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Due to the rapid increase of enterprise scale, the traditional financing methods can no longer meet the needs of enterprises. As a financing method with both equity and debt, the flexibility of convertible bonds is favored by enterprises. Especially in 2017, China's supervision on the financing method of private placement of shares became stricter, and some companies chose convertible bonds for financing. This paper takes the ownership structure as the starting point, takes the listed companies in Shanghai and Shenzhen as the research object, and uses the regression analysis method to test the relationship between convertible bond financing, ownership structure and enterprise performance. It is found that convertible bond financing will reduce the performance level of enterprises, and the ownership concentration strengthens the negative relationship.

The rapid development of economy requires more and more energy. With the continuous enhancement of the awareness of environment and sustainable development, new energy has the advantages of low pollution and wide development prospects, and has been deeply studied by various countries. At the same time, in order to regulate the development of the new energy automobile industry, China revised the accounting standards for Business Enterprises No. 14 - revenue in 2017 to standardize the relevant measurement methods, which has a certain impact on the new energy automobile industry. Taking the development status and trend of China's new energy automobile industry in recent years as the research background, this paper uses the case analysis method and selects BYD, a new energy automobile company, as the research sample to systematically analyze the impact of the revision of the income accounting standards on the accounting, strategy and risk management of BYD, and puts forward targeted suggestions and measures for the effective implementation of the income accounting standards in the new energy automobile industry.

Noise in software patches impacts their understanding, analysis, and use for tasks such as change prediction. Although several approaches have been developed to identify noise in patches, this issue has persisted. An analysis of a dataset of security patches for the Tomcat web server, which we further expanded with security patches from five additional systems, uncovered several kinds of previously unreported noise which we call nonessential casualty changes. These are changes that themselves do not alter the logic of the program but are necessitated by other changes made in the patch. In this paper, we provide a comprehensive taxonomy of casualty changes. We then develop CasCADe, an automated technique for automatically identifying casualty changes. We evaluate CasCADe with several publicly available datasets of patches and tools that focus on them. Our results show that CasCADe is highly accurate, that the kinds of noise it identifies occur relatively commonly in patches, and that removing this noise improves upon the evaluation results of a previously published change-based approach.

Strategic management is a shortto long-term development plan concerning the goals of an enterprise. Formulating appropriate strategic management is of great and far-reaching significance for the current development and sustainable development of the enterprise There is no doubt that the formulation of strategic management is very important. In the new era, under the condition of rapid economic development, the way enterprises formulate strategies and the development of strategic formulation have very important research value. This paper thus examines the characteristics of strategic management and the process of strategic management, the current situation of the development of entrepreneurial enterprises in the new era, and then uses quantitative analysis to analyse the impact of the Midea group on the strategic management of enterprises, puts forward several issues and decisive factors that should be considered for strategic management, and puts forward important implications for the strategic management of entrepreneurial enterprises.

Network latency in mobile software has a large impact on user experience, with potentially severe economic consequences. Prefetching and caching have been shown effective in reducing the latencies in browser-based systems. However, those techniques cannot be directly applied to the emerging domain of mobile apps because of the differences in network interactions. Moreover, there is a lack of research on prefetching and caching techniques that may be suitable for the mobile app domain, and it is not clear whether such techniques can be effective or whether they are even feasible. This paper takes the first step toward answering these questions by conducting a comprehensive study to understand the characteristics of HTTP requests in over 1000 popular Android apps. Our work focuses on the prefetchability of requests using static program analysis techniques and cacheability of resulting responses. We find that there is a substantial opportunity to leverage prefetching and caching in mobile apps, but that suitable techniques must take into account the nature of apps' network interactions and idiosyncrasies such as untrustworthy HTTP header information. Our observations provide guidelines for developers to utilize prefetching and caching schemes in app development, and motivate future research in this area., Comment: ASE 2018

Reducing network latency in mobile applications is an effective way of improving the mobile user experience and has tangible economic benefits. This paper presents PALOMA, a novel client-centric technique for reducing the network latency by prefetching HTTP requests in Android apps. Our work leverages string analysis and callback control-flow analysis to automatically instrument apps using PALOMA's rigorous formulation of scenarios that address "what" and "when" to prefetch. PALOMA has been shown to incur significant runtime savings (several hundred milliseconds per prefetchable HTTP request), both when applied on a reusable evaluation benchmark we have developed and on real applications, Comment: ICSE 2018

Android's communication model has a major security weakness: malicious apps can manipulate other apps into performing unintended operations and can steal end-user data, while appearing ordinary and harmless. This paper presents SEALANT, a technique that combines static analysis of app code, which infers vulnerable communication channels, with runtime monitoring of inter-app communication through those channels, which helps to prevent attacks. SEALANT's extensive evaluation demonstrates that (1) it detects and blocks inter-app attacks with high accuracy in a corpus of over 1,100 real-world apps, (2) it suffers from fewer false alarms than existing techniques in several representative scenarios, (3) its performance overhead is negligible, and (4) end-users do not find it challenging to adopt.

Design problems affect every software system. Diverse software systems have been discontinued or reengineered due to design problems. As design documentation is often informal or nonexistent, design problems need to be located in the source code. The main difficulty to identify a design problem in the implementation stems from the fact that such problem is often scattered through several program elements. Previous work assumed that code anomalies -- popularly known as code smells -- may provide sufficient hints about the location of a design problem. However, each code anomaly alone may represent only a partial embodiment of a design problem. In this paper, we hypothesize that code anomalies tend to ``flock together'' to realize a design problem. We analyze to what extent groups of inter-related code anomalies, named agglomerations, suffice to locate design problems. We analyze more than 2200 agglomerations found in seven software systems of different sizes and from different domains. Our analysis indicates that certain forms of agglomerations are consistent indicators of both congenital and evolutionary design problems, with accuracy often higher than 80%.

The flourish of services on the Internet results in the flourish of personal service data. The volume of the data produced by various services around a person is fairly large. However, in the service-centric paradigm, these data are distributed in the clouds of different service providers and these clouds are mutually isolated, but there lacks of a global view of the service data related to a specific person, limiting the collaboration between various services. To overcome this deficiency, we propose a user-centric paradigm for personal data management, called "Personal Data Cloud" (PDC), which is a SaaS application storing a user's data from different services in a centralized way. A key issue in PDC is how to collect personal data from distributed services and store them in a unified form. In this paper we present three ways of collecting personal data, namely open API based, web crawler based, and manual importation based ways. To deal with the semantics unification among the collected data, we adopt Linked Data and ontology techniques for semantic annotation. Some open APIs are designed for the PDC to facilitate the access and usage of the personal data from a portal or apps on mobile terminals.

On the basis of the characteristics of Ad Hoc Networks, from the perspective of the authentication and key agreement between nodes, this paper puts forward Ad Hoc Networks key cluster management solution based on the hash function. By introducing a clustering technology, this solution reduces the amount of computation and communication between nodes, improves the efficiency of authentication, and achieves effective communication between nodes authentication, digital signatures and other functions.

Based on the principle of AHP, this paper establishes B2C e-commerce site evaluation system,whose Perspective start from consumer. This paper regards the quality of B2C e-commerce site as overall goal, and set product, price, service, Credibility as first indicators, at the same time, which establishes 15 secondary indicators. Finally, this paper utilizes AHP to establish the quantitative index system.

UI testing is tedious and time-consuming due to the manual effort required. Recent research has explored opportunities for reusing existing UI tests from an app to automatically generate new tests for other apps. However, the evaluation of such techniques currently remains manual, unscalable, and unreproducible, which can waste effort and impede progress in this emerging area. We introduce FrUITeR, a framework that automatically evaluates UI test reuse in a reproducible way. We apply FrUITeR to existing test-reuse techniques on a uniform benchmark we established, resulting in 11,917 test reuse cases from 20 apps. We report several key findings aimed at improving UI test reuse that are missed by existing work., ESEC/FSE 2020