Abstract: Technologies are described for ranking test cases related to changes in a software code base using at least a portion of a call graph that is generated from the software code base. The at least a portion of the call graph comprises method nodes corresponding to methods in the software code base. The method nodes represent control flow relationships between the methods in the software code base. The at least a portion of the call graph also comprises test case nodes. Each test case node is connected to one or more method nodes corresponding to coverage of the one or more method nodes by the test case node. Using the at least a portion of the call graph, the test case nodes are automatically ranked. Ranking of the test case nodes is performed by evaluating various criteria associated with the at least a portion of the call graph.

Abstract: Technologies are described for ranking test cases related to changes in a software code base using at least a portion of a call graph that is generated from the software code base. The at least a portion of the call graph comprises method nodes corresponding to methods in the software code base. The method nodes represent control flow relationships between the methods in the software code base. The at least a portion of the call graph also comprises test case nodes. Each test case node is connected to one or more method nodes corresponding to coverage of the one or more method nodes by the test case node. Using the at least a portion of the call graph, the test case nodes are automatically ranked. Ranking of the test case nodes is performed by evaluating various criteria associated with the at least a portion of the call graph.

Abstract: Technologies are described for identifying critical methods in a software code base. The critical methods are identified using a call graph that is generated from the software code base. The call graph comprises method nodes that correspond to the methods of the software code base. One or more algorithms are applied to the call graph to calculate values for the method nodes of the call graph. The one or more algorithms comprise a betweenness centrality algorithm, a harmonic closeness centrality algorithm, or a NodeRank centrality algorithm. From the values generated by the algorithms, criticality scores are determined for the method nodes. The criticality scores are then used to determine which of the method nodes are critical method nodes. Indications of the critical method nodes can be output.

Abstract: A code base is parsed to identify methods having changes in a code base since a last code commit. Thereafter, a call graph is traversed to identify test cases implicated by the identified methods having changes in the code base. The call graph can be a directed call graph comprising a plurality of connected nodes in which a first subset of the connected nodes are method nodes representing each method in the code base in which unidirectional edges connecting method nodes correspond to invocations by a calling method to a callee method, and in which a second subset of the connected nodes are test case nodes representing each of a plurality of available test cases to test the code base. The test case nodes are each coupled to one or more method nodes by unidirectional edges that correspond to the test case coverage of the method.

Abstract: A code base is parsed to identify methods encapsulated therein. Thereafter, a call graph is generated based on the parsing using a graph generation technique. The call graph is a directed call graph comprising a plurality of nodes characterizing the identified methods. It can then be determined, based on one or more design patterns used to generate the code base, that at least a portion of the nodes generated call graph are disconnected nodes. At least two of the disconnected nodes are then connected using a stitching algorithm to result in a modified call graph. Data characterizing the modified call graph can then be provided (e.g., displayed in a graphical user interface, stored in a database, loaded into memory, transmitted to a remote computing device, etc.).

Abstract: A code base is parsed to identify methods having changes in a code base since a last code commit. Thereafter, a call graph is traversed to identify test cases implicated by the identified methods having changes in the code base. The call graph can be a directed call graph comprising a plurality of connected nodes in which a first subset of the connected nodes are method nodes representing each method in the code base in which unidirectional edges connecting method nodes correspond to invocations by a calling method to a callee method, and in which a second subset of the connected nodes are test case nodes representing each of a plurality of available test cases to test the code base. The test case nodes are each coupled to one or more method nodes by unidirectional edges that correspond to the test case coverage of the method.

Abstract: A code base is parsed to identify methods encapsulated therein. Thereafter, a call graph is generated based on the parsing using a graph generation technique. The call graph is a directed call graph comprising a plurality of nodes characterizing the identified methods. It can then be determined, based on one or more design patterns used to generate the code base, that at least a portion of the nodes generated call graph are disconnected nodes. At least two of the disconnected nodes are then connected using a stitching algorithm to result in a modified call graph. Data characterizing the modified call graph can then be provided (e.g., displayed in a graphical user interface, stored in a database, loaded into memory, transmitted to a remote computing device, etc.).