Abstract: A mechanism is provided in a data processing system having a processor and a memory. The memory comprises instructions which are executed by the processor to cause the processor to implement a training system for finding an optimal surface for hierarchical classification task on an ontology. The training system receives a training data set and a hierarchical ontology data structure. A surface finding component executing within the training system selects a surface that passes through each path from a root to a leaf node in the hierarchical ontology data structure. The surface finding component determines a plurality of adjacent surfaces that differ from the selected component by one node. The surface finding component selects an optimal surface, based on the selected surface and the plurality of adjacent surfaces, that maximizes accuracy and coverage. The training system trains a classifier model for a cognitive system using the optimal surface and the training data set.

Abstract: A mechanism is provided in a data processing system having a processor and a memory. The memory comprises instructions which are executed by the processor to cause the processor to implement a training system for finding an optimal surface for hierarchical classification task on an ontology. The training system receives a training data set and a hierarchical ontology data structure. A surface finding component executing within the training system selects a surface that passes through each path from a root to a leaf node in the hierarchical ontology data structure. The surface finding component determines a plurality of adjacent surfaces that differ from the selected component by one node. The surface finding component selects an optimal surface, based on the selected surface and the plurality of adjacent surfaces, that maximizes accuracy and coverage. The training system trains a classifier model for a cognitive system using the optimal surface and the training data set.

Abstract: A method, system and computer program product, the method comprising: receiving a user document describing at least a part of a system to be tested; computing a similarity measurement between the user document and documents in a document corpus, each describing at least part of a system and associated with a combinatorial model representing the at least part of the system, wherein the combinatorial model comprises a set of attributes, a respective domain for each attribute defining possible values for the attribute, and restrictions, wherein each restriction comprises at least one attribute, a respective value and a logical operator, based upon the similarity measurement, selecting selected documents from the document corpus; obtaining one or more combinatorial models corresponding to the selected documents; selecting elements from the combinatorial models; generating an initial combinatorial model for the user document, wherein said generating comprises adding the elements to the initial combinatorial model.

Abstract: A method, system and computer program product, the method comprising: receiving a partial description of a combinatorial model defining a test space and comprising a set of attributes, a respective domain for each attribute defining possible values for the attribute, and restrictions, each comprising an attribute, a respective value and a logical operator, the partial description comprising an attribute and a value thereof; computing a similarity measurement between the partial description and each model in a corpus, based on similarity of attributes and domains, and not on a test space defined by compared models, whereby similarity between models is indifferent to a size of the test space of the models; selecting models from the corpus according to the computed similarity measurements; determining elements from the selected models to be suggested for modifying the partial description; and outputting the suggestions to modify the partial description useful for completing the combinatorial model.

Abstract: An example system includes a processor to receive a source code and history information, wherein the history information includes a version control history or a defect history, or a combination of the version control history and the defect history. The processor is to also divide the source code into security-related components and security-non-related components. The processor is to further calculate security metrics for each of the security-related components and each of the security-non-related components based on the history information. The processor is also to compare the security metrics of the security-related components with the security metrics of the security-non-related components. The processor is to further generate a visual representation comprising a highlighted area of concern based on the comparison.

Abstract: Embodiments include method, systems and computer program products for identifying dependency relationships in a software product. Aspects include obtaining change history data for the software product and extracting a plurality of change elements from the change history data, each change element including an identifier of a code segment that was changed and a timestamp of the change. Aspects also include creating a dependency graph based on the plurality of change elements, wherein the dependency graph includes nodes that correspond to the code segments and edges that connect nodes that were both updated in a same logical grouping, calculating a weight for each of the edges based on probability that the nodes connected by the edge will be updated together, and outputting the dependency graph.

Abstract: A method, product and apparatus for creating functional model of test cases. The method comprising obtaining a set of test cases, wherein each test case of the set of test cases comprises free-text; defining one or more tags, wherein each tag of the one or more tags is associated with a query that is configured, when applied, to determine possession of the tag with respect to a test case based on the free-text; applying the queries on the set of test cases to determine possession of the of the one or more tags for each test case; and generating a functional model based on the set of test cases, wherein the functional model comprising for each tag of the one or more tags, a corresponding functional attribute.

Abstract: A method, product and apparatus for creating functional model of test cases. The method comprising obtaining a set of test cases, wherein each test case of the set of test cases comprises free-text; defining one or more tags, wherein each tag of the one or more tags is associated with a query that is configured, when applied, to determine possession of the tag with respect to a test case based on the free-text; applying the queries on the set of test cases to determine possession of the of the one or more tags for each test case; and generating a functional model based on the set of test cases, wherein the functional model comprising for each tag of the one or more tags, a corresponding functional attribute.

Abstract: A method and apparatus for estimating coverage of a computer program from traces, the method comprising: receiving trace data generated by an execution of an executable unit; and estimating coverage of the executable unit from the trace data, wherein estimating coverage comprises estimating trace coverage.

Abstract: A method that includes obtaining an area of text that has changed in a functional document, wherein the functional document corresponds to one or more coverage tasks. The method also includes computing an impact measurement for each of the one or more coverage task, wherein the impact measurement is indicative of a potential to be impacted by the change. As a result of the method it is possible to identify coverage tasks that are estimated to be impacted by the change of the functional document.

Abstract: Method, apparatus and product for test selection based on domination criterion. In some embodiments, excluding from a test suite dominated tests, each of which is dominated by a predetermined number of dominating tests, wherein a dominated test is dominated by a dominating test if each target that is covered by the dominated test is also covered by the dominating test. In some embodiments, a reduced test suite is determined by excluding from a test suite each test that covers a dominated set of targets that is N-dominated by the reduced test suite, wherein a dominated set of targets is N-dominated by a set of tests if each target in the dominated set of targets is covered by at least N tests in the set of tests, wherein N is a predetermined number greater than one.

Abstract: A method and apparatus for estimating coverage of a computer program from traces, the method comprising: receiving trace data generated by an execution of an executable unit; and estimating coverage of the executable unit from the trace data, wherein estimating coverage comprises estimating trace coverage.

Abstract: Systems and methods for detecting faults in a system. The method comprising maintaining diagnostic history for one or more system components; receiving system information about operational state and relational interaction among system components; determining if one or more system components are to be examined, in response to performing an analysis of the diagnostic history, wherein the analysis is performed to determine if the diagnostic history includes any information that may indicate that certain system components or combinations of components are suspected of causing a problem detected in the system, wherein the diagnostic history is maintained based on an at least one examination performed on said one or more components when said one or more components were installed in a system other than the system in which the problem is detected.

Abstract: A method, apparatus and product for software bug prediction. The method comprising obtaining from a plurality of developers probability estimates to areas in a plurality of code partitioned areas of a code, wherein a probability estimate is representative of an estimated probability of the area having a software bug according to a developer of the plurality of developers; and determining a testing strategy of the plurality of code partitioned areas based on the probability estimates.

Abstract: A method for software processing includes extracting from software code under test respective items of meta-information pertaining to elements of the software code and receiving respective quality data regarding the elements of software code. The quality data and meta-information are processed in a computer so as to assign respective metrics to the items of the meta-information responsively to the quality data regarding the elements of the software code to which the items pertain. At least some of the meta-information is presented to a user in accordance with the assigned metrics.

Abstract: Detecting locking discipline violations on shared resources. For example, a method of detecting locking discipline violations of shared resources of a computing platform, by a testing process to be executed concurrently with one or more other processes on said computing platform, the testing process comprising: locking a shared resource of said computing platform; reading a value of the shared resource; locally storing the value of the shared resource; rereading the value of the shared resource after a predefined time period; and generating a locking discipline violation report if the value of said shared resource as reread by said rereading is different from the value of said resource as locally stored by said locally storing.

Abstract: Detecting locking discipline violations on shared resources. For example, a method of detecting locking discipline violations of shared resources of a computing platform, by a testing process to be executed concurrently with one or more other processes on said computing platform, the testing process comprising: locking a shared resource of said computing platform; reading a value of the shared resource; locally storing the value of the shared resource; rereading the value of the shared resource after a predefined time period; and generating a locking discipline violation report if the value of said shared resource as reread by said rereading is different from the value of said resource as locally stored by said locally storing.

Abstract: A functional coverage model may be generated based on a trace. The functional coverage model may comprise values of attributes. The values may be extracted from one or more entries comprised by the trace. Based upon a selection of a field of an exemplary entry, content of the corresponding fields in other entries may be extracted and utilized. In some exemplary embodiments, names of attributes may be extracted from the trace. In some exemplary embodiments, a reference trace may be utilized as a comparative baseline coverage by generating a functional coverage model based upon the reference trace and comparing coverage of a second trace in respect to the functional coverage model with the coverage of the reference trace.

Abstract: A meta attribute useful for functional coverage is computed based on values comprised by two or more matching fields in a trace. The two or more matching fields may be comprised by a single entry of the trace or by a plurality of entries of the trace. A definition of the meta attribute may define which fields of the entries comprise values useful for computation of the meta attributes. The matching entries may be identified based on identifying values within the entries.

Abstract: A coverage analysis tool may determine coverage in respect to heterogeneous coverage tasks associated with different hierarchy levels of a tasks hierarchy. The coverage analysis tool may iteratively refine coverage tasks to determine coverage of sub-tasks. In some cases, coverage tasks may be unrefined in order to reduce overhead of coverage analysis in performance of the software under test, such that the software under test may perform in an essentially similar manner as in non-testing mode.