174 results about "Test generator" patented technology

An apparatus and method provide non-intrusive in-service testing of audio/video synchronization testing without using traditional audio marker tones. The network includes an A/V synchronous test signal generator which injects video and audio markers into the video and audio non-intrusively and routes the two signals into a switch where they are switched into a channel for encoding and transmission via the ATM network. At the distant end the signal is decoded and routed by a switch into the A/V test generator and measurement set where the markers are detected and the A/V skew calculated, after which the audio and video are routed to the subscriber. The A/V test set signal generator includes a Video Blanking Interval (VBI) test signal generator and a white noise generator, the former injecting a marker into the video signal and the later injecting an audio marker into the audio signal. The video marker is injected into the VBI and broadband, background audio noise to measure the delay between the audio and video components of a broadcast. The marking of the audio is accomplished by gradually injecting white noise into the audio channel until the noise level is 6 dB above the noise floor of the audio receiver. As a precursor A/V sync signal, a small spectrum of the white noise is notched or removed. This signature precludes inadvertent recognition of program audio noise as the audio marker.

A test coverage tool provides output that identifies differences between the actual coverage provided by a test suite run on a program under test and the coverage criteria (e.g., the coverage criteria required by the test/development team management). The output from the test coverage tool is generated in the same language that was used to write the coverage criteria that are input to an automated test generator to create the test cases which form the test suite. As a result, the output from the coverage tool can be input back into the automated test generator to cause the generator to revise the test cases to correct the inadequacies. This allows iterative refinement of the test suite automatically, enabling automated test generation to be more effectively and efficiently used with more complex software and more complex test generation inputs.

In preferred embodiments, test coverage analysis results of several different test suites, some manually generated and others automatically generated, are used to produce a streamlined automatically-generated test suite and/or to add missing elements to an automatically generated test-suite.

A novel system, computer program product, and method are disclosed for feedback-directed automated test generation for programs, such as JavaScript, in which execution is monitored to collect information that directs the test generator towards inputs that yield increased coverage. Several instantiations of the framework are implemented, corresponding to variations on feedback-directed random testing, in a tool called Artemis.

A tool is provided for modifying the code of a multi-threaded computer program undergoing testing. The program executes in an environment that has a governing memory model. It is assumed that there is a global heap and a thread-local heap, which are synchronized from time to time. The modifications are of two types: (1) code instructions are reordered while remaining in compliance with the memory model; and (2) thread-local variables are added to functions, together with inserted heap synchronizing instructions. The modified programs are then used by a test generator to prepare test cases for execution. The modifications have the effect of changing the interleavings that occur among different threads, and increase the likelihood of exposing flaws that may become evident under different memory models.

A multi-core multi-node processor system has a plurality of multiprocessor nodes, each including a plurality of microprocessor cores. The plurality of microprocessor nodes and cores are connected and form a transactional communication network. The multi-core multi-node processor system has further one or more buffer units collecting transaction data relating to transactions sent from one core to another core. An agent is included which calculates latency data from the collected transaction data, processes the calculated latency data to gather transaction latency coverage data, and creates random test generator templates from the gathered transaction latency coverage data. The transaction latency coverage data indicates at least the latencies of the transactions detected during collection of the transaction data having a pre-determined latency, and includes, for example, four components for transaction type latency, transaction sequence latency, transaction overlap latency, and packet distance latency. Thus, random test generator templates may be created using latency coverage.

Middleware is validated using a two layered modeling strategy for the generation of test suites. A high level model of the syntax of the programming language used to program the middleware generates a series of high level abstract programs. These high level abstract programs then undergo two separate translations. First they are translated directly into actual test programs, which are expressed in the programming language of the middleware. Second, they are translated into second models of the high level abstract programs. Running the model based test generator again on the second models produces a set of suites of test cases, each test case consisting of data inputs and predicted results for one of the actual test programs. The actual test programs are run repetitively using the middleware execution engine. The results are compared with the predicted results, using a generic validation engine.

The input for a test generator is a plurality of test templates, each of which typically aims at covering a specific verification task. Test templates direct the production of distinct transactions, which are the atomic functional building blocks of the design-under-verification. Test templates directed to different hardware functions of the scenario are dynamically interleaved. In this way several transactions are combined together in complex statements in order to achieve a complex test scenario. The transactions are submitted to the test generator, which generates test cases, in which the different hardware functions of the scenario are exercised in combinations. Variation among the test cases is achieved through a large number of random decisions made during the generation process.

A scan testing technique in which test data is pipelined to scan logic within an integrated circuit. In system on a programmable chip (SOPC) designs, pipelines are easily built in the programmable logic device (PLD) logic by configuring programmable interconnects to connect registers in a pipelined manner so that test data can be pipelined to scan the logic under test. In system on a chip (SOC) designs, a smart test generator-analyzer is configured to recursively extract pipeline information from a design-so that test data can be pipelined to scan the logic under test. Generally, test data is pipelined using existing functional logic and/or scan chains. Furthermore, a failure analysis (FA) platform is described. The FA platform is operable to take as its input a failing vector as well as a pipelined scan vector and unroll the pipeline sequence to determine which vector caused the failure.

A self-checking test generator program creates a self-checking test program that can test a device under test (DUT). The self-checking test generator selects instructions for a test. Selected instructions are executed on a software DUT model to generate results that can be self-checked by other instructions such as compare and branch instructions. The software DUT model has fuzzy models and unknown models for blocks in the DUT. Fuzzy models generate expected outputs for a block of the DUT. Fuzzy models may propagate unknown data from their inputs to their outputs. Unknown models do not predict expected outputs. Instead, unknown models always output unknown (X). Over time, as more of the DUT logic is modeled, unknown models may be replaced with fuzzy models.

Improvements in functional verification of a design are achieved by providing a test template that specifies test parameters directed to a function of the design. An exemption mode of operation is associated with a portion of the template, in which constraints and variables associated with the template are revised. The template is an input to a CSP engine, which, in cooperation with a test generator engine, produces test scenarios that lie in an expanded region of the generator's usual operational space. Provision is made for independently enabling and disabling a plurality of exemption modes of operation that are associated with the same or different areas of the template.