with other services using lightweight mechanisms, often implemented as RESTful APIs. A recent report shows that only 20% of the enterprise workloads are in the cloud, and they were predominately written for native cloud architectures. This leaves 80% of legacy applications onpremises, waiting to be refactored and modernized for the cloud. In this tutorial, we will discuss the motivation---supported by illustrative industrial case studies---for modernizing and migrating legacy applications to cloud. We will then present a detailed tool-supported approach for transforming a monolithic Java application into microservices. This will be followed by a handson virtual lab, where participants will have the opportunity to apply the learned concepts on a real-world enterprise application. Finally, we will conclude the tutorial with a discussion of promising directions for future research more broadly in the area of application modernization.
{"title":"Transforming monolithic applications to microservices with Mono2Micro","authors":"R. Krishna, A. Kalia, S. Sinha, Rachel Tzoref-Brill, J. Rofrano, Jin Xiao","doi":"10.1109/ase51524.2021.9678878","DOIUrl":"https://doi.org/10.1109/ase51524.2021.9678878","url":null,"abstract":"Enterprises are increasingly moving their production workloads to the cloud to take advantage of capabilities, such as streamlined provisioning of infrastructure and services, elasticity, scalability, reliability, and security. To leverage such capabilities, monolithic applications typically have to be decomposed to cloud-native architectures, such as microservices. A microservice encapsulates a small and well-defined set of business functionalities and interacts with other services using lightweight mechanisms, often implemented as RESTful APIs. A recent report shows that only 20% of the enterprise workloads are in the cloud, and they were predominately written for native cloud architectures. This leaves 80% of legacy applications onpremises, waiting to be refactored and modernized for the cloud. In this tutorial, we will discuss the motivation---supported by illustrative industrial case studies---for modernizing and migrating legacy applications to cloud. We will then present a detailed tool-supported approach for transforming a monolithic Java application into microservices. This will be followed by a handson virtual lab, where participants will have the opportunity to apply the learned concepts on a real-world enterprise application. Finally, we will conclude the tutorial with a discussion of promising directions for future research more broadly in the area of application modernization.","PeriodicalId":414461,"journal":{"name":"Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122288723","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}
Pub Date : 2021-11-01DOI: 10.1109/ase51524.2021.9678707
M. Mannion, H. Kaindl
Several socio-economic trends are driving customer demands towards individualization. Many suppliers are responding by offering supplier-led software product design customization choices ("mass customization"). Some are also offering customer-led software product design choices ("mass personalization"). This tutorial introduces these concepts and explores the implications for software product line development. One particular technical challenge is being able to respond to and manage at scale the increasing variety of common, supplier-led and customer-led features. We will discuss two different approaches to address this challenge. One is grounded in feature modelling, the other in case-based reasoning, where the latter relies on measuring similarities. We will then describe a specific product similarity evaluation process in which a product configured from a product line feature model is represented as a weighted binary string, the overall similarity between products is compared using a binary string metric, and the significance of individual feature combinations for product similarity can be explored by modifying the weights. We will illustrate our ideas with mobile phone worked examples, and discuss some of the benefits and limitations of this approach.
{"title":"Enhancing requirements reuse through automated similarity matching","authors":"M. Mannion, H. Kaindl","doi":"10.1109/ase51524.2021.9678707","DOIUrl":"https://doi.org/10.1109/ase51524.2021.9678707","url":null,"abstract":"Several socio-economic trends are driving customer demands towards individualization. Many suppliers are responding by offering supplier-led software product design customization choices (\"mass customization\"). Some are also offering customer-led software product design choices (\"mass personalization\"). This tutorial introduces these concepts and explores the implications for software product line development. One particular technical challenge is being able to respond to and manage at scale the increasing variety of common, supplier-led and customer-led features. We will discuss two different approaches to address this challenge. One is grounded in feature modelling, the other in case-based reasoning, where the latter relies on measuring similarities. We will then describe a specific product similarity evaluation process in which a product configured from a product line feature model is represented as a weighted binary string, the overall similarity between products is compared using a binary string metric, and the significance of individual feature combinations for product similarity can be explored by modifying the weights. We will illustrate our ideas with mobile phone worked examples, and discuss some of the benefits and limitations of this approach.","PeriodicalId":414461,"journal":{"name":"Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123646272","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：