Abstract: Tools and techniques assist developers with the detection of memory leaks by using correlation of data type memory usage trends. In particular, investigations of memory leaks can be prioritized without always resorting to the use of bulky and performance-degrading memory dumps, by using these tools and techniques to identify leaky correlated data types. Data about a program's memory usage is processed to identify memory usage trends over time for respective data types, and the trends are searched for significant correlations. Correlated trends (and hence their corresponding data types) are grouped. Memory usage analysis information is displayed for grouped data types, such as the names of the most rapidly leaking data types, the names of correlated data types, leak rates, and leak amounts in terms of memory size and/or data object counts. Memory usage data may also be correlated with processing load requests to indicate which requests have associated memory leaks.

Abstract: Tools and techniques assist developers with the detection of memory leaks by using correlation of data type memory usage trends. In particular, investigations of memory leaks can be prioritized without always resorting to the use of bulky and performance-degrading memory dumps, by using these tools and techniques to identify leaky correlated data types. Data about a program's memory usage is processed to identify memory usage trends over time for respective data types, and the trends are searched for significant correlations. Correlated trends (and hence their corresponding data types) are grouped. Memory usage analysis information is displayed for grouped data types, such as the names of the most rapidly leaking data types, the names of correlated data types, leak rates, and leak amounts in terms of memory size and/or data object counts. Memory usage data may also be correlated with processing load requests to indicate which requests have associated memory leaks.

Abstract: Data applications may be developed within an integrated development environment comprising an iterative cycle of writing source code, building the source code, running the data application, and testing the data application. The development becomes iterative because the application is torn down, redesigned, rebuilt, and re-executed if the data application is modified. Developing an application at runtime is disclosed herein, which is generally more efficient than conventional iterative techniques. As provided herein, runtime application comprising prebuilt components is presented to a user. The runtime application may be modified through modification gestures. An update assembly may be built based upon the modification gestures. The runtime application may be updated based upon the updated assembly.

Abstract: A method and system for testing the interoperability of application programs. The interoperability testing system uses an application-independent test script and application-specific command scripts to test the interoperability of application programs. An application-independent test script contains a series of high-level application-independent commands that are to be performed to test the application programs. Each application program to be tested has a corresponding application-specific command script. An application-specific command script contains an implementation of each high-level command for the corresponding application program. To test application programs, the interoperability testing system executes an application-independent test script by reading each high-level command from the test script, retrieving the implementation of that high-level command for the application program that is to perform that command, and executing that implementation.