Program execution traces provide the most intimate details of a program's dynamic behavior. They can be used for program optimization, failure diagnosis, collecting software metrics like coverage, test prioritization, etc. Two major obstacles to exploiting the full potential of information they provide are: (i) performance overhead while collecting traces, and (ii) significant size of traces even for short execution scenarios. Reducing information output in an execution trace can reduce both performance overhead and the size of traces. However, the applicability of such traces is limited to a particular task. We present a runtime framework with a goal of collecting a complete, machine-and task-independent, user-mode trace of a program's execution that can be re-simulated deterministically with full fidelity down to the instruction level. The framework has reasonable runtime overhead and by using a novel compression scheme, we significantly reduce the size of traces. Our framework enables building a wide variety of tools for understanding program behavior. As examples of the applicability of our framework, we present a program analysis and a data locality profiling tool. Our program analysis tool is a time travel debugger that enables a developer to debug in both forward and backward direction over an execution trace with nearly all information available as in a regular debugging session. Our profiling tool has been used to improve data locality and reduce the dynamic working sets of real world applications.

No abstract

No abstract

In the knowledge economy era, the competitive advantage of an enterprise is established on intangible resources and capability. Trust allows individuals acquiring and exchanging intellectual capitals, especially in ambiguous and uncertain situations, and knowledge exchange relies on the existence of trust. Different from past other industries, hi-tech industry stresses on intangible assets, endeavors to transform real assets into valuable knowledge, and manage and create "intellectual property" based on value for specific operating performance of an enterprise. This study therefore discusses the effect of organizational trust on organizational learning and creativity in hi-tech industry. Aiming at Mawei Hi-Tech Park in Fujian Province, 500 supervisors and employees are distributed the questionnaire and 373 valid copies are retrieved, with the retrieval rate 75%. The research results show 1. positive and significant effects of organizational trust on organizational learning, 2. positive and remarkable effects of organizational learning on creativity, and 3. positive effects of organizational trust on creativity. It is expected to propose suggestions, based on the results, for the promotion of intellectual capitals in hi-tech industry.