Error trapping and metamorphic testing for spreadsheet failure detection

This study deepens the research on error trapping (ET) and metamorphic testing (MT) for detecting spreadsheet failures. It is observed that some spreadsheet developers and testers are confused between ET and MT, because the two techniques are similar to each other in some aspects. Inspired by the observation, this paper first outlines the main concepts of ET and MT using several examples for illustration. This is followed by discussing an experiment with a view to investigating and comparing the failure detection capabilities of the two techniques. The results of the experiment indicate that neither technique is sufficient in spreadsheet testing. Rather, ET and MT are complementary and they should be used together in spreadsheet testing whenever possible

Poster: Enhancing partition testing through output variation

A major test case generation approach is to divide the input domain into disjoint partitions, from which test cases can be selected. However, we observe that in some traditional approaches to partition testing, the same partition may be associated with different output scenarios. Such an observation implies that the partitioning of the input domain may not be precise enough for effective software fault detection. To solve this problem, partition testing should be fine-tuned to additionally use the information of output scenarios in test case generation, such that these test cases are more fine-grained not only with respect to the input partitions but also from the perspective of output scenarios

Computational intelligence and security: International conference, CIS 2006, Guangzhou, China, November 3-6, 2006: Revised selected papers

The International Conference on Computational Intelligence and Security was held in Guangzhou, China, in November 2006. The conference brought together leading minds in computing, programming, and security to discuss the latest developments, applications, and challenges in the field. This volume constitutes the refereed post-proceedings of the conference. The 116 papers contained in this volume were submitted to two rounds of careful review and revision. Collectively, they represent some of the most important developments and new applications in the field.The papers are organized into topical sections covering bio-inspired computing, evolutionary computation, learning systems and multi-agents, cryptography, information processing and intrusion detection, systems and security, image and signal processing, and pattern recognition

Multi-objective DSTATCOM placement based on sensitivity analysis and genetic algorithm in unbalanced mv distribution networks

As a new type of reactive compensation device, distribution static compensator (DSTATCOM) is gradually utilized to mitigate voltage drop and power losses caused by increasing loads. Considering load variations, this study proposes a multi-objective placement model based on sensitivity analysis and genetic algorithm (GA) for the sequential and optimal allocation of DSTATCOM in unbalanced MV distribution networks. Weighted sum method is adopted to reflect the preferences on conflicting placement objectives, including network losses, voltage magnitude and balance profiles, as well as economic costs. To efficiently solve the multi- objective placement problem defined above, an improved direct distribution load flow approach integrating DSTATCOM is presented, and a comprehensive loss sensitivity index is defined to reasonably select the installation site. Finally the proposed placement model and strategy are simulated and validated on an unbalanced Australian MV network with MATLAB

Federated Deep Reinforcement Learning-Based Spectrum Access Algorithm With Warranty Contract in Intelligent Transportation Systems

Cognitive radio (CR) provides an effective solution to meet the huge bandwidth requirements in intelligent transportation systems (ITS), which enables secondary users (SUs) to access the idle spectrum of the primary users (PUs). However, the high mobility of users and real-time service requirements result in the additional transmission collisions and interference, which degrades the spectrum access rate and the quality of service (QoS) of users in ITS. This paper proposes a spectrum access algorithm (Feilin) based on federated deep reinforcement learning (FDRL) to improve spectrum access rate, which maximizes the QoS reward function with considering the hybrid benefits of delay, transmission power and utility of SUs. To guarantee the utility of SUs, the warranty contract is designed for SUs to obtain compensation for data transmission failure, which promotes SUs to compete for more spectrum resources. To meet the real-time requirements and improve QoS in ITS, a spectrum access model called FDQN-W is proposed based on federated deep Q-network (DQN), which adopts the asynchronous federated weighted learning algorithm (AFWLA) to share and update the weights of DQN in multiple agents to decrease time cost and accelerate the convergence. Detailed simulation results show that, in the multiuser scenario, compared with the existing methods, the proposed algorithm Feilin increases the spectrum access success rate by 15.1%, and reduces the collision rate with SUs and the collision rate with PUs by 46.4% and 6.8%, respectively

GA-LNS Optimization for Helicopter Rescue Dispatch

Aviation emergency rescue has become one of the most effective means for natural disaster relief due to its flexible and timely characteristics. A reasonable emergency dispatch plan can guarantee the effective implementation of all the rescue measures. Most of previous studies in this area focused on the scheduling and routing but ignored the impact of the specific rescue process, for example the fuel consumption of various helicopters. In this paper, a multi-helicopter-multi-trip Aviation Rescue Routing Problem (ARRP) is analysed which covers the whole rescue process. In addition, a time-domain procedural simulation model is built which can consider different helicopters, refueling or not, various resource locations, multiple disaster sites and other operation factors. Based on that, a Genetic Algorithm (GA) hybridized Large Neighborhood Search (LNS) algorithm (GA-LNS) is proposed for optimization. In ARRP, single search algorithm may lead to the local optimum due to complexity. In contrast, the distance greedy strategy and the load ratio strategy are combined in GA-LNS which can fix the local optimum problem. More specifically, based on the helicopter-tagged-task-sequenced chromosome, the single-point crossover operator is used in GA and then, the worst removal strategy and the first/last insertion strategy are adopted in LNS. Finally, the numerical experiments are exercised to verify the effectiveness of the proposed GA-LNS algorithm which is compared with three traditional basic heuristic algorithms and a stateof-the-art memetic algorithm.</p

How can non-technical end users effectively test their spreadsheets?

Purpose – An alarming number of spreadsheet faults have been reported in the literature, indicating that effective and easy-to-apply spreadsheet testing techniques are not available for “non-technical,” end-user programmers. The purpose of this paper is to alleviate the problem by introducing a metamorphic testing (MT) technique for spreadsheets. Design/methodology/approach – The paper discussed four common challenges encountered by end-user programmers when testing a spreadsheet. The MT technique was then discussed and how it could be used to solve the common challenges was explained. An experiment involving several “real-world” spreadsheets was performed to determine the viability and effectiveness of MT. Findings – The experiment confirmed that MT is highly effective in spreadsheet fault detection, and yet MT is a general technique that can be easily used by end-user programmers to test a large variety of spreadsheet applications. Originality/value – The paper provides a detailed discussion of some common challenges of spreadsheet testing encountered by end-user programmers. To the best of the authors knowledge, the paper is the first that includes an empirical study of how effective MT is in spreadsheet fault detection from an end-user programmer’s perspective

Impacts of gas source and surfactant on gas-water coupling transmission along a long-distance drip tape in one or two line layout under aerated drip irrigation

Aerated drip irrigation (ADI) is a technique to aerate the rhizosphere by aerated water through the drip irrigation system. The dissolved oxygen (DO) in water, water flow rate and gas flow uniformity are the essential indexes for the evaluation of irrigation quality in ADI. The use of biodegradable surfactant BS1000 and the optimization of transmission modes are of great significance in the existence of microbubble and the retention of DO in water during ADI. To increase the uniformity of gas, oxygen and water and the delivery distance under ADI, transmission characteristics, i.e., gas-oxygen-water mixture produced by aerated irrigation system using Mazzei 1078 venturi air injector, were studied. The impacts of gas source and surfactant on gas-water coupling transmission along a long-distance drip tape in one or two line layout were investigated. Totally 16 combinations were tested, including 2 types of gas (air and oxygen), 2 transmission modes (one and two line transmission), and 4 levels of BS1000 concentrations (0, 1, 2 and 4 mg/L), respectively. During the experiment, parameters and uniformities of water flow rate, DO, gas void fraction (GVF), and water flow rate were observed. The DO and GVF of irrigation water along a drip tape were monitored by a dissolved oxygen meter and a vacuum device of gas void fraction measurement. Main results were given as below. Aeration treatment resulted in the slight reduce in the uniformity of water flow rate during one line transmission under ADI along a drip tape, but the DO concentration and GVF in irrigation water were significantly increased at the level of 0.05. The DO concentration in air and oxygen aerated water were increased by 160.80% and 617.05% compared with non-aerated treatment during one line transmission. However, DO levels in air and oxygen aerated water were increased by 185.26% and 643.23% compared with non-aerated treatments during two line transmission. Use of biodegradable surfactant BS1000 concentration brought an increase in GVF. Under the condition of air aerated treatment during one line transmission, the GVF at 1, 2 and 4 mg/L of BS1000 were significantly increased by 17.42%, 60.41% and 80.32% than the non-use of surfactant treatment, respectively. Similarly, under the condition of oxygen aerated treatment during one line treatment, GVF at 1, 2 and 4 mg/L of BS1000 were significantly increased by 25.00%, 55.05% and 69.27% in contrast to non-use of surfactant treatment. The use of BS1000 had a positive effect on the DO under ADI. With the increasing of BS1000 concentration, there was no significant difference neither in uniformity of DO nor water flow rate. However, compared to non-use of BS1000, the uniformity of gas flow at 4 mg/L of BS1000 was significantly decreased during one line transmission. The uniformity of water flow rate, DO and gas flow during two line transmission under ADI were higher than 95%, 96% and 67%. Compared to one line transmission, the uniformity of water flow rate, DO and gas flow during two line transmission were increased by 14.00%, 4.05% and 30.64%, respectively. Two line transmission was an optimal connection mode under ADI at the long distance of water delivery under ADI. This research will provide valuable information for optimization of aerated technique parameters and drip tape layout under ADI

Multi-user image retrieval with suppression of search pattern leakage

In image retrieval applications for multi-users, users can retrieve similar images in a database. The server can collude with the user and exploit the search patterns to infer the information of other users, which may cause search pattern leakage. However, current forward privacy solutions can only partially solve the problem. In this paper, a multi-user image retrieval scheme, called multi-user image retrieval with suppression of search pattern (MIRSP), is presented to suppress the search pattern leakage. This scheme uses a blockchain structure to establish an optimized tree index. Meanwhile, compressive sensing is used to convert high-dimensional feature vectors into similarity-preserving binary codes, which reduces the similarity calculation cost and guarantees the security of nodes. Then, a path shuffling algorithm is proposed to hide the identifier and position of the search nodes. Finally, a fully trusted certificate authority center is added to ensure the security management and distribution of keys and avoid unnecessary communication overhead. Our experimental evaluation shows that the proposed MIRSP is 3 × faster than the state-of-the-art schemes in search computation times, which demonstrates that MIRSP contributes significantly in providing security and privacy protection in multi-user scenarios

An Efficient Oblivious Random Data Access Scheme in Cloud Computing

With the development of cloud computing and cloud storage techniques, much attention has been focused on the privacy protection of outsourced data. Existing searchable encryption solutions can ensure the confidentiality and availability of data stored on the cloud. However, searchable encryption is vulnerable to statistical inference attacks, which exploit the disclosure of access patterns on encrypted indexes and encrypted file sets, which has become a potential way to reveal user privacy. Oblivious random access memory (ORAM) is an important means of concealing access patterns, yet its direct use in searchable encryptions is expensive. This paper presents a scheme for efficient and oblivious access to encrypted databases through encrypted indexes. This scheme is a hybrid ORAM scheme, which utilizes semi-homomorphic encryption to perform calculations in the ciphertext domain, overcoming the limitations of the huge overhead associated with Path-ORAM. For excessive amounts of data, semi-homomorphic encryption can significantly reduce communication and storage overhead. Our scheme can achieve high-security encrypted search and update operations at the same time. Moreover, the execution speed of ODS-Tree is 2-8x faster than that of ORAM-based schemes. In addition, the proposed scheme reduces the data block transmission and storage costs compared to existing frameworks