scholarly journals An Automated Refactoring Approach to Improve IoT Software Quality

2020 ◽  
Vol 10 (1) ◽  
pp. 413
Author(s):  
Yang Zhang ◽  
Shuai Shao ◽  
Minghan Ji ◽  
Jing Qiu ◽  
Zhihong Tian ◽  
...  
Keyword(s):  
Program Analysis ◽  
Pattern Analysis ◽  
Alias Analysis ◽  
Effect Analysis ◽  
Analysis Techniques ◽  
Fine Grained ◽  
Real World Applications ◽  
Iot Devices ◽  
Time And Energy ◽  
Good Support

Internet of Things (IoT) software should provide good support for IoT devices as IoT devices are growing in quantity and complexity. Communication between IoT devices is largely realized in a concurrent way. How to ensure the correctness of concurrent access becomes a big challenge to IoT software development. This paper proposes a general refactoring framework for fine-grained read–write locking and implements an automatic refactoring tool to help developers convert built-in monitors into fine-grained ReentrantReadWriteLocks. Several program analysis techniques, such as visitor pattern analysis, alias analysis, and side-effect analysis, are used to assist with refactoring. Our tool is tested by several real-world applications including HSQLDB, Cassandra, JGroups, Freedomotic, and MINA. A total of 1072 built-in monitors are refactored into ReentrantReadWriteLocks. The experiments revealed that our tool can help developers with refactoring for ReentrantReadWriteLocks and save their time and energy.

scholarly journals Incremental and Modular Context-sensitive Analysis

2021 ◽  
pp. 1-48
Author(s):  
ISABEL GARCIA-CONTRERAS ◽  
JOSÉ F. MORALES ◽  
MANUEL V. HERMENEGILDO
Keyword(s):  
Global Analysis ◽  
Memory Consumption ◽  
Sensitive Analysis ◽  
Analysis Techniques ◽  
Context Sensitive ◽  
Fine Grained ◽  
Fine Grain ◽  
Modular Analysis ◽  
Modular Algorithm ◽  
Modular Structures

Abstract Context-sensitive global analysis of large code bases can be expensive, which can make its use impractical during software development. However, there are many situations in which modifications are small and isolated within a few components, and it is desirable to reuse as much as possible previous analysis results. This has been achieved to date through incremental global analysis fixpoint algorithms that achieve cost reductions at fine levels of granularity, such as changes in program lines. However, these fine-grained techniques are neither directly applicable to modular programs nor are they designed to take advantage of modular structures. This paper describes, implements, and evaluates an algorithm that performs efficient context-sensitive analysis incrementally on modular partitions of programs. The experimental results show that the proposed modular algorithm shows significant improvements, in both time and memory consumption, when compared to existing non-modular, fine-grain incremental analysis techniques. Furthermore, thanks to the proposed intermodular propagation of analysis information, our algorithm also outperforms traditional modular analysis even when analyzing from scratch.

Semi-Supervised Aspect-Based Sentiment Analysis for Case-Related Microblog Reviews Using Case Knowledge Graph Embedding

2021 ◽  
pp. 2050012
Author(s):  
Peilian Zhao ◽  
Cunli Mao ◽  
Zhengtao Yu
Keyword(s):  
Sentiment Analysis ◽  
Domain Knowledge ◽  
Opinion Mining ◽  
Data Augmentation ◽  
Training Data ◽  
Knowledge Graph ◽  
Fine Grained ◽  
Learning Framework ◽  
Proposed Model ◽  
Real World Applications

Aspect-Based Sentiment Analysis (ABSA), a fine-grained task of opinion mining, which aims to extract sentiment of specific target from text, is an important task in many real-world applications, especially in the legal field. Therefore, in this paper, we study the problem of limitation of labeled training data required and ignorance of in-domain knowledge representation for End-to-End Aspect-Based Sentiment Analysis (E2E-ABSA) in legal field. We proposed a new method under deep learning framework, named Semi-ETEKGs, which applied E2E framework using knowledge graph (KG) embedding in legal field after data augmentation (DA). Specifically, we pre-trained the BERT embedding and in-domain KG embedding for unlabeled data and labeled data with case elements after DA, and then we put two embeddings into the E2E framework to classify the polarity of target-entity. Finally, we built a case-related dataset based on a popular benchmark for ABSA to prove the efficiency of Semi-ETEKGs, and experiments on case-related dataset from microblog comments show that our proposed model outperforms the other compared methods significantly.

Layered Region Based Flow-Sensitive Demand-Driven Alias Analysis

2014 ◽  
Vol 577 ◽  
pp. 917-920
Author(s):  
Long Pang ◽  
Xiao Hong Su ◽  
Pei Jun Ma ◽  
Ling Ling Zhao
Keyword(s):  
Program Analysis ◽  
Control Flow ◽  
Alias Analysis ◽  
Reachability Problem ◽  
Analysis Algorithm ◽  
Context Free Language ◽  
Context Free ◽  
Free Language ◽  
Demand Driven Analysis

The pointer alias is indispensable for program analysis. Comparing to point-to set, it’s more efficient to formulate the alias as the context free language (CFL) reachability problem. However, the precision is limited to flow-insensitivity. To solve this problem, we propose a flow sensitive, demand-driven analysis algorithm for answering may-alias queries. First the partial single static assignment is used to discriminate the address-taken pointers. Then the order of control flow is encoded in the level linearization code to ease comparison. Finally, the query of alias in demand driven is converted into the search of CFL reachability with feasible flows. The experiments demonstrate the effectiveness of the proposed approach.

An Overview of Methods for Automatic Reassembly of Fragmented Objects

2011 ◽  
pp. 263-288
Author(s):  
Dimitris Arabadjis ◽  
Michael Exarhos ◽  
Fotios Giannopoulos ◽  
Solomon Zannos ◽  
Panayiotis Rousopoulos ◽  
...  
Keyword(s):  
Signal Processing ◽  
Pattern Analysis ◽  
Complete System ◽  
General Purpose ◽  
Wall Paintings ◽  
Analysis Techniques ◽  
Application Problem ◽  
Archaeological Objects

In this chapter the authors outline some research works characteristic for the application of Signal Processing and Pattern Analysis techniques to the automatic reconstruction / reassembly of fragmented archaeological objects. The studies described in the chapter cover in their application cases a variety of archaeological objects, ranging from documents and wall-paintings to pots and sculptures. Moreover there are distinct approaches in the treatment of these application cases, with some works focusing on the development of a reconstruction methodology of general purpose, while others aim to develop a complete system to treat a specific application problem. The methodologies developed in these studies are outlined in the chapter so as to retain the basic technical elements of each approach that compile the proposed reconstruction algorithmic scheme.

scholarly journals BaDS: Blockchain-Based Architecture for Data Sharing with ABS and CP-ABE in IoT

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Yunru Zhang ◽  
Debiao He ◽  
Kim-Kwang Raymond Choo
Keyword(s):  
Data Sharing ◽  
Consensus Algorithm ◽  
Byzantine Fault Tolerance ◽  
Tolerance Mechanism ◽  
User Privacy ◽  
Fine Grained ◽  
User Data ◽  
Iot Devices ◽  
And Storage ◽  
Inform Decision Making

Internet of Things (IoT) and cloud computing are increasingly integrated, in the sense that data collected from IoT devices (generally with limited computational and storage resources) are being sent to the cloud for processing, etc., in order to inform decision making and facilitate other operational and business activities. However, the cloud may not be a fully trusted entity, like leaking user data or compromising user privacy. Thus, we propose a privacy-preserving and user-controlled data sharing architecture with fine-grained access control, based on the blockchain model and attribute-based cryptosystem. Also, the consensus algorithm in our system is the Byzantine fault tolerance mechanism, rather than Proof of Work.

scholarly journals An SDN-Based Connectivity Control System for Wi-Fi Devices

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Duc-Thang Nguyen ◽  
Taehong Kim
Keyword(s):  
Control System ◽  
Service Providers ◽  
Connection Management ◽  
Fine Grained ◽  
Connectivity Information ◽  
Wireless Environment ◽  
Remote Services ◽  
Iot Devices ◽  
And Performance ◽  
High Level

In recent years, the prevalence of Wi-Fi-enabled devices such as smartphones, smart appliances, and various sensors has increased. As most IoT devices lack a display or a keypad owing to their tiny size, it is difficult to set connectivity information such as service set identifier (SSID) and password without any help from external devices such as smartphones. Moreover, it is much more complex to apply advanced connectivity options such as SSID hiding, MAC ID filtering, and Wi-Fi Protected Access (WPA) to these devices. Thus, we need a new Wi-Fi network management system which not only facilitates client access operations but also provides a high-level authentication procedure. In this paper, we introduce a remote connectivity control system for Wi-Fi devices based on software-defined networking (SDN) in a wireless environment. The main contributions of the proposed system are twofold: (i) it enables network owner/administrator to manage and approve connection request from Wi-Fi devices through remote services, which is essential for easy connection management across diverse IoT devices; (ii) it also allows fine-grained access control at the device level through remote control. We describe the architecture of SDN-based remote connectivity control of Wi-Fi devices. While verifying the feasibility and performance of the proposed system, we discuss how the proposed system can benefit both service providers and users.

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