Floating point computation is by nature inexact, and numerical libraries that intensively involve floating-point computations may encounter high floating-point errors. Due to the wide use of numerical libraries, it is highly desired to reduce high floating-point errors in them. Using higher precision will degrade performance and may also introduce extra errors for certain precision-specific operations in numerical libraries. Using mathematical rewriting that mostly focuses on rearranging floating-point expressions or taking Taylor expansions may not fit for reducing high floating-point errors evoked by ill-conditioned problems that are in the nature of the mathematical feature of many numerical programs in numerical libraries. In this paper, we propose a novel approach for efficient automated repair of high floating-point errors in numerical libraries. Our main idea is to make use of the mathematical feature of a numerical program for detecting and reducing high floating-point errors. The key components include a detecting method based on two algorithms for detecting high floating-point errors and a repair method for deriving an approximation of a mathematical function to generate patch to satisfy a given repair criterion. We implement our approach by constructing a new tool called AutoRNP. Our experiments are conducted on 20 numerical programs in GNU Scientific Library (GSL). Experimental results show that our approach can efficiently repair (with 100% accuracy over all randomly sampled points) high floating-point errors for 19 of the 20 numerical programs. CCS Concepts: • Mathematics of computing → Mathematical software; Computations in finite fields; • Theory of computation → Numeric approximation algorithms; • Software and its engineering → Search-based software engineering;

Background: Over the years, Automated Program Repair (APR) has attracted much attention from both academia and industry since it can reduce the costs in fixing bugs. However, how to assess the patch correctness remains to be an open challenge. Two widely adopted ways to approach this challenge, including manually checking and validating using automated generated tests, are biased (i.e., suffering from subjectivity and low precision respectively). Aim: To address this concern, we propose to conduct an empirical study towards understanding the correct patches that are generated by existing state-of-the-art APR techniques, aiming at providing guidelines for future assessment of patches. Method: To this end, we first present a Literature Review (LR) on the reported correct patches generated by recent techniques on the Defects4J benchmark and collect 177 correct patches after a process of sanity check. We investigate how these machine-generated correct patches achieve semantic equivalence, but syntactic difference compared with developerprovided ones, how these patches distribute in different projects and APR techniques, and how the characteristics of a bug affect the patches generated for it. Results: Our main findings include 1) we do not need to fix bugs exactly like how developers do since we observe that 25.4% (45/177) of the correct patches generated by APR techniques are syntactically different from developerprovided ones; 2) the distribution of machine-generated correct patches diverges for the aspects of Defects4J projects and APR techniques; and 3) APR techniques tend to generate patches that are different from those by developers for bugs with large patch sizes. Conclusion: Our study not only verifies the conclusions from previous studies but also highlights implications for future study towards assessing patch correctness. Keywords-Automated Program Repair; Defects4J; patch correctness assessment.RQ1 How do machine-generated correct patches differ from developer-provided ones?RQ2 How do different types of patches distribute? RQ3 Do APR tools tend to generate correct patches but different from the developer-provided ones for bugs with certain characteristics?A patch is generated based on the buggy location identified by fault localization techniques (i.e., denoted as edit point in this study) with certain code modifications. Based on this, the differences between patches can be distinguished in terms of two aspects, edits points and code modifications. To answer RQ1, we compare the collected patches with developerprovided ones and classify them into four types based on the aforementioned two aspects. We further investigate how the patches that are syntactically different from developer-provided ones achieve semantic equivalence. In RQ2, we investigate the distribution of patches from two aspects (i.e., different De-fects4J projects and APR techniques) and observe that fault localization is critical for generating correct patches for bugs in three projects of Defects4J. In RQ3, we aim at investigating whethe...

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PurposePublic participation is essential for mitigating local resistance faced by the environmentally stigmatized facilities. The purpose of this study is to investigate public participation intention in the decision-making of waste incineration power (WIP) projects by examining the role of perceived corporate social responsibility (PCSR) and public knowledge (PK) based on the theory of planned behavior (TPB).Design/methodology/approachA theoretical model correlating PCSR with public participation intention was developed by using the constructs of TPB as the mediators and PK as the moderator. Drawing on structural equation modeling (SEM), the data collected from 485 local residents of the WIP projects in Jiangsu, China were analyzed to test the model.FindingsCompanies' CSR practice went through public attitude, subjective norm and personal norm as mediating steps towards promoting participation intention. PK positively moderated the indirect relationships between PCSR and participation intention. Moreover, attitude, subjective norm and personal norm were found to have a positive effect on participation intention.Originality/valueThis study advances the understanding of public participation intention and enriches the literature relating to CSR and TPB involved in infrastructure development. In order to improve public participation intention, companies should take strategic social responsibility actions and present the benefits and moral values of the activities to the public, and as well make effort to diffuse WIP-related knowledge through interactive activities with the public. Authorities should establish social and personal value systems that praise public participation and improve their expectations of participation outcomes.