{"title":"面向软件质量工程的DevOps方法","authors":"Juan F. Pérez, Weikun Wang, G. Casale","doi":"10.1145/2693561.2693564","DOIUrl":null,"url":null,"abstract":"DevOps is a novel trend in software engineering that aims at bridging the gap between development and operations, putting in particular the developer in greater control of deployment and application runtime. Here we consider the problem of designing a tool capable of providing feedback to the developer on the performance, reliability, and in general quality characteristics of the application at runtime. This raises a number of questions related to what measurement information should be carried back from runtime to design-time and what degrees of freedom should be provided to the developer in the evaluation of performance data. To answer these questions, we describe the design of a filling-the-gap (FG) tool, a software system capable of automatically analyzing performance data either directly or through statistical inference. A natural application of the FG tool is the continuous training of stochastic performance models, such as layered queueing networks, that can inform developers on how to refactor the software architecture.","PeriodicalId":235512,"journal":{"name":"Workshop on Software and Performance","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Towards a DevOps Approach for Software Quality Engineering\",\"authors\":\"Juan F. Pérez, Weikun Wang, G. Casale\",\"doi\":\"10.1145/2693561.2693564\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"DevOps is a novel trend in software engineering that aims at bridging the gap between development and operations, putting in particular the developer in greater control of deployment and application runtime. Here we consider the problem of designing a tool capable of providing feedback to the developer on the performance, reliability, and in general quality characteristics of the application at runtime. This raises a number of questions related to what measurement information should be carried back from runtime to design-time and what degrees of freedom should be provided to the developer in the evaluation of performance data. To answer these questions, we describe the design of a filling-the-gap (FG) tool, a software system capable of automatically analyzing performance data either directly or through statistical inference. A natural application of the FG tool is the continuous training of stochastic performance models, such as layered queueing networks, that can inform developers on how to refactor the software architecture.\",\"PeriodicalId\":235512,\"journal\":{\"name\":\"Workshop on Software and Performance\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-01-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on Software and Performance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2693561.2693564\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Software and Performance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2693561.2693564","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards a DevOps Approach for Software Quality Engineering
DevOps is a novel trend in software engineering that aims at bridging the gap between development and operations, putting in particular the developer in greater control of deployment and application runtime. Here we consider the problem of designing a tool capable of providing feedback to the developer on the performance, reliability, and in general quality characteristics of the application at runtime. This raises a number of questions related to what measurement information should be carried back from runtime to design-time and what degrees of freedom should be provided to the developer in the evaluation of performance data. To answer these questions, we describe the design of a filling-the-gap (FG) tool, a software system capable of automatically analyzing performance data either directly or through statistical inference. A natural application of the FG tool is the continuous training of stochastic performance models, such as layered queueing networks, that can inform developers on how to refactor the software architecture.