Software testing plays a crucial role in software engineering, ensuring the reliability and correctness of evolving systems. Well-maintained test suites are essential for ensuring software quality. However, in modern development cycles that emphasize rapid feature iteration, the co-evolution of test suites often lags behind, leading to more appearance of obsolete tests. To this end, automated approaches for updating obsolete test code have been proposed, and recent approaches have achieved the state-of-the-art performance with the support of large language models (LLMs). This paper presents COMMITUP, a new approach that leverages LLMs to effectively automate method-level obsolete test code updates. COMMITUP mimics how humans solve the problem, first comprehending the code modifications, searching for similar examples to imitate, and finally performing the update. We evaluate COMMITUP on a curated dataset from real-world Java projects. The results demonstrate the superior performance of COMMITUP, achieving 96.4%, 94.4%, 93.1% success rates for generating compilable, runtime failure-free, and full coverage updates, respectively. We believe our study can provide new insight into LLM-based test code update. The dataset and code are available at https://github.com/SoftWiser-group/CommitUp.

Doppler radar life sensing has shown promise in medical and security applications. The current paper considers the problem of determining the number of persons in a given area (e.g., a room) using the Doppler shift due to heartbeat. The signal is weak and time-varying, and therefore poses a complicated signal processing problem. We develop a generalized likelihood ratio test (GLRT) based on a model of the heartbeat, and show that this can be used to distinguish between the presence of 2, 1, or 0 subjects, even with a single antenna. We further extend this to N antennas. The results show that one can expect to detect up to 2N-1 subjects using this technique

We consider the minimum energy unicast problem in ad-hoc wireless networks. A source node wants to transmit a sequence of messages to a single destination node. Other nodes in the network may operate as relay nodes. The problem is to do this with the minimum overall power consumption in the network. In this paper we investigate the power saving that can be achieved by using advanced relay-channel signaling rather than traditional multi-hop routing. Under the assumptions that carrier level synchronization is not available and every intermediate node uses a decode-forward scheme, we show that any optimal relaying structure can be converted to a sequential path, for which we find a simple optimal power-allocation policy. Finding an optimal sequential path is still complex, and we therefore present two polynomial heuristic algorithms to find good cooperative routes. Our simulation results show that they can achieve average power savings of up to 3 dB for a network size of 60 nodes in low attenuation regimes. For high attenuation regimes, cooperative routing exhibits limited gain and traditional multi-hop operation is a reasonable choice.

We consider practical two-way communication schemes with blind channel estimation in TDD (time-division duplex) MISO (multi-input single-output) and MIMO (multi-input multi-output) systems. In the MISO system, we show that blind channel estimation only needs to be done at a transceiver equipped with multiple antennas and this estimated channel can be efficiently utilized for both uplink and downlink communication. In the MIMO system, we propose a two-stage communication scheme which begins with uplink transmission using differential space-time block codes and follows with two-way beamforming with blind channel estimation. We demonstrate, through simulations, that the novel schemes possess very good performance and compare them with training-based schemes.

This paper presents the study of transmit power adaption and capacity-approaching coding/decoding in multiple-input-multiple-output (MIMO) Rayleigh fading channels under the assumption that perfect channel state information (CSI) is known at both the transmitter and the receiver. We propose three different simple, but powerful, methods for transforming the MIMO fading channel into a set of additive white noise Gaussian (AWGN) channels. We show that the channel capacity can be closely approached by using only a small number of different codes designed for the Gaussian channel.