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OPA Solver: A web-based software for Ordinal Priority Approach in multiple criteria decision analysis using javascript

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SOFTWAREX 2023年 24卷

作者： Mahmoudi, Amin Sadeghi, Mahsa Deng, Xiaopeng Pan, Pengcheng Southeast Univ Sch Civil Engn Dept Construct & Real Estate Nanjing Peoples R China Yanshan Univ Coll Civil Engn & Mech Dept Civil Engn Qinhuangdao Hebei Peoples R China

Multiple criteria decision-making (MCDM) is an effective technique for evaluating and selecting alternative(s) based on a set of criteria/sub-criteria. Most MCDM techniques use cardinal data as input data. However, in realworld situations, decision-makers face difficulties, while providingexact values for comparing alternatives/ criteria. While "Ordinal Data" is more tangible and straightforward to use by human. Considering human ability in ordinal thinking and expressing preferences, the Ordinal Priority Approach (OPA) was proposed in 2020 to solve the MCDM problems with the ordinal data as input. In the current study, a novel web-based software is developed using javascript to streamline and facilitate solving the OPA model. It (i) supports individual and group decision-making, (ii) calculates the weights of the experts, alternatives, and criteria, and (iii) determines confidence level value and uncertainty in the group decision-making problems to check the quality of the input and result. Promisingly, this software is user-friendly for users, time-efficient, accurate for solving MCDM problems, and practical with significant impacts on the academic and industrial worlds.

关键词： Ordinal priority approach Multiple criteria decision-making javascript Spreadsheet Software

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Is javascript Call Graph Extraction Solved Yet? A Comparative Study of Static and Dynamic Tools

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IEEE ACCESS 2023年 11卷 25266-25284页

作者： Antal, Gabor Hegedus, Peter Herczeg, Zoltan Loki, Gabor Ferenc, Rudolf Univ Szeged Dept Software Engn H-6720 Szeged Hungary

Code analysis is more important than ever because javascript is increasingly popular and actively used, both on the client and server sides. Most algorithms for analyzing vulnerabilities, finding coding issues, or inferring type depend on the call graph representation of the underlying program. Luckily, there are quite a few tools to get this job done already. However, their performance in vitro and especially in vivo has not yet been extensively compared and evaluated. In this paper, we compare several approaches for building javascript call graphs, namely five static and two dynamic approaches on 26 WebKit SunSpider programs, and two static and two dynamic approaches on 12 real-world *** programs. The tools under examination using static techniques were npm call graph, IBM WALA, Google Closure Compiler, Approximate Call Graph, and Type Analyzer for javascript. We performed dynamic analyzes relying on the nodejs-cg tool (a customized *** runtime) and the NodeProf instrumentation and profiling framework. We provide a quantitative evaluation of the results, and a result quality analysis based on 941 manually validated call edges. On the SunSpider programs, which do not take any inputs, so dynamic extraction could be complete, all the static tools also performed well. For example, TAJS found 93% of all edges while having a 97% precision compared to the precise dynamic call graph. When it comes to real-world *** modules, our evaluation shows that static tools struggle with parsing the code and fail to detect a significant amount of call edges that dynamic approaches can capture. Nonetheless, a significant number of edges not detected by dynamic approaches are also reported. Among these, however, there are also edges that are real, but for some reason the unit tests did not execute the branches in which these calls were included.

关键词： Image edge detection Codes Performance analysis Source coding Static analysis Servers Call graph comparative study dynamic code analysis javascript static code analysis

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Automate cancer synoptic reporting with HyperText Markup Language (HTML) and javascript

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AMERICAN JOURNAL OF CLINICAL PATHOLOGY 2025年第5期163卷 678-687页

作者： Duan, Aaron Guo, Kevin Guo, Huazhang Clayton High Sch Clayton MO USA St Louis Univ Dept Pathol St Louis MO 63103 USA

Objectives The College of American Pathologists (CAP) Cancer Protocols are developed to facilitate cancer synoptic reporting. CAP offers these Cancer Protocols in both free printable and commercially licensed electronic formats. Several academic institutions have also implemented these Cancer Protocols as web-based services. Due to financial and technical limitations, many resource-limited pathology laboratories still rely on the free printable Cancer Protocols that involve extensive text editing and secretarial support, and they are *** study implemented low-cost, low-barrier, and flexible electronic CAP Cancer Protocols to automate cancer synoptic *** For each printable CAP Cancer Protocol, a dynamic data entry form is created using HyperText Markup Language (HTML) with embedded javascript, which is then presented in a web browser for pathologists to enter cancer case-specific information. Once the data entry form is complete, the case-specific information entered by the pathologists will be collected, and a synoptic report will be automatically created in the web browser by a companion javascript program. The synoptic report can then be copied into the corresponding pathology *** We implemented the commonly used CAP Cancer Protocols into electronic form using HTML/javascript. Using this tool, our pathologist reported at least 50% time savings compared to the previous manual *** The proposed HTML/javascript-based Cancer Protocols are low-cost, low-barrier, and flexible alternatives to current commercially and academically available electronic CAP Cancer Protocols, especially for pathologists working in resource-limited laboratories. The same implementation methods can also be extended to implement international variants of Cancer Protocols, including non-English Cancer Protocols.

关键词： CAP Cancer Protocols cancer synoptic reporting HyperText Markup Language (HTML) javascript automation

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Breaking Bad: Quantifying the Addiction of Web Elements to javascript

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ACM TRANSACTIONS ON INTERNET TECHNOLOGY 2023年第1期23卷 1-28页

作者： Fouquet, Romain Laperdrix, Pierre Rouvoy, Romain Univ Lille INRIA CNRS Cent LilleUMR 9189 CRIStAL F-59000 Lille France Univ Lille Inria Lille CNRS Lille France Univ Lille Inria IUF Lille France

While javascript established itself as a cornerstone of the modern web, it also constitutes a major tracking and security vector, thus raising critical privacy and security concerns. In this context, some browser extensions propose to systematically block scripts reported by crowdsourced trackers lists. However, this solution heavily depends on the quality of these built-in lists, which may be deprecated or incomplete, thus exposing the visitor to unknown trackers. In this article, we explore a different strategy by investigating the benefits of disabling javascript in the browser. More specifically, by adopting such a strict policy, we aim to quantify the javascript addiction of web elements composing a web page through the observation of web breakages. As there is no standard mechanism for detecting such breakages, we introduce a framework to inspect several page features when blocking javascript, that we deploy to analyze 6,384 pages, including landing and internal web pages. We discover that 43% of web pages are not strictly dependent on javascript and that more than 67% of pages are likely to be usable as long as the visitor only requires the content from the main section of the page, for which the user most likely reached the page, while reducing the number of tracking requests by 85% on average. Finally, we discuss the viability of currently browsing the web without javascript and detail multiple incentives for websites to be kept usable without javascript.

关键词： Web privacy javascript page breakage

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Forecasting the Principal of Code Technical Debt in javascript Applications

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2023年第4期49卷 2498-2512页

作者： Zozas, Ioannis Bibi, Stamatia Ampatzoglou, Apostolos Univ Western Macedonia Dept Elect & Comp Enigneering Kozani 50100 Greece Univ Macedonia Dept Appl Informat Thessaloniki 54636 Greece

javascript (JS) is one of the most popular programming languages for developing client-side applications mainly due to allowing the adoption of different programming styles, not having strict syntax rules, and supporting a plethora of frameworks. The flexibility that the language provides may accelerate the development of application, but also pose threats to the quality of the final software product, e.g., introducing Technical Debt (TD). TD reflects the additional cost of software maintenance activities to implement new features, occurring due to poorly developed solutions. Being able to forecast the levels of TD in the future can be extremely valuable in managing TD, since it can contribute to informed decision making when designating future repayments and refactoring budget among a company's projects. Despite the popularity of JS and the undoubtful benefits of accurate TD forecasting, in the literature, there is available only a limited number of tools and methodologies that are able to: (a) forecast TD during software evolution, (b) provide a ground-truth TD quantifications to train forecasting, since TD tools that are available are based on different rulesets and none is recognized as a state-of-the-art solution, (c) take into consideration the language-specific characteristics of JS. As a main contribution for this study, we propose a methodology (along with a supporting tool) that supports the aforementioned goals based on the Backward Stepwise Regression and Auto-Regressive Integrated Moving Average (ARIMA). We evaluate the proposed approach through a case study on 19,636 releases of 105 open-source applications. The results point out that: (a) the proposed model can lead to an accurate prediction of TD, and (b) the Number of appearances of the "new" and "eval" keyword along with the number of "anonymous" and "arrow" functions are among the features of javascript language that are related to high levels of TD.

关键词： Predictive models Measurement Forecasting Codes Java Source coding Programming Code technical debt javascript software quality source code quality

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Finding Server-Side Endpoints with Static Analysis of Client-Side javascript

Finding Server-Side Endpoints with Static Analysis of Client...

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28th European Symposium on Research in Computer Security (ESORICS)

作者： Sigalov, Daniil Gamayunov, Dennis Lomonosov Moscow State Univ Moscow Russia SolidSoft LLC Moscow Russia

ISBN: (纸本)9783031541285;9783031541292

Determining server HTTP endpoints - essentially, revealing server's attack surface - is a crucial step of every black-box web security scanner. An indispensable method of doing that is inferring server endpoints from client side, discovering what HTTP requests can be sent from client to server. This is easy for requests triggered by HTML markup elements, such as links and forms, but is difficult for requests sent by javascript. Existing approaches to determining requests sent from javascript are based on a technique known as dynamic crawling automated interaction with web page elements using a headless browser. Dynamic crawling fails when the code that sends a request is impossible or very hard to trigger with interface interaction. We propose a different approach for finding HTTP requests sent by JS code, which uses static code analysis. While analyzing javascript statically is known to be hard and applying existing analyzers to real-world web pages usually does not work, we propose a new lightweight analysis algorithm that can work on pages of real websites, and can discover server endpoints that dynamic crawlers cannot. Evaluation results show that augmenting a black-box scanner with the proposed static analysis may significantly improve server-side endpoint coverage.

关键词： Web applications Static analysis javascript

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JSMBox-A Runtime Monitoring Framework for Analyzing and Classifying Malicious javascript 33rd

JSMBox-A Runtime Monitoring Framework for Analyzing and Clas...

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33rd International Conference on Software and Data Engineering

作者： Phung, Phu H. Varghese, Allen Wang, Bojue Zhao, Yu Yu, Chong Univ Dayton Dept Comp Sci Intelligent Syst Secur Lab 300 Coll Pk Ave Dayton OH 45469 USA Univ Cincinnati Dept Comp Sci 2901 Woodside Dr Cincinnati OH 45221 USA Univ Cincinnati Dept Elect & Comp Engn Cincinnati OH USA

ISBN: (纸本)9783031752001;9783031752018

In recent years, there has been a notable increase in the prevalence of malicious websites, leading to a majority of cyber-attacks and data breaches. Malicious websites often incorporate javascript code to execute attacks on web browsers. Despite existing methodologies documented in the literature, the analysis and detection of malicious javascript pose significant challenges due to the dynamic nature of javascript and the use of advanced evasion techniques. These challenges motivate the need for an innovative and efficient approach to comprehensively analyze the code to identify its malicious intent. In this paper, we introduce a monitoring approach for analyzing javascript code, which can capture all of the code's features at runtime. Our method leverages the security reference monitor technique to mediate javascript security-sensitive executions, including function calls and property accesses. Therefore, the proposed method can capture behaviors at runtime regardless of how the code is written, even with recent advanced evasion techniques like WebAssembly diversification. We have implemented our approach as a javascript dynamic analysis framework called JSMBox in aChromium-based browser extension. Our experiments demonstrated that JSMBox is capable of effectively countering sophisticated evasion techniques found in modern malicious javascript code, including WebAssembly diversification. We have also evaluated the framework's ability to classify malicious behaviors based on a large-scale raw dataset comprising about 20,000 malicious and benign webpages. Our developed tool automatically launches the browser to execute these webpages, records javascript code execution events, and captures their execution frequency as extracted features. We have tested the extracted dataset with various machine-learning models, yielding promising experimental results that confirm the effectiveness of our approach and achieve a high accuracy rate.

关键词： javascript Dynamic Analysis Runtime Monitoring Maliciousness Classification

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Elysia: Optimizing javascript Web Framework 24

Elysia: Optimizing JavaScript Web Framework

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39th Annual ACM Symposium on Applied Computing (SAC)

作者： Archiwaranguprok, Chayapatr Khunpanitchot, Kongkeit Mano, Phoomparin Toahchoodee, Manachai Univ Thai Chamber Commerce Bangkok Thailand Creatorsgarten Bangkok Thailand

ISBN: (纸本)9798400702433

As javascript and its backend web frameworks garnered mainstream adoption and played a pivotal role in today's industry, challenges of runtime performance, developer experience, and type safety are potential hindrances to scaling and maintainability. This paper suggests strategies for web frameworks in javascript to provide a balanced focus between performance and convenience by optimizing the performance of potentially expensive ergonomic features by utilizing javascript's interpreted nature and Just-In-Time compilation through the use of static analysis and dynamic code generation techniques in conjunction with adopting TypeScript's type system to provide an improved developer experience. The reference implementation of the optimization strategies and design for developer experience is illustrated through the implementations in the Elysia javascript web framework, in which the performance is evaluated against non-optimized code and benchmarked against other real-world backend web frameworks.

关键词： javascript RESTful API Static Analysis Optimization Type Safety

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jscefr: A Framework to Evaluate the Code Proficiency for javascript 40

jscefr: A Framework to Evaluate the Code Proficiency for Jav...

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40th International Conference on Software Maintenance and Evolution

作者： Ragkhitwetsagur, Chaiyong Kongwongsupak, Komsan Maneesawas, Thanakrit Puttiwarodom, Natpichsinee Rojpaisarnkitt, Ruksit Choetkiertikul, Morakot Kulat, Raula Gaikovina Sunetnanta, Thanwadee Mahidol Univ Fac Informat & Commun Technol ICT Phutthamonthon Dist Nakhon Pathom Thailand Nara Inst Sci & Technol Grad Sch Sci & Technol Nara Japan Osaka Univ Grad Sch Informat Sci & Technol Osaka Japan

ISBN: (纸本)9798350395693;9798350395686

In this paper, we present jscefr (pronounced jes-cee-fer), a tool that detects the use of different elements of the javascript (JS) language, effectively measuring the level of proficiency required to comprehend and deal with a fragment of javascript code in software maintenance tasks. Based on the pycefr tool, the tool incorporates javascript elements and the well-known Common European Framework of Reference for Languages (CEFR) and utilizes the official ECMAScript javascript documentation from the Mozilla Developer Network. jscefr categorizes JS code into six levels based on proficiency. jscefr can detect and classify 138 different javascript code constructs. To evaluate, we apply our tool to three javascript projects of the NPM ecosystem, with interesting results. A video demonstrating the tool's availability and usage is available at https://***/Ehh-Prq59Pc.

关键词： javascript proficiency CEFR

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Energy Consumption of Evolutionary Algorithms in javascript 17th

Energy Consumption of Evolutionary Algorithms in JavaScript

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17th Italian Workshop on Artificial Life and Evolutionary Computation (WIVACE)

作者： Merelo-Guervos, Juan J. Garcia-Valdez, Mario Castillo, Pedro A. Univ Granada Dept Comp Engn Automat & Robot Granada Spain Natl Technol Inst Mexico Dept Grad Studies Tijuana Mexico

ISBN: (纸本)9783031574290;9783031574306

Green computing is a methodology for saving energy when implementing algorithms. In environments where the runtime is an integral part of the application, it is essential to measure their energy efficiency so that researchers and practitioners have enough choice. In this paper, we will focus on javascript runtime environments for evolutionary algorithms;although not the most popular language for scientific computing, it is the most popular language for developers, and it has been used repeatedly to implement all kinds of evolutionary algorithms almost since its inception. In this paper, we will focus on the importance of measuring different versions of the same runtimes, as well as extending the EA operators that will be measured. We also like to remark on the importance of testing the operators in different architectures to have a more precise picture that tips the balance towards one runtime or another.

关键词： Green computing metaheuristics javascript energy-aware computing evolutionary algorithms

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