Test-based automatic program repair has attracted a lot of attention in recent years. However, the test suites in practice are often too weak to guarantee correctness and existing approaches often generate a large number of incorrect patches.To reduce the number of incorrect patches generated, we propose a novel approach that heuristically determines the correctness of the generated patches. The core idea is to exploit the behavior similarity of test case executions. The passing tests on original and patched programs are likely to behave similarly while the failing tests on original and patched programs are likely to behave differently. Also, if two tests exhibit similar runtime behavior, the two tests are likely to have the same test results. Based on these observations, we generate new test inputs to enhance the test suites and use their behavior similarity to determine patch correctness.Our approach is evaluated on a dataset consisting of 139 patches generated from existing program repair systems including jGen-Prog, Nopol, jKali, ACS and HDRepair. Our approach successfully prevented 56.3% of the incorrect patches to be generated, without blocking any correct patches.

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The synthesis of new functionally diverse alkenyl-derived Cr-MIL-101s (MIL=material of Institute Lavoisier) was realized by a novel and convenient postsynthetic modification (PSM) protocol by means of the carbon-carbon bond-forming Mizoroki-Heck reaction. The new PSM protocol demonstrates a broad scope of substrates with excellent tolerance of functionality under mild reaction conditions. Moreover, a new metal-organic framework (MOF) that bears both alkenyl and thiol side chains prepared by means of the tandem PSM method has shown excellent adsorbent ability in removing mercury ions from water.

Though considerable effort has been devoted to exploiting generation-side and demand-side operational flexibility in order to cope with uncertain renewable generations, grid-side operational flexibility has not been fully investigated. In this review, we define grid-side flexibility as the ability of a power network to deploy its flexibility resources to cope with the changes of power system state, particularly due to variation of renewable generation. Starting with a survey on the metrics of operational flexibility, we explain the definition from both physical and mathematical point of views. Then conceptual examples are presented to demonstrate the impacts of grid-side flexibility graphically, providing a geometric interpretation for a better understanding of the concepts. Afterwards the formulations and solution approaches in terms of grid-side flexibility in power system operation and planning are reviewed, based on which future research directions and challenges are outlined.

The conservativeness of unit commitment models-based robust optimization (RO) depends on the modeling of uncertainty sets. This paper proposes a new two-stage robust security-constrained unit commitment (SCUC) model, which aims at minimizing the operating cost in the base scenario while guaranteeing that the robust solution can be adaptively and safely adjusted according to the uncertainties of wind power, load, and N-k fault. This new model has the following characteristics: 1) the temporal correlation of continuous uncertainties (i.e., wind power output and load) are studied and a time-correlation constraint is established to reduce the conservativeness of uncertainty sets in the proposed robust SCUC model; 2) the discrete characteristics of the uncertain set is used to describe the uncertainty of discrete N-k fault; 3) the outage probability of units with different capacity is also considered with a proposed probability criterion; and 4) the constraint approximation is simplified to a linear constraint that can be applied to RO. The proposed model is solved by the Benders decomposition and dual theory. The simulation results on modified IEEE-RTS-96 system show that the proposed method can effectively reduce the conservativeness of uncertain sets and ensure the economic and security of the optimization results.

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This paper focuses on deriving optimal refill rules for a multi-purpose reservoir, and aims to maximize utilization benefits under the condition of flood control safety. The entire flood season is divided into multiple sub-seasons (i.e. preflood season, main-flood season and post-flood season). By advancing the start of the refill period to the beginning of the post-flood season, seasonal design flows during the new refill period are estimated. A multi-objective refill operation model is proposed by combining flood control and conservation together. The simulationoptimization-test framework and hybrid multi-objective genetic algorithms are developed and used to optimize the rule curves. China's Three Gorges Reservoir is selected as a case study and the application results show that the proposed model can increase the hydropower generation by 17.4%, decrease spilled water by 43.9%, and improve the refill probability greatly without decreasing the flood control standard and navigation probability during the refill period.

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