Abstract: Automatic detection of software program regression points enables developers to more quickly and accurately diagnose and solve issues in changes to software. Traces of instructions are collected from before and after a change to a program or settings thereto on a computing device and are compared to identify differences between the two traces. Areas of differences are ranked and returned to identify the point(s) of regression in the traces to alert a user of programs of behaviors to avoid and/or a developer a point to focus efforts on to patch the responsible program or update other programs around the responsible application.

Abstract: A system generates a command to cause a computing machine to collect information for an issue that occurred with an application. The command is stored in a command list and associated with a computing machine identifier for the computing machine. The system receives a query from the computing machine for the command list. The query includes the computing machine identifier and the system locates the command in the command list based on the command being associated with the computing machine identifier. The system then sends the command to the computing machine where the command dynamically causes the computing machine to collect the information for the issue with the application.

Abstract: A static multi-entry point function with more than one entry point is provided. The function allows callers to enter the function at different entry points using an offset. Each entry point of the function is associated with a different offset, and includes instructions that identify data that is associated with the entry point. Each entry point further includes an instruction that jumps to a common prologue of the function. The common prologue loads the identified data into local variables. The function also includes a functional component that performs different actions depending on the data in the local variables. The function includes a default entry point that is used when the function is called without any offset, so that the function appears to behave like a normal function to scanners.

Abstract: Enhanced longest common subsequence techniques are provided to improve efficiency and accuracy of any process that uses long sequences. Two superscale data sequences are received. Each data sequence is divided into a set of segments based on one or more heuristics or user input. From the sets of segments, pairs of segments are selected and processed using any longest common subsequence algorithm to determine the longest common subsequence for each pair of segments. The results of the processing are merged to determine the enhanced longest subsequence which is the longest common subsequence for the received superscale data sequences. Dividing the superscale data sequences into segments allows for parallel processing of each segment pair, which results in a faster completion time than prior art methods for determining longest common subsequences.

Abstract: A system generates a command to cause a computing machine to collect information for an issue that occurred with an application. The command is stored in a command list and associated with a computing machine identifier for the computing machine. The system receives a query from the computing machine for the command list. The query includes the computing machine identifier and the system locates the command in the command list based on the command being associated with the computing machine identifier. The system then sends the command to the computing machine where the command dynamically causes the computing machine to collect the information for the issue with the application.

Abstract: Testing is provided for software applications in each of a plurality of languages without a separate automation test script (TAS) for each language. A TAS runs on multiple language platforms without any change to the TAS. A method of running a test script in multiple language platforms comprises receiving a TAS for an application in a first language, retrieving language metadata used by the TAS, replacing the language metadata in the TAS with a language neutral identifier (LNI), retrieving data associated with a second language based on the LNI and providing the data associated with the second language to the TAS.

Abstract: Enhanced longest common subsequence techniques are provided to improve efficiency and accuracy of any process that uses long sequences. Two superscale data sequences are received. Each data sequence is divided into a set of segments based on one or more heuristics or user input. From the sets of segments, pairs of segments are selected and processed using any longest common subsequence algorithm to determine the longest common subsequence for each pair of segments. The results of the processing are merged to determine the enhanced longest subsequence which is the longest common subsequence for the received superscale data sequences. Dividing the superscale data sequences into segments allows for parallel processing of each segment pair, which results in a faster completion time than prior art methods for determining longest common subsequences.

Abstract: A static multi-entry point function with more than one entry point is provided. The function allows callers to enter the function at different entry points using an offset. Each entry point of the function is associated with a different offset, and includes instructions that identify data that is associated with the entry point. Each entry point further includes an instruction that jumps to a common prologue of the function. The common prologue loads the identified data into local variables. The function also includes a functional component that performs different actions depending on the data in the local variables. The function includes a default entry point that is used when the function is called without any offset, so that the function appears to behave like a normal function to scanners.

Abstract: Computer programs are dynamically instrumented for telemetry data collection. An instrumentation manifest is received that includes metadata specifying one or more target functions that exist within a target computer program which is installed on a target computing device. The metadata also specifies for each of the target functions the types of telemetry data to be collected from the target function. The manifest is utilized to insert code into each of the target functions whenever the target function is executed, where this inserted code collects the specified types of telemetry data from each of the target functions. The collected telemetry data is stored.

Abstract: Automatic detection of software program regression points enables developers to more quickly and accurately diagnose and solve issues in changes to software. Traces of instructions are collected from before and after a change to a program or settings thereto on a computing device and are compared to identify differences between the two traces. Areas of differences are ranked and returned to identify the point(s) of regression in the traces to alert a user of programs of behaviors to avoid and/or a developer a point to focus efforts on to patch the responsible program or update other programs around the responsible application.