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Improving the detection of technical debt in java source code with an enriched dataset

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arXiv 2024年

作者： Hai, Nam Le Bui, Anh M.T. Nguyen, Phuong T. Di Ruscio, Davide Kazman, Rick Hanoi University of Science and Technology Viet Nam Università degli Studi dell'Aquila L'Aquila67100 Italy University of Hawaii United States

Technical debt (TD) is a term used to describe the additional work and costs that emerge when developers have opted for a quick and easy solution to a problem, rather than a more effective and well-designed, but time-consuming approach. Self-Admitted Technical Debts (SATDs) are a specific type of technical debts that developers intentionally document and acknowledge, typically via textual comments. While these self-admitted comments are a useful tool for identifying technical debts, most of the existing approaches focus on capturing crucial tokens associated with various categories of TD, neglecting the rich information embedded within the source code itself. Recent research has focused on detecting SATDs by analyzing comments embedded in source code, and there has been little work dealing with technical debts contained in the source code. To fill such a gap, in this study, through the analysis of comments and their associated source code from 974 java projects hosted in the Stack corpus, we curated the first ever dataset of TD identified by code comments, coupled with its associated source code. Through an empirical evaluation, we found out that the comments of the resulting dataset help enhance the prediction performance of state-of-the-art SATD detection models. More importantly, including the classified source code significantly improves the accuracy in predicting various types of technical debt. In this respect, our work is two-fold: (i) We believe that our dataset will catalyze future work in the domain, inspiring various research issues related to the recognition of technical debt;(ii) The proposed classifiers may serve as baselines for other studies on the detection of TD by means of the curated dataset. © 2024, CC BY-NC-SA.

关键词： java programming language

A scalable contents distribution service using a java agent application framework

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Lecture Notes in Computer Science (including subseries Lectu...

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2005年 3754卷 266-276页

作者： Lee, Kil-Hung Kim, Jae-Soo Shin, Yong-Hyeon Dept. of Computer Science and Engineering Seoul National Univ. of Tech. 172 Gongnung-2dong Nowon-gu Seoul139-743 Korea Republic of

ISBN: (纸本)3540296417

This paper presents a java agent application framework and shows its example through the implementation of an agent application service. This framework comprised of agent, agent system, agent master and agent manager components. Each component is connected to others via an agent interface, and messages are passed through these interface points. By using this framework, it is possible to deploy a new agent application service with simple and efficient operation. Herein, we implemented the agent application service network using a java agent application framework. Specifically, the implemented network was a contents distribution network using an agent service, and the network was both controlled and managed with the agent framework interface. In our test, the network service decreased network traffic while preserving reasonable quality through the adequate deployment and management of agent components. © IFIP International Federation for Information Processing 2005.

关键词： java programming language

Automating Alert Handling Reduces Manual Effort

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Automating Alert Handling Reduces Manual Effort

Static analysis tools search code for flaws without executing it providing alerts about flaws that cyber intruders might exploit as ***, those alerts require costly human effort to determine if they are true about tw... 详细信息

关键词： Vulnerability Coding Intrusion detection Software tools Computer programs Machine learning Algorithms java programming language Automating alert handling

Object race detection 01

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Object race detection

ACM SIGPLAN Conference on Object-oriented programming, Systems, languages, and Applications

作者： Christoph von Praun Thomas R. Gross Laboratory for Software Technology Department of Computer Scinece ETH Z?rich 8092 Z?rich Switzerland

ISBN: (纸本)1581133359

We present an on-the-fly mechanism that detects access conflicts in executions of multi-threaded java programs. Access conflicts are a conservative approximation of data races. The checker tracks access information at the level of objects (object races) rather than at the level of individual variables. This viewpoint allows the checker to exploit specific properties of object-oriented programs for optimization by restricting dynamic checks to those objects that are identified by escape analysis as potentially shared. The checker has been implemented in collaboration with an "ahead-of-time"java compiler. The combination fo static program analysis (escape-analysis) and inline instrumentation during code generation allows us to reduce the runtime overhead of detecting access conflicts. This overhead amounts to about 16-129% in time and less than 25% in space for typical benchmark applications and compares favorably to previously published on-the-fly mechanism that incurred an overhead of abouta factor of 2-80 in time and up to a factor of 2 in space.

关键词： checker Conflict (Psychology) Racial Stocks Code generation specific properties java java programming language program optimization Access

How Do java Developers Reuse StackOverflow Answers in Their GitHub Projects?

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arXiv 2023年

作者： Chen, Juntong Zhao, Yan Meng, Na Virginia Tech United States Eastern Michigan University United States

StackOverflow (SO) is a widely used question-and-answer (Q&A) website for software developers and computer scientists. GitHub is an online development platform used for storing, tracking, and collaborating on software projects. Prior work relates the information mined from both platforms to link user accounts or compare developers' activities across platforms. However, not much work is done to characterize the SO answers reused by GitHub projects. For this paper, we did an empirical study by mining the SO answers reused by java projects available on GitHub. We created a hybrid approach of clone detection, keyword-based search, and manual inspection, to identify the answer(s) actually leveraged by developers. Based on the identified answers, we further studied topics of the discussion threads, answer characteristics (e.g., scores, ages, code lengths, and text lengths), and developers' reuse practices. We observed that most reused answers offer programs to implement specific coding tasks. Among all analyzed SO discussion threads, the reused answers often have relatively higher scores, older ages, longer code, and longer text than unused answers. In only 9% of scenarios (40/430), developers fully copied answer code for reuse. In the remaining scenarios, they reused partial code or created brand new code from scratch. Our study characterized 130 SO discussion threads referred to by java developers in 357 GitHub projects. Our observations can guide SO answerers to provide better answers, and shed lights on future human-centric software engineering research that creates better tools to facilitate reliable and responsible code reuse. © 2023, CC BY.

关键词： java programming language

Performance and Energy Consumption Analysis of java Code utilizing Embedded GPU

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Performance and Energy Consumption Analysis of Java Code uti...

IEEE Canadian Conference on Electrical and Computer Engineering

作者： Iype P. Joseph Jonathan Parri Yu Wang Miodrag Bolic Amir Rajabzadeh Voicu Groza Computer Architecture Research Group EECS University of Ottawa Ottawa Canada Razi University Kermanshah Iran

ISBN: (纸本)9781479931026

GPUs and multicore CPUs are becoming common in today's embedded world of tablets and smartphones. With CPUs and GPUs getting more complex, maximizing hardware utilization and minimizing energy consumption are becoming problematic. The challenges faced in GPGPU computing on embedded platforms are different from their desktop counterparts due to the memory and computational limitations. This study evaluates the advantages of offloading java applications to an embedded GPU. By employing two approaches namely, java Native Interface (JNI-OpenCL) and java bindings for OpenCL (JOCL) we allowed programmers to program an embedded GPU from java. Experiments were conducted on a Freescale ***6Q SabreLite board which contains a quad-core ARM Cortex A9 CPU and a Vivante GC 2000 GPU that supports the OpenCL 1.1 Embedded Profile. The results show up to an eight times increase in performance efficiency by consuming only one-third the energy compared to the CPU-only version of the java program. This paper demonstrates the performance and energy benefits achieved by offloading java programs onto an embedded GPU. To the best of our knowledge, this is the first work involving java acceleration on embedded GPUs.

关键词： java java programming language GRAPPER PICK UP Graphics Processing Unit central processing units embedding energy consumption energy consumption analysis Smartphone Computer personnel embedded platform

Using Knowledge Units of programming languages to Recommend Reviewers for Pull Requests: An Empirical Study

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arXiv 2023年

作者： Ahasanuzzaman, Md Oliva, Gustavo A. Hassan, Ahmed E. School of Computing Queen’s University KingstonON Canada

Code review is a key element of quality assurance in software development. Determining the right reviewer for a given code change requires understanding the characteristics of the changed code, identifying the skills of each potential reviewer (expertise profile), and finding a good match between the two. To facilitate this task, we design a code reviewer recommender that operates on the knowledge units (KUs) of a programming language. We define a KU as a cohesive set of key capabilities that are offered by one or more building blocks of a given programming language. We operationalize our KUs using certification exams for the java programming language. We detect KUs from 10 actively maintained java projects from GitHub, spanning 290K commits and 65K pull requests (PRs). Next, we generate developer expertise profiles based on the detected KUs. Finally, these KU-based expertise profiles are used to build a code reviewer recommender (KUREC). The key assumption of KUREC is that the code reviewers of a given PR should be experts in the KUs that appear in the changed files of that PR. In RQ1, we compare KUREC’s performance to that of four baseline recommenders: (i) a commit-frequency-based recommender (CF), (ii) a review-frequency-based recommender (RF), (iii) a modification-expertise-based recommender (ER), and (iv) a review-history-based recommender (CHREV). We observe that KUREC performs as well as the top-performing baseline recommender (RF). From a practical standpoint, we highlight that KUREC’s performance is more stable (lower interquartile range) than that of RF, thus making it more consistent and potentially more trustworthy. Next, in RQ2 we design three new recommenders by combining KUREC with our baseline recommenders. These new combined recommenders outperform both KUREC and the individual baselines. Finally, in RQ3 we evaluate how reasonable the recommendations from KUREC and the combined recommenders are when those deviate from the ground truth. KUREC is the

关键词： java programming language

Visual Information Retrieval using java and LIRE 12

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Visual Information Retrieval using Java and LIRE

International ACM SIGIR Conference on Research & Development in Information Retrieval

作者： Oge Marques Mathias Lux Florida Atlantic University 777 Glades Road Boca Raton FL 33431 Klagenfurt University Universitaetsstrasse 65-67 Klagenfurt Austria

ISBN: (纸本)9781450320016

Visual information retrieval (VIR) is an active and vibrant research area, which attempts at providing means for organizing, indexing, annotating, and retrieving visual information (images and videos) form large, unstructured repositories. The goal of VIR is to retrieve the highest number of relevant matches to a given query (often expressed as an example image and/or a series of keywords). In its early years (1995-2000) the research efforts were dominated by content-based approaches contributed primarily by the image and video processing community. During the past decade, it was widely recognized that the challenges imposed by the semantic gap (the lack of coincidence between an image's visual contents and its semantic interpretation) required a clever use of textual metadata (in addition to information extracted from the image's pixel contents) to make image and video retrieval solutions efficient and effective. The need to bridge (or at least narrow) the semantic gap has been one of the driving forces behind current VIR research. Additionally, other related research problems and market opportunities have started to emerge, offering a broad range of exciting problems for computer scientists and engineers to work on. In this tutorial, we present an overview of visual information retrieval (VIR) concepts, techniques, algorithms, and applications. Several topics are supported by examples written in java, using Lucene (an open-source java-based indexing and search implementation) and LIRE (Lucene Image REtrieval), an open-source java-based library for content-based image retrieval (CBIR) written by Mathias Lux. After motivating the topic, we briefly review the fundamentals of information retrieval, present the most relevant and effective visual descriptors currently used in VIR, the most common indexing approaches for visual descriptors, the most prominent machine learning techniques used in connection with contemporary VIR solutions, as well as the challenges associa

关键词： Content-Based Image Retrieval Visual Information Retrieval Image Search java information retrieval java java programming language visual information images Tutorials Imagery (Psychotherapy) retrieval Semantic Interpretation Virgo Indexing Videotapes Research Problems content-based image retrieval market opportunities

An Empirical Study on Bug Severity Estimation using Source Code Metrics and Static Analysis

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arXiv 2022年

作者： Mashhadi, Ehsan Chowdhury, Shaiful Modaberi, Somayeh Hemmati, Hadi Uddin, Gias University of Calgary CalgaryAB Canada University of Manitoba WinnipegMB Canada York University TorontoON Canada

In the past couple of decades, significant research efforts have been devoted to the prediction of software bugs (i.e., defects). In general, these works leverage a diverse set of metrics, tools, and techniques to predict which classes, methods, lines, or commits are buggy. However, most existing work in this domain treats all bugs the same, which is not the case in practice. The more severe the bugs the higher their consequences. Therefore, it is important for a defect prediction method to estimate the severity of the identified bugs, so that the higher severity ones get immediate attention. In this paper, we provide a quantitative and qualitative study on two popular datasets (Defects4J and ***), using 10 common source code metrics, and two popular static analysis tools (SpotBugs and Infer) for analyzing their capability to predict defects and their severity. We studied 3,358 buggy methods with different severity labels from 19 java open-source projects. Results show that although code metrics are useful in predicting buggy code (Lines of the Code, Maintainable Index, FanOut, and Effort metrics are the best), they cannot estimate the severity level of the bugs. In addition, we observed that static analysis tools have weak performance in both predicting bugs (F1 score range of 3.1%-7.1%) and their severity label (F1 score under 2%). We also manually studied the characteristics of the severe bugs to identify possible reasons behind the weak performance of code metrics and static analysis tools in estimating their severity. Also, our categorization shows that Security bugs have high severity in most cases while Edge/Boundary faults have low severity. Finally, we discuss the practical implications of the results and propose new directions for future research. Copyright © 2022, The Authors. All rights reserved.

关键词： java programming language