International Business Machines Corporation

Aharon Kupershtok

Yaakov Yaari

Moshe Klausner

Yousef Shajrawi

Onn Menahem Shehory

Rachel Tzoref

Daniel Citron

Andre Heiper

A method, system and product for predicting an outcome of a program based on input. The method comprising: obtaining an input to be used by a program prior to executing the program; predicting by, a machine learning module, a predicted outcome of the program based on the input; wherein the predicted outcome is selected from the group consisting of: a pass outcome and a fail outcome, wherein the pass outcome is the program executing without failing when using the input, and wherein the fail outcome is the program failing when using the input.

Predicting outcome based on input

A method, system and product for automatic systems configuration. The method comprising: obtaining utilization of workloads of processing units, wherein at least a portion of the workloads include transferring of data to other processing units; and automatically determining, by a processor, a system configuration, wherein the system configuration comprises assigning to plurality of physical locations the processing units, wherein in at least one physical location the system configuration assigns two or more processing units, wherein the system configuration indicates throughput requirement between the plurality of physical locations.

Optimum design method for configuration of servers in a data center environment

Computer-implemented method, computerized apparatus and a computer program product for test selection. The computer-implemented method comprising: obtaining a test suite comprising a plurality of tests for a Software Under Test (SUT); and selecting a subset of the test suite, wherein the subset provides coverage of the SUT that correlates to a coverage by a workload of the SUT, wherein the workload defines a set of input events to the SUT thereby defining portions of the SUT that are to be invoked during execution.

Test selection

Detecting optimization opportunities is enabled by utilizing a trace of a target concurrent computer program and determining a relation between data objects accessed during the tracked execution. The relation may be stored in a Temporal Relation Graph (TRG), in an extended-TRG or another data structure. The relation may be affected by temporally-adjacent accesses to data objects. The relation may further be affected by accesses to data objects performed during critical sections of the target program.

Performance optimization based on data accesses during critical sections

Systems and methods for cache optimization are provided. The method comprises tracing objects instantiated during execution of a program code under test according to type of access by one or more threads running in parallel, wherein said tracing provides information about order in which different instances of one or more objects are accessed by said one or more threads and whether the type of access is a read operation or a write operation; and utilizing tracing information to build a temporal relationship graph (TRG) for the accessed objects, wherein the objects are represented by nodes in the TRG and at least two types of edges for connecting the nodes are defined.

Growing community of inventors

Ramat Gan, Israel

Aharon Kupershtok