{"title":"在测试数据搜索中应用程序数据状态多样性","authors":"M. Alshraideh, L. Bottaci","doi":"10.1109/TAIC-PART.2006.37","DOIUrl":null,"url":null,"abstract":"Search-based automatic software test data generation for structural testing depends on the instrumentation of the test goal to construct a many-valued function which is then optimised. The method encounters difficulty when the search is in a region in which the function is not able to discriminate between different candidate test cases because it returns a constant value. A typical example of this problem arises in the instrumentation of branch predicates that depend on the value of a Boolean-valued (flag) variable. Existing transformation techniques can solve many cases of the problem but there are situations for which transformation techniques are inadequate. This paper presents a technique for directing the search when the function that instruments the test goal is not able to discriminate candidate test inputs. The new technique depends on introducing program data-state diversity as an additional search goal. The search is guided by a new evaluation (cost) function made up of two parts, one depends on the conventional instrumentation of the test goal, the other depends on the diversity of the data-states produced during execution of the program under test. The method is demonstrated for a number of example programs for which existing methods are inadequate","PeriodicalId":441264,"journal":{"name":"Testing: Academic & Industrial Conference - Practice And Research Techniques (TAIC PART'06)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Using Program Data-State Diversity in Test Data Search\",\"authors\":\"M. Alshraideh, L. Bottaci\",\"doi\":\"10.1109/TAIC-PART.2006.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Search-based automatic software test data generation for structural testing depends on the instrumentation of the test goal to construct a many-valued function which is then optimised. The method encounters difficulty when the search is in a region in which the function is not able to discriminate between different candidate test cases because it returns a constant value. A typical example of this problem arises in the instrumentation of branch predicates that depend on the value of a Boolean-valued (flag) variable. Existing transformation techniques can solve many cases of the problem but there are situations for which transformation techniques are inadequate. This paper presents a technique for directing the search when the function that instruments the test goal is not able to discriminate candidate test inputs. The new technique depends on introducing program data-state diversity as an additional search goal. The search is guided by a new evaluation (cost) function made up of two parts, one depends on the conventional instrumentation of the test goal, the other depends on the diversity of the data-states produced during execution of the program under test. The method is demonstrated for a number of example programs for which existing methods are inadequate\",\"PeriodicalId\":441264,\"journal\":{\"name\":\"Testing: Academic & Industrial Conference - Practice And Research Techniques (TAIC PART'06)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Testing: Academic & Industrial Conference - Practice And Research Techniques (TAIC PART'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAIC-PART.2006.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Testing: Academic & Industrial Conference - Practice And Research Techniques (TAIC PART'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAIC-PART.2006.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Program Data-State Diversity in Test Data Search
Search-based automatic software test data generation for structural testing depends on the instrumentation of the test goal to construct a many-valued function which is then optimised. The method encounters difficulty when the search is in a region in which the function is not able to discriminate between different candidate test cases because it returns a constant value. A typical example of this problem arises in the instrumentation of branch predicates that depend on the value of a Boolean-valued (flag) variable. Existing transformation techniques can solve many cases of the problem but there are situations for which transformation techniques are inadequate. This paper presents a technique for directing the search when the function that instruments the test goal is not able to discriminate candidate test inputs. The new technique depends on introducing program data-state diversity as an additional search goal. The search is guided by a new evaluation (cost) function made up of two parts, one depends on the conventional instrumentation of the test goal, the other depends on the diversity of the data-states produced during execution of the program under test. The method is demonstrated for a number of example programs for which existing methods are inadequate