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14th International Symposium on Search-Based Software Engineering (SSBSE)

作者： Stallenberg, Dimitri Olsthoorn, Mitchell Panichella, Annibale Delft Univ Technol Delft Netherlands

ISBN: (纸本)9783031212505;9783031212512

Search-based test case generation approaches make use of static type information to determine which data types should be used for the creation of new test cases. Dynamically typed languages like javascript, however, do not have this type information. In this paper, we propose an unsupervised probabilistic type inference approach to infer data types within the test case generation process. We evaluated the proposed approach on a benchmark of 98 units under test (i.e., exported classes and functions) compared to random type sampling w. r. t. branch coverage. Our results show that our type inference approach achieves a statistically significant increase in 56% of the test files with up to 71% of branch coverage compared to the baseline.

关键词： Empirical software engineering Search-based software testing Test case generation javascript Type inference

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Trends on Crowdsourcing javascript Small Tasks 17

Trends on Crowdsourcing JavaScript Small Tasks

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17th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE)

作者： Zozas, Ioannis Anagnostou, Iason Bibi, Stamatia Univ Western Macedonia Dept Elect & Comp Engn Kozani Greece

ISBN: (纸本)9789897585685

Crowdsourcing has become a popular alternative model for software development, aiming at assigning tasks to developers through an open call for participation. The major challenge when crowdsourcing software tasks, is to appropriately orient the tasks to ensure the participation of the community and increase the chances of getting a high-quality solution. Especially in constantly evolving development environments, such as javascript (JS) programming language and its applications, it is of high importance to be aware of the skills that can be acquired by the community, to successfully invest in crowdsourcing. In the current paper, we aim to explore trends when crowdsourcing small JS development tasks in an attempt to unveil a) the core technological skills that are more frequently required in the crowdsourced tasks, b) the functionalities that are more frequently crowdsourced, and c) the relationship between the technological skills and the functionalities crowdsourced. For this reason, we analysed 8-year contest data collected from Bountify crowdsourcing platform. The results showed that JS small task development does not focus on a single technology but on a series of technologies, frameworks and libraries that in most cases either overlap or complement each other.

关键词： javascript Crowdsourcing Small Tasks Bountify

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Performance Benchmarking of PyScript and Comparative Results with javascript 13

Performance Benchmarking of PyScript and Comparative Results...

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IEEE 13th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)

作者： Arepalli, Venkata Sai Pavan Sekharan, Chandra N. Texas A&M Univ Corpus Christi Dept Comp Sci Corpus Christi TX 78412 USA

ISBN: (数字)9781665492997

ISBN: (纸本)9781665492997

In the last two decades that there has been an explosion in the use of web applications. Given the ever expanding number of web and mobile apps, extensive work has been done in developing and using efficient core technologies to support the performance goals of the apps. In particular, front-end developer languages such as javascript are highly popular. In this paper, we perform a detailed study of the recently introduced Python-based web development framework PyScript and evaluate the performance of PyScript in comparison with javascript using standard benchmarks. The research contributions of this work are in the benchmarking of code in three different categories (i) DOM manipulation, (ii) Operations involving the network layer, and (iii)cpu-intensive computations. The benchmarks come from one of the standards and carefully implemented to perform a comparative evaluation. Results show that native javascript code runs faster on all DOM and networking sets of benchmarks by a factor of 1.5 to 5 when compared with PyScript, with the exception of two of the networking benchmarks. It is in the computationally intensive benchmarks that javascript trumps PyScript by a factor of 25 to 35 depending the algorithm. We offer architectural insights into performance issues and conclude with directions on further research.

关键词： javascript PyScript benchmarking comparative results DOM network algorithms

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AUGUR: Dynamic Taint Analysis for Asynchronous javascript 7

AUGUR: Dynamic Taint Analysis for Asynchronous JavaScript

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37th IEEE/ACM International Conference on Automated Software Engineering (ASE)

作者： Aldrich, Mark W. Turcotte, Alexi Blanco, Matthew Tip, Frank Tufts Univ Medford MA 02155 USA Northeastern Univ Boston MA 02115 USA

ISBN: (纸本)9781450394758

Dynamic taint analysis (DTA) is a popular approach to help protect javascript applications against injection vulnerabilities. In 2016, the ECMAScript 7 javascript language standard introduced many language features that most existing DTA tools for javascript do not support, e.g., the async/await keywords for asynchronous programming. We present Augur, a high-performance dynamic taint analysis for ES7 javascript that leverages VM-supported instrumentation. Integrating directly with a public, stable instrumentation API gives Augur the ability to run with high performance inside the VM and remain resilient to language revisions. We extend the abstract-machine approach to DTA to handle asynchronous function calls. In addition to providing the classic DTA use case of injection vulnerability detection, Augur is highly configurable to support any type of taint analysis, making it useful outside of the security domain. We evaluated Augur on a set of 20 benchmarks, and observed a median runtime overhead of only 1.77x, a median performance improvement of 298% compared to the previous state-of-the-art.

关键词： dynamic program analysis taint analysis information flow analysis security vulnerabilities javascript

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Towards Understanding the Faults of javascript-Based Deep Learning Systems 7

Towards Understanding the Faults of JavaScript-Based Deep Le...

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37th IEEE/ACM International Conference on Automated Software Engineering (ASE)

作者： Quan, Lili Guo, Qianyu Xie, Xiaofei Chen, Sen Li, Xiaohong Liu, Yang Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China Zhongguancun Lab Beijing Peoples R China Singapore Management Univ Singapore Singapore Nanyang Technol Univ Singapore Singapore

ISBN: (纸本)9781450394758

Quality assurance is of great importance for deep learning (DL) systems, especially when they are applied in safety-critical applications. While quality issues of native DL applications have been extensively analyzed, the issues of javascript-based DL applications have never been systematically studied. Compared with native DL applications, javascript-based DL applications can run on major browsers, making the platform- and device-independent. Specifically, the quality of javascript-based DL applications depends on the 3 parts: the application, the third-party DL library used and the underlying DL framework (e.g., ***), called javascript-based DL system. In this paper, we conduct the first empirical study on the quality issues of javascript-based DL systems. Specifically, we collect and analyze 700 real-world faults from relevant GitHub repositories, including the official *** repository, 13 third-party DL libraries, and 58 javascript-based DL applications. To better understand the characteristics of these faults, we manually analyze and construct taxonomies for the fault symptoms, root causes, and fix patterns, respectively. Moreover, we also study the fault distributions of symptoms and root causes, in terms of the different stages of the development lifecycle, the 3-level architecture in the DL system, and the 4 major components of *** framework. Based on the results, we suggest actionable implications and research avenues that can potentially facilitate the development, testing, and debugging of javascript-based DL systems.

关键词： javascript Deep Learning TensorFlow.js Faults

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An Empirical Study of Flaky Tests in javascript 39

An Empirical Study of Flaky Tests in JavaScript

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39th IEEE International Conference on Software Maintenance and Evolution (ICSME)

作者： Hashemi, Negar Tahir, Amjed Rasheed, Shawn Massey Univ Palmerston North New Zealand

ISBN: (数字)9781665479561

ISBN: (纸本)9781665479561

Flaky tests (tests with non-deterministic outcomes) can be problematic for testing efficiency and software reliability. Flaky tests in test suites can also significantly delay software releases. There have been several studies that attempt to quantify the impact of test flakiness in different programming languages (e.g., Java and Python) and application domains (e.g., mobile and GUI-based). In this paper, we conduct an empirical study of the state of flaky tests in javascript. We investigate two aspects of flaky tests in javascript projects: the main causes of flaky tests in these projects and common fixing strategies. By analysing 452 commits from large, top-scoring javascript projects from GitHub, we found that flakiness caused by concurrency-related issues (e.g., async wait, race conditions or deadlocks) is the most dominant reason for test flakiness. The other top causes of flaky tests are operating system-specific (e.g., features that work on specific OS or OS versions) and network stability (e.g., internet availability or bad socket management). In terms of how flaky tests are dealt with, the majority of those flaky tests (>80%) are fixed to eliminate flaky behaviour and developers sometimes skip, quarantine or remove flaky tests.

关键词： Flaky Tests Test Bugs javascript

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More Effective javascript Breaking Change Detection via Dynamic Object Relation Graph

Proceedings of the ACM on Software Engineering

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Proceedings of the ACM on Software Engineering 2025年第ISSTA期2卷 2340-2361页

作者： Dezhen Kong Jiakun Liu Chao Ni David Lo Lingfeng Bao Zhejiang University Hangzhou China Singapore Management University Singapore Singapore Zhejiang University Ningbo China

javascript libraries are characterized by their widespread use, frequent code changes, and a high tolerance for backward incompatible changes. Awareness of such breaking changes can help developers adapt to version updates and avoid negative impacts. Several tools have been targeted to or can be used to detect breaking change detection in the javascript community. However, these tools detect breaking changes using different ways, and there are currently no systematic reviews of these approaches. From a preliminary study on popular javascript libraries, we find that existing approaches, including simple regression testing, model-based testing and type differencing cannot detect many breaking changes but can produce plenty of false positives. We discuss the reasons for missing breaking changes and producing false *** on the insights from our findings, we propose a new approach named Diagnose that iteratively constructs an object relation graph based on API exploration and forced execution-based type analysis. Diagnose then refine the graphs and reconstruct the graphs in the newer versions of the libraries to detect breaking changes. By evaluating approach on the same set of libraries used in the empirical study, we find that Diagnose can detect much more breaking changes (60.2%) and produce fewer false positives. Therefore, Diagnose is suitable for practical use.

关键词： Breaking Change javascript NPM

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ThingsMigrate: Platform-independent migration of stateful javascript Internet of Things applications

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SOFTWARE-PRACTICE & EXPERIENCE 2021年第1期51卷 117-155页

作者： Jung, Kumseok Gascon-Samson, Julien Goyal, Shivanshu Rezaiean-Asel, Armin Pattabiraman, Karthik Univ British Columbia Elect & Comp Engn Dept Vancouver BC Canada Ecole Technol Super Software & IT Engn Dept Montreal PQ Canada

The Internet of Things (IoT) has gained wide popularity both in academic and industrial contexts. Unlike traditional embedded devices with specialized firmwares, modern IoT devices accommodate general-purpose operating systems, allowing developers to run more sophisticated applications written in high-level languages like javascript. Because IoT devices are subject to resource constraints like available battery power, we need to dynamically migrate a running process between different devices to prevent losing state. However, it is challenging to apply migration techniques using memory snapshots across the heterogeneous pool of IoT devices. We present ThingsMigrate, a middleware providing platform-independent migration of javascript processes across IoT devices. Prior to execution, ThingsMigrate instruments the source code of a given program to expose its internal state. During run-time, the transformed program produces on demand a JSON snapshot of its current state, from which new code is generated to resume execution. Thus, ThingsMigrate enables process migration entirely in the application space without any modifications to the underlying virtual machine (VM), providing VM-independence. We present three versions of ThingsMigrate, each building on the previous to optimize for run-time latency and memory consumption. We report on the experience of building each successive version and discuss the insights gained and the learning outcomes. We evaluated ThingsMigrate against standard benchmarks, over two IoT platforms and a cloud-like environment. We show that it can migrate even highly CPU-intensive applications, with average run-time latency overhead of 33% and memory overhead of 78%. ThingsMigrate supports multiple subsequent migrations without introducing additional overhead over each subsequent migration.

关键词： Internet of Things javascript process migration program transformation

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Evolving javascript Code to Reduce Load Time

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2021年第8期47卷 1544-1558页

作者： Farzat, Fabio de A. Barros, Marcio de O. Travassos, Guilherme H. COPPE UFRJ Syst Engn & Comp Sci Program Cx Postal 68501Cidade Univ BR-21941594 Rio De Janeiro RJ Brazil PPGI UNIRIO Postgrad Informat Syst Dept AV Pasteur 458 BR-22290250 Rio De Janeiro RJ Brazil

javascript is one of the most used programming languages for front-end development of Web applications. The increase in complexity of front-end features brings concerns about performance, especially the load and execution time of javascript code. In this paper, we propose an evolutionary program improvement technique to reduce the size of javascript programs and, therefore, the time required to load and execute them in Web applications. To guide the development of this technique, we performed an experimental study to characterize the patches applied to javascript programs to reduce their size while keeping the functionality required to pass all test cases in their test suites. We applied this technique to 19 javascript programs varying from 92 to 15,602 LOC and observed reductions from 0.2 to 73.8 percent of the original code, as well as a relationship between the quality of a program's test suite and the ability to reduce the size of its source code.

关键词： Software Syntactics Genetic programming Software algorithms Heuristic algorithms Libraries Runtime javascript source code improvement genetic programming local search

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Muzeel: Assessing the Impact of javascript Dead Code Elimination on Mobile Web Performance 22

Muzeel: Assessing the Impact of JavaScript Dead Code Elimina...

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22nd ACM Internet Measurement Conference (IMC)

作者： Kupoluyi, Jesutofunmi Chaqfeh, Moumena Varvello, Matteo Coke, Russell Hashmi, Waleed Subramanian, Lakshmi Zaki, Yasir New York Univ Abu Dhabi Abu Dhabi U Arab Emirates Nokia Berkeley Hts NJ USA

ISBN: (纸本)9781450392594

To quickly create interactive web pages, developers heavily rely on (large) general-purpose javascript libraries. This practice bloats web pages with complex unused functions dead code which are unnecessarily downloaded and processed by the browser. The identification and the elimination of these functions is an open problem, which this paper tackles with Muzeel, a black-box approach requiring neither knowledge of the code nor execution traces. While the state-of-the-art solutions stop analyzing javascript when the page loads, the core design principle of Muzeel is to address the challenge of dynamically analyzing javascript after the page is loaded, by emulating all possible user interactions with the page, such that the used functions (executed when interactivity events fire) are accurately identified, whereas unused functions are filtered out and eliminated. We run Muzeel against 15,000 popular web pages and show that half of the 300,000 javascript files used in these pages have at least 70% of unused functions, accounting for 55% of the files' sizes. To assess the impact of dead code elimination on Mobile Web performance, we serve 200 Muzeel-ed pages to several Android phones and browsers, under variable network conditions. Our evaluation shows that Muzeel can speed up page loads by 25-30% thanks to a combination of lower CPU and bandwidth usage. Most importantly, we show that such savings are achieved while maintaining the pages' visual appearance and interactive functionality.

关键词： javascript User Experience Web Simplification Mobile Web

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