Software testing has been the major approach to software quality assurance for decades, but it typically involves intensive manual efforts. To reduce manual efforts, researchers have proposed numerous approaches to automate test-case generation, which is one of the most time-consuming tasks in software testing. One most recent achievement in the area is Dynamic Symbolic Execution (DSE), and tools based on DSE, such as KLEE, have been reported to generate test suites achieving higher code coverage than manually developed test suites. However, besides the competitive code coverage, there have been few studies to compare DSE-based test suites with manually developed test suites more thoroughly on various metrics to understand the detailed differences between the two testing methodologies. In this paper, we revisit the experimental study on the KLEE tool and GNU CoreUtils programs, and compare KLEE-based test suites with manually developed test suites on various aspects. We further carried out a qualitative study to investigates the reasons behind the differences in statistical results. The results of our studies show that while KLEE-based test suites are able to generate test cases with higher code coverage, they are relatively less effective on covering hard-to-cover code and killing mutants. Furthermore, our qualitative study reveals that KLEE-based test suites have advantages in exploring error-handling code and exhausting options, but are less effective on generating valid string inputs and exploring meaningful program behaviors.

In today's industry, intuitive gesture recognition, as manifested in numerous consumer electronics devices, becomes a main issue of HMI device research. Although finger-tip touch based user interface has paved a main stream in mobile electronics, we envision touch-less HMI as a promising technology in futuristic applications with higher potential in areas where sanity or outdoor operation become of importance. In this paper, we introduce a novel HMI device for non-contact gesture input for intuitive HMI experiences. The enabling technology of the proposed device is the IPA (infrared Proximity Array) sensor by which realtime 3 dimensional depth information can be captured and realized for machine control. For the usability study, two different operating modes are adopted for hand motion inputs: one is a finger tip control mode and the other is a palm control mode. Throughput of the proposed device has been studied and compared to a traditional mouse device for usability evaluation. During the human subject test, the proposed device is found to be useful for PC mouse pointer control. The experimental results are shared in the paper as well.