Abstract: A computer that receives a set of names of coverage events. The computer creates, by a machine learning-based technique, groups from the set of received names of the coverage events based on the set of names of the coverage events. The computer generates a cross product coverage model from the created groups and identifies subgroups of uncovered events for each of the created groups.

Abstract: A browse node page is addressed by its path. As a result, a web crawler may be more likely to find the browse node than the corresponding parameter-based search page. The browse node may be further distinguished from a search result page by the use of a title or header metatag that indicates information about the browse node and distinguishes the browse node from a general search result page. The number of combinations of keywords, categories, and key-value pairs makes the creation of a browse node for every possible combination prohibitive in all but the simplest applications. Methods and systems to identify which search result pages should be converted to browse nodes are disclosed herein.

Abstract: An example system includes a processor to receive a template-aware coverage data that tracks probabilities of events in a list of events being hit for a set of test-templates over a first and second predetermined period of time. The processor is to generate a hit prediction score for each combination of unhit event in the events and each test-template in the set of test-templates of the second predetermined period of time. The hit prediction score indicates a probability of an unhit event being hit by a particular test-template in a future third predetermined period of time based on the template-aware coverage data and similarities between the events and the test-templates. The processor is to generate a template score for each test-template based on the hit prediction scores for each test-template. The processor is to select a test-template from the set of test-templates based on the template score.

Abstract: A method, apparatus and product for testing a system under development. The method comprises obtaining information including a current version of a code, and predicting that a subset of code elements from the current version of the code are bug-prone elements. The method comprises determining one or more coverage events corresponding to the bug-prone elements. The method further comprises determining a testing policy based on the one or more coverage events that correspond to the bug-prone elements, wherein the testing policy is determined based on a statistical analysis of coverage likelihood of tests generated based on a test template for each coverage event of the one or more coverage events. The method further comprises implementing the testing policy.

Abstract: A method, apparatus and product for testing a system under development. The method comprises obtaining information including a current version of a code, and predicting that a subset of code elements from the current version of the code are bug-prone elements. The method comprises determining one or more coverage events corresponding to the bug-prone elements. The method further comprises determining a testing policy based on the one or more coverage events that correspond to the bug-prone elements, wherein the testing policy is determined based on a statistical analysis of coverage likelihood of tests generated based on a test template for each coverage event of the one or more coverage events. The method further comprises implementing the testing policy.

Abstract: A browse node page is addressed by its path. As a result, a web crawler may be more likely to find the browse node than the corresponding parameter-based search page. The browse node may be further distinguished from a search result page by the use of a title or header metatag that indicates information about the browse node and distinguishes the browse node from a general search result page. The number of combinations of keywords, categories, and key-value pairs makes the creation of a browse node for every possible combination prohibitive in all but the simplest applications. Methods and systems to identify which search result pages should be converted to browse nodes are disclosed herein.

Abstract: An example system includes a processor to receive a template-aware coverage data that tracks probabilities of events in a list of events being hit for a set of test-templates over a first and second predetermined period of time. The processor is to generate a hit prediction score for each combination of unhit event in the events and each test-template in the set of test-templates of the second predetermined period of time. The hit prediction score indicates a probability of an unhit event being hit by a particular test-template in a future third predetermined period of time based on the template-aware coverage data and similarities between the events and the test-templates. The processor is to generate a template score for each test-template based on the hit prediction scores for each test-template. The processor is to select a test-template from the set of test-templates based on the template score.

Abstract: A computer that receives a set of names of coverage events. The computer creates, by a machine learning-based technique, groups from the set of received names of the coverage events based on the set of names of the coverage events. The computer generates a cross product coverage model from the created groups and identifies subgroups of uncovered events for each of the created groups.

Abstract: A browse node page is addressed by its path. As a result, a web crawler may be more likely to find the browse node than the corresponding parameter-based search page. The browse node may be further distinguished from a search result page by the use of a title or header metatag that indicates information about the browse node and distinguishes the browse node from a general search result page. The number of combinations of keywords, categories, and key-value pairs makes the creation of a browse node for every possible combination prohibitive in all but the simplest applications. Methods and systems to identify which search result pages should be converted to browse nodes are disclosed herein.

Abstract: A browse node page is addressed by its path. As a result, a web crawler may be more likely to find the browse node than the corresponding parameter-based search page. The browse node may be further distinguished from a search result page by the use of a title or header metatag that indicates information about the browse node and distinguishes the browse node from a general search result page. The number of combinations of keywords, categories, and key-value pairs makes the creation of a browse node for every possible combination prohibitive in all but the simplest applications. Methods and systems to identify which search result pages should be converted to browse nodes are disclosed herein.