An Empirical Application of User-Guided Program Analysis

Although static program analysis methods are frequently employed to enhance software quality,their efficiency in commercial settings is limited by their high false positive rate.The EUGENE tool can effectively lower the false positive rate.However,in continuous integration(CI)environments,the code is always changing,and user feedback from one version of the software cannot be applied to a subsequent version.Additionally,people find it difficult to distinguish between true positives and false positives in the analytical output.In this study,we developed the EUGENE-CI technique to address the CI problem and the EUGENE-rank lightweight heuristic algorithm to rate the reports of the analysis output in accordance with the likelihood that they are true positives.On the three projects ethereum,go-cloud,and kubernetes,we assessed our methodologies.According to the trial findings,EUGENE-CI may drastically reduce false positives while EUGENE-rank can make it much easier for users to identify the real positives among a vast number of reports.We paired our techniques with GoInsight~1 and discovered a vulnerability.We also offered a patch to the community.

Defeating constraint based program analysis with temporal correlation function

Constraint based program analysis is widely used in program validation, program vulnerability analysis, etc. This paper proposes a temporal correlation function to protect programs from analysis. The temporal correlation function can be applied to resist against both static and dynamic function summary and eoncolie testing. What＇ s more, the temporal correlation function can produce different outputs even with same input. This feature can be used to damage the premise of function summary as well as prevent concolie testing process to run the new branch with new input. Experiment results show that this method can reduce efficiency and path coverage of concolic testing, while greatly in- creasing the difficulty of constraint based program analysis.

An Object Extraction Model Using Association Rules and Dependence Analysis

Extracting objects from legacy systems is a basic step in system's object orientation to improve the maintainability and understandability of the systems. A new object extraction model using association rules and dependence analysis is proposed. In this model data are classified by association rules and the corresponding operations are partitioned by dependence analysis.

Static program analysis for IoT risk mitigation in space-air-ground integrated networks

The space-air-ground integrated networks(SAGINs)are pivotal for modern communication and surveillance,with a growing number of connected devices.The proliferation of Io T devices within these networks introduces new risks due to potential erroneous synergistic interactions that could compromise system integrity and security.This paper addresses the challenges in coordination,synchronization,and security within SAGINs by introducing a novel static program analysis(SPA)technique using zero-knowledge(ZK)proofs.This approach ensures the detection of risky interactions without compromising sensitive source code,thus safeguarding intellectual property and privacy.The proposed method overcomes the incompatibility between SPA and ZK systems by developing an imperative programming language for SAGINs and a specialized abstract domain for interaction threats.The system translates network control algorithms into arithmetic circuits suitable for ZK analysis,maintaining high accuracy in detecting risks.Evaluations of real-world scenarios demonstrate the system's efficacy in identifying risky interactions with minimal computational overhead.This research presents the first ZK-based SPA scheme for SAGINs,enhancing security and confidentiality in network analysis while adhering to privacy regulations.

Uncertainty quantification of inverse analysis for geomaterials using probabilistic programming

Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological systems.In this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic programming.The ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical problems.Probabilistic programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical solution.The results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under uncertainty.Then,a slope case was employed to demonstrate the performance of the developed framework.The results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems.

Enhancing Data Analysis and Automation: Integrating Python with Microsoft Excel for Non-Programmers

Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and informed decision-making across diverse domains. Conversely, Python is indispensable for professional programming due to its versatility, readability, extensive libraries, and robust community support. It enables efficient development, advanced data analysis, data mining, and automation, catering to diverse industries and applications. However, one primary issue when using Microsoft Excel with Python libraries is compatibility and interoperability. While Excel is a widely used tool for data storage and analysis, it may not seamlessly integrate with Python libraries, leading to challenges in reading and writing data, especially in complex or large datasets. Additionally, manipulating Excel files with Python may not always preserve formatting or formulas accurately, potentially affecting data integrity. Moreover, dependency on Excel’s graphical user interface (GUI) for automation can limit scalability and reproducibility compared to Python’s scripting capabilities. This paper covers the integration solution of empowering non-programmers to leverage Python’s capabilities within the familiar Excel environment. This enables users to perform advanced data analysis and automation tasks without requiring extensive programming knowledge. Based on Soliciting feedback from non-programmers who have tested the integration solution, the case study shows how the solution evaluates the ease of implementation, performance, and compatibility of Python with Excel versions.

Dynamic Positioning Capability Analysis for Marine Vessels Based on A DPCap Polar Plot Program

Dynamic positioning capability(DPCap) analysis is essential in the selection of thrusters, in their configuration, and during preliminary investigation of the positioning ability of a newly designed vessel dynamic positioning system.DPCap analysis can help determine the maximum environmental forces, in which the DP system can counteract in given headings. The accuracy of the DPCap analysis is determined by the precise estimation of the environmental forces as well as the effectiveness of the thrust allocation logic. This paper is dedicated to developing an effective and efficient software program for the DPCap analysis for marine vessels. Estimation of the environmental forces can be obtained by model tests, hydrodynamic computation and empirical formulas. A quadratic programming method is adopted to allocate the total thrust on every thruster of the vessel. A detailed description of the thrust allocation logic of the software program is given. The effectiveness of the new program DPCap Polar Plot(DPCPP)was validated by a DPCap analysis for a supply vessel. The present study indicates that the developed program can be used in the DPCap analysis for marine vessels. Moreover, DPCap analysis considering the thruster failure mode might give guidance to the designers of vessels whose thrusters need to be safer.

MIXED ENERGY METHOD FOR SOLUTION OF QUADRATIC PROGRAMMING PROBLEMS AND ELASTIC-PLASTIC ANALYSIS OF TRUSS STRUCTURES

A new algorithm for the solution of quadratic programming problemsis put forward in terms of the mixed energy theory and is furtherused for the incremental solution of elastic-plastic trussstructures. The method proposed is different from the traditionalone, for which the unknown variables are selected just in one classsuch as displacements or stresses. The present method selects thevariables in the mixed form with both displacement and stress. As themethod is established in the hybrid space, the information found inthe previous incremental step can be used for the solution of thepresent step, making the algorithm highly effi- cient in thenumerical solution process of quadratic programming problems. Theresults obtained in the exm- ples of the elastic-plastic solution ofthe truss structures verify what has been predicted in thetheoretical anal- ysis.

Automatic Analysis Reporting for Hydro-Chemical Data Using Updated DurovPwin Program

Graphical representation of groundwater major dissolved constituents greatly help researchers in understanding the hydro-chemical evolution, grouping and areal distribution. Durov diagram is one of the most widely used technique but it requires a lot of tedious calculations. The DurovPlot program, which is used to plot the expanded Durov diagram as a graphical representation of groundwater major dissolved constituents is working on Disk Operating System （DOS） environment. Therefore, the need of a new program working under windows is a must. The program termed as DurovPwinis developed using Microsoft visual studio 2010. The DurovPwin program not only calculates the Durov coordinates and plot it, but also plots the total dissolved solids （TDS） on logarithmic scale and the measure of the activity of hydrogen ion （pH） of the given samples. The updated DurovPwin adds many features such as interface with Microsoft Office package （Word and Excel） to read the input chemical elements and automatically write result interpretation report. The user facility to group wells based on data features is added and the selection of the electric balance tolerance （10% as default） value is given. Another feature of the modified DurovPwinis has the ability to do useful X-Y plot for different hydro-chemical parameters to assist in data interpretation. The sodium adsorption ratio （SAR） is also calculated and written in the final report. Also, in the present study, the usability of the new version of DurovPwin program has been tested on the chemical data from 59 groundwater samples collected from A1-Jawf area, Saudi Arabia. The collected water samples were mainly from the Secondary-Tertiary-Quaternary （STQ） aquifer and some from Tawil and Jaufaquifers. The grouping of the major ions in the three aquifers have been displayed and presented using the DurovPwin program. The TDS values of Tawil aquifer ranges from 257.9 to 822.3 （2.4115 to 2.915） and for Jawf aquifer from 494.4 to 1,070 （2.6941 to 3.0294） and for STQ aquifer ranges from 399.5 to 9,861.8 （2.6015 to 3.994）. The pH for the three aquifers ranges from 7 to 7.9, 7.6 to 7.8 and 7.2 to 8.3, respectively.

The clinical association of programmed cell death protein 4(PDCD4) with solid tumors and its prognostic significance:a meta-analysis

Background: Programmed cell death protein 4(PDCD4) is a novel tumor suppressor protein involved in pro?grammed cell death. Its association with cancer progression has been observed in multiple tumor models, but evidence supporting its association with solid tumors in humans remains controversial. This study aimed to determine the clinical signiicance and prognostic value of PDCD4 in solid tumors.Methods: A systematic literature review was performed to retrieve publications with available clinical informa?tion and survival data. The eligibility of the selected articles was based on the criteria of the Dutch Cochrane Centre proposed by the Meta?analysis Of Observational Studies in Epidemiology group. Pooled odds ratios(ORs), hazard ratios(HRs), and 95% conidence intervals(CIs) for survival analysis were calculated. Publication bias was examined by Begg's and Egger's tests.Results: Clinical data of 2227 cancer patients with solid tumors from 23 studies were evaluated. PDCD4 expression was signiicantly associated with the diferentiation status of head and neck cancer(OR 4.25, 95% CI 1.87–9.66) and digestive system cancer(OR 2.87, 95% CI 1.84–4.48). Down?regulation of PDCD4 was signiicantly associated with short overall survival of patients with head and neck(HR: 3.44, 95% CI 2.38–4.98), breast(HR: 1.86, 95% CI 1.36–2.54), digestive system(HR: 2.12, 95% CI 1.75–2.56), and urinary system cancers(HR: 3.16, 95% CI 1.06–9.41).Conclusions: The current evidence suggests that PDCD4 down?regulation is involved in the progression of several types of solid tumor and is a potential marker for solid tumor prognoses. Its clinical usefulness should be conirmed by large?scale prospective studies.

A MATHEMATICAL PROGRAMMING ALGORITHM FOR LIMIT ANALYSIS

This paper deals with the limit analyses of perfect rigid-plastic continua.Based on the kinematic theorem of the limit analysis theory,a mathematical programming finite element formula for determining the upper bound load multiplier has been established,and an iteration algorithm proposed accordingly.In this algorithm the plastic and rigid zones are distinguished for every iteration step,and the goal function is modified gradually.The difficulties caused by the nonsmoothness of the goal function are over- come.Some examples solved by this algorithm are presented.

Application of Hybrid Programming with Matlab and C # in Reliability Analysis Software

Matlab has a high performance at engineering calculation.C# is good at interface development.Combining their advantages together,hybrid programming with Matlab and C # will help to improve the reliability analysis software efficiency and accuracy significantly.Procedures of hybrid programming with Matlab and C# in reliability analysis software are introduced in this paper.Finally a mathematical problem is tested to verify the feasibility of this programming method.

SHFuzz:A Hybrid Fuzzing Method Assisted by Static Analysis for Binary Programs

Fuzzing is an effective technique to find security bugs in programs by quickly exploring the input space of programs.To further discover vulnerabilities hidden in deep execution paths,the hybrid fuzzing combines fuzzing and concolic execution for going through complex branch conditions.In general,we observe that the execution path which comes across more and complex basic blocks may have a higher chance of containing a security bug.Based on this observation,we propose a hybrid fuzzing method assisted by static analysis for binary programs.The basic idea of our method is to prioritize seed inputs according to the complexity of their associated execution paths.For this purpose,we utilize static analysis to evaluate the complexity of each basic block and employ the hardware trace mechanism to dynamically extract the execution path for calculating the seed inputs’weights.The key advantage of our method is that our system can test binary programs efficiently by using the hardware trace and hybrid fuzzing.To evaluate the effectiveness of our method,we design and implement a prototype system,namely SHFuzz.The evaluation results show SHFuzz discovers more unique crashes on several real-world applications and the LAVA-M dataset when compared to the previous solutions.

Evaluating and Improving the Effectiveness of Vehicle Inspection and Maintenance Programs: A Cost-Benefit Analysis Framework

Motor vehicle inspection and maintenance (I/M) programs are designed to identify high-emitting vehicles and mitigate their impacts on air quality and climate. I/M programs have been traditionally ranked superior among various vehicle emission control measures by the results of cost-benefit analysis, based on the assumption that these programs will achieve the targeted emission reduction outcomes. However, the actual effects of I/M programs may be greatly uncertain and when this uncertainty is taken into account, these programs may become suboptimal. This study develops a new a cost-benefit analysis framework that links various program design consideration, such as program participation rate, identification rate and effective repair rate, to the public health benefits as well as costs of the programs. This framework helps decision makers to investigate minimum implementation requirements that at least ensure the benefits are greater than the costs of implementing the programs in order to improve the overall effectiveness of the I/M programs. To illustrate the applications of the framework, it was applied to a particulate matter oriented I/M program targeting all diesel-fueled vehicles in the city of Bangkok, Thailand, a large metropolitan area that has been suffering from severe ambient PM pollution mainly attributable to its wide use of diesel-fueled vehicles and motorcycles. It was found that the health benefits achieved from the program are sensitive to several key program design elements, including participation rate and problem vehicle identification rate, fraction of effective repairs and illegal operation rate. Other variables, such as the testing cut-points and vehicle population growth rate, only have modest effects on the overall emission reduction and consequent health benefits. Overall, the performance of multiple variables associated with I/M program design needs to be improved simultaneous in order to achieve the targeted benefits of the program.

Spatial Social Network Analysis: Program Pengembangan Usaha Agribisnis Perdesaan (PUAP) or an Exertion Development Program in Supporting the Region Revitalization Development

As the exertion development (PUAP) develop in Rejang Lebong Regency in Bengkulu province which had been started since 2008 by giving a kind of fund aid called Bantuan Langsung Masyarakat (BLM PUAP), to Gapoktan (Gabungan Kelompok Tani) or an organization of farmers such by giving some money as the capital used for 1) food plant cultiva-tion, horticulture, animal husbandry, plantation, and2) non-cultivation exertion such as;home industry of agriculture, small marketing scale and another agriculture exertion. By the approach which had been done is hoped to get the important result, on the other way the role of analysis factor (Social Network Analysis) from all undertaking stakeholders programs PUAP to be relevance steps aimed to understand the relation or connectivity from all factors in the network and also the role of factor inside the network itself be the relevance steps in arranging the strategy and work intention from the realization stage of PUAP program for the continuity of the realization program in the future (finding the good strategy) which aimed to develop the program of PUAP in Rejang Lebong Regency in Bengkulu Province, and to be a reference from doing the program as a national program in Indonesia.

A Review of Quantitative Analysis (QA) in Production Planning Decisions Using the Linear Programming Model

The purpose of this paper was to examine the role of quantitative analysis in production planning decisions. This draws from the observed imperatives of quantitative analysis in business decisions and its capacity for predictability and enhanced decision making given the increasingly complex nature of the business environment. The paper therefore addressed the historical evolution of quantitative technique as an efficient and effective decision-making tool. The content of the paper addressed commonly applied quantitative technique in manufacturing firms today which is, linear programming and its subsequent impact on production planning decisions. The results based on a congruence of views revealed that the “best-fit” application of quantitative analysis models and tools can untangle the complexities of production and planning decision making process in order to achieve the organizational goal. This is, as literature also showed that there is obviously no consensus or integrated model that is capable of solving all managerial problem, different models such as the linear programming model have however been developed to cater for different problems as they arise. The workability or suitability of quantitative analysis is actually premised on its appropriate application. The paper recommends the application of quantitative analysis using linear programming in solving various resource allocation related issues in the primary production planning function of manufacturing firms.

Turning Research into Action: Using Factor Analysis to Enhance Program Evaluation

Purpose: Sexual activity among adolescents in the United States remains high. Nearly 46% of students grades 9-12 have engaged in sexual intercourse. One of the more recent statistical tools employed in evaluation efforts includes factor analysis. The objective of this study was to investigate the underlying dimensions of a survey instrument that assesses a youth character development program, which focuses on avoiding high-risk behaviors. Method: The 76-item survey instrument was administered to adolescents (age 12-18). During the 2009-2010 school year, 652 participants in the intervention group and 1110 participants in the comparison group completed the pre-, post-, and 6-month follow-up survey. Results: Using Ajzen’s theory of planned behavior groupings, 27 survey items were selected. Through iterative principal axis factoring, four factors were extracted and rotated. A visual scree plot was generated to determine the number of acceptable factors. The extracted factors accounted for 52.53% of the total variance. Factors were subjected to Equimax rotation with Kaiser normalization and converged after six iterations. Variables with patterned weights less than 0.44 were excluded. A reliability analysis demonstrated internal consistency. Conclusions: Identified factors included: 1) Teenagers’ attitudes toward sexual health behaviors;2) Teenagers’ perceptions of the consequences of sexual health behaviors;3) Parental or guardian expectations;and 4) Teenagers’ relationships with parents or guardians. This study’s results indicated that all factors can be described within Ajzen’s theoretical framework consistent with previous research findings. Results may be used to enhance delivery of the intervention.

An Efficiency Analysis of MBA Programs in China’s Business Schools

Based on the data of the best MBA ranking in China selected by Manager Magazine,DEA and Malmquist index were used to evaluate the efficiency of MBA programs of top 25 business schools in China.The results show that the overall MBA programs have a high value on technical efficiency due to the high pure technical efficiency and scale efficiency.As the technical regress deepened,the total factor productivity of MBA program presents a dropped tendency.The results of ANOVA show that the location,type and international certification have no significant effect on the efficiency.According to the cross analysis of technical efficiency and total factor productivity,different business schools should adopt different development strategies.

An Efficiency and Ranking Analysis of EMBA Programs in China

Even though ranking scores help business schools to build their own reputation,they lack of guidance to assess the actual efficiency of operations.Based on the data of the best MBA ranking in China selected by Manager Magazine,DEA was used to evaluate the efficiency of EMBA programs of top 36 business schools in China.This paper also compared the efficiency score of each business school with the rank score assigned by the traditional ranking.The results show that the overall EMBA programs have a high value on technical efficiency due to the high pure technical efficiency and scale efficiency.Different business schools have different efficiency.The findings reveal areas of incoherence between efficiency measures and rankings.

Combined Water-Oxygen Pinch Analysis with Mathematical Programming for Wastewater Treatment

Water-oxygen pinch analysis is an effective method to decrease the wastewater quantity and improve the wastewater quality. But when multiple-contaminants are present, the method is difficult to be carried out. In this paper, the method that combines water-oxygen pinch analysis with mathematical programming is proposed. It obtains the general optimal solution and leads to the reuse stream that cannot be found only by pinch analysis. The new method is illustrated by an example, and the annual cost is reduced by 8.43% compared with the solution of literature.