Christopher Henard, Mike Papadakis, Gilles Perrouin, Jacques Klein, Yves Le Traon
{"title":"软件产品线的多目标测试生成","authors":"Christopher Henard, Mike Papadakis, Gilles Perrouin, Jacques Klein, Yves Le Traon","doi":"10.1145/2491627.2491635","DOIUrl":null,"url":null,"abstract":"Software Products Lines (SPLs) are families of products sharing common assets representing code or functionalities of a software product. These assets are represented as features, usually organized into Feature Models (FMs) from which the user can configure software products. Generally, few features are sufficient to allow configuring millions of software products. As a result, selecting the products matching given testing objectives is a difficult problem.\n The testing process usually involves multiple and potentially conflicting testing objectives to fulfill, e.g. maximizing the number of optional features to test while at the same time both minimizing the number of products and minimizing the cost of testing them. However, most approaches for generating products usually target a single objective, like testing the maximum amount of feature interactions. While focusing on one objective may be sufficient in certain cases, this practice does not reflect real-life testing situations.\n The present paper proposes a genetic algorithm to handle multiple conflicting objectives in test generation for SPLs. Experiments conducted on FMs of different sizes demonstrate the effectiveness, feasibility and practicality of the introduced approach.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"108","resultStr":"{\"title\":\"Multi-objective test generation for software product lines\",\"authors\":\"Christopher Henard, Mike Papadakis, Gilles Perrouin, Jacques Klein, Yves Le Traon\",\"doi\":\"10.1145/2491627.2491635\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software Products Lines (SPLs) are families of products sharing common assets representing code or functionalities of a software product. These assets are represented as features, usually organized into Feature Models (FMs) from which the user can configure software products. Generally, few features are sufficient to allow configuring millions of software products. As a result, selecting the products matching given testing objectives is a difficult problem.\\n The testing process usually involves multiple and potentially conflicting testing objectives to fulfill, e.g. maximizing the number of optional features to test while at the same time both minimizing the number of products and minimizing the cost of testing them. However, most approaches for generating products usually target a single objective, like testing the maximum amount of feature interactions. While focusing on one objective may be sufficient in certain cases, this practice does not reflect real-life testing situations.\\n The present paper proposes a genetic algorithm to handle multiple conflicting objectives in test generation for SPLs. Experiments conducted on FMs of different sizes demonstrate the effectiveness, feasibility and practicality of the introduced approach.\",\"PeriodicalId\":339444,\"journal\":{\"name\":\"Software Product Lines Conference\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"108\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Software Product Lines Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2491627.2491635\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software Product Lines Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2491627.2491635","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-objective test generation for software product lines
Software Products Lines (SPLs) are families of products sharing common assets representing code or functionalities of a software product. These assets are represented as features, usually organized into Feature Models (FMs) from which the user can configure software products. Generally, few features are sufficient to allow configuring millions of software products. As a result, selecting the products matching given testing objectives is a difficult problem.
The testing process usually involves multiple and potentially conflicting testing objectives to fulfill, e.g. maximizing the number of optional features to test while at the same time both minimizing the number of products and minimizing the cost of testing them. However, most approaches for generating products usually target a single objective, like testing the maximum amount of feature interactions. While focusing on one objective may be sufficient in certain cases, this practice does not reflect real-life testing situations.
The present paper proposes a genetic algorithm to handle multiple conflicting objectives in test generation for SPLs. Experiments conducted on FMs of different sizes demonstrate the effectiveness, feasibility and practicality of the introduced approach.