International Business Machines Corporation

Satish Chandra Gupta

Kumar Rangarajan

Ishai Rabinovitz

Ziv Glazberg

Sandeep Kohli

Janees Elamkulam

Embodiments of the present invention provide a computing system and method to profile a program for finding potential optimization in heap usage by reducing lag and drag in lifetimes of heap memory blocks. The process consists of three steps. First, an instrumentation engine analyzes a given program and inserts additional code at interesting locations to collect needed information. Second, when the instrumented program is executed on a set of test cases, runtime data is collected. Third, since this data is large for a complex and long running program, data is processed to present it to a user in useful ways so that a programmer improves the heap utilization in the program.

Optimizing heap memory usage

Dangling pointers and memory leak locations within software are detected. As the software allocates and deallocates memory, lists of pointers referencing the memory, and pointer status, are maintained. As the software writes new addresses within pointers and reads addresses referenced by the pointers, the pointer lists are maintained to determine whether the pointers are dangling and to detect memory leak locations. A balanced binary tree having a number of nodes can be maintained. The nodes represent heap or stack records. Each heap record corresponds to heap memory that has been allocated and has a list of pointers referencing the heap memory. Each stack record corresponds to a stack within which a stack frame is allocated each time a function is entered. The stack record has frame records corresponding to the stack frames. Each frame record has a list of pointers referencing the corresponding stack frame.

Detecting dangling pointers and memory leaks within software

This disclosure provides a computing system and method to profile a program for finding potential optimization in heap usage by reducing lag and drag in lifetimes of heap memory blocks. The process consists of three steps. First, an instrumentation engine analyzes a given program, and inserts additional code at interesting locations to collect needed information. Second, when the instrumented program is executed on a set of test cases, runtime data is collected. Third, since this data could be relatively large for a complex and long running program, data is processed to present it to a user in useful ways so that the programmer can improve the heap utilization in the program.

A method and system are disclosed for modeling non-deterministic queues for efficient model checking. In this method and system, a multitude of messages are held in a plurality of queues, and these messages having n priorities. The method comprises the steps of providing (n+1) queues, including a first queue, and n priority queues; passing said messages from a source to the first queue; passing each of said messages from the first queue to one of said n priority queues based on the priority of the message; and passing each of said messages from the n priority queues to a destination based on the priority of the message. One or more non-deterministic waits are introduced into one or more of the passing steps to simplify passing the messages into or out of the n priority queues.

Modeling non-deterministic priority queues for efficient model checking

A method and system to identifying the use of dangling pointers in software instrumentation irrespective of the location of the pointer in the memory. The main memory is preferably segmented into three parts defined as a first memory, a version segment and a pointer version segment. By use of the version segment and pointer version stored in the pointer version segment, checksum are made on a pointer version with a version on dereferencing a pointer in the first memory to identify references to a dangling pointer on negative determination. Identified dangling pointer may be reported to the end user.

Growing community of inventors

Kerala, India

Satish Chandra Gupta