2022 IEEE/ACM International Conference on Technical Debt (TechDebt)最新文献

PILOT: Synergy between Text Processing and Neural Networks to Detect Self-Admitted Technical Debt 试点:文本处理和神经网络之间的协同作用，以检测自我承认的技术债务

2022 IEEE/ACM International Conference on Technical Debt (TechDebt) Pub Date : 2022-05-01 DOI: 10.1145/3524843.3528093

A. D. Salle, Alessandra Rota, Phuong T. Nguyen, D. D. Ruscio, F. Fontana, Irene Sala

{"title":"PILOT: Synergy between Text Processing and Neural Networks to Detect Self-Admitted Technical Debt","authors":"A. D. Salle, Alessandra Rota, Phuong T. Nguyen, D. D. Ruscio, F. Fontana, Irene Sala","doi":"10.1145/3524843.3528093","DOIUrl":"https://doi.org/10.1145/3524843.3528093","url":null,"abstract":"During the development phase, software programmers usually introduce code that contains issues intentionally left for additional treatment. To allow for future fixing, they mark such code using textual comments, resulting in Self-Admitted Technical Debt (SATD). Detecting SATD contained in source code has become crucial in the development cycle since it helps program-mers locate issues that need to be solved, thus improving code quality. We introduce PILOT, a technical debt detector built on top of a combination of different natural language processing (NLP) and machine learning (ML) techniques. First, the semantic among SATD comments is captured using feature extraction steps. Then, neural network algorithms are applied to classify comments, represented as vectors. We built a PILOT prototype with a feed-forward neural network and evaluated it using real-world datasets as proof of concept. The empirical evaluation shows that PILOT obtains an encouraging performance and outperforms a well-established baseline. We anticipate that our tool will come in handy, as once being embedded in the IDE, it can help developers recognize SATD manifested in their code, allowing them to conveniently identify and fix issues.","PeriodicalId":149335,"journal":{"name":"2022 IEEE/ACM International Conference on Technical Debt (TechDebt)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128622646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Towards measuring the aggregated debt of Trustworthiness level 论信用水平综合债务的测度

2022 IEEE/ACM International Conference on Technical Debt (TechDebt) Pub Date : 2022-05-01 DOI: 10.1145/3524843.3528090

Imanol Urretavizcaya, Nuria Quintano, Jabier Martinez

{"title":"Towards measuring the aggregated debt of Trustworthiness level","authors":"Imanol Urretavizcaya, Nuria Quintano, Jabier Martinez","doi":"10.1145/3524843.3528090","DOIUrl":"https://doi.org/10.1145/3524843.3528090","url":null,"abstract":"The management of technical debt related to non-functional properties such as security, reliability or other trustworthiness dimensions is of paramount importance for critical systems (e.g., safety-critical, systems with strong privacy constraints etc.). Unfortunately, diverse factors such as time pressure, resource limitations, organizational aspects, lack of skills, or the fast pace at which new risks appears, can result in an inferior level of trustworthiness than the desired or required one. In addition, there is increased interest in considering trustworthiness characteristics, not in isolation, but in an aggregated fashion, as well as using this knowledge for risk quantification. In this work, we propose a trustworthiness debt measurement approach using 1) established categories and subcategories of trustworthiness characteristics from SQuaRE, 2) a weighting approach for the characteristics based on an AHP method, 3) a composed indicator based on a Fuzzy method, and 4) a risk management and analysis support based on Monte Carlo simulations. Given the preliminary nature of this work, while we propose the general approach for all trustworthiness dimensions, we elaborate more on security and reliability. This initial proposal aims providing a practical approach to manage trustworthiness debt suitable for any life cycle phase and bringing the attention to aggregation methods.","PeriodicalId":149335,"journal":{"name":"2022 IEEE/ACM International Conference on Technical Debt (TechDebt)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128853257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sonarlizer Xplorer: a tool to mine Github projects and identify technical debt items using SonarQube Sonarlizer explorer:一个使用SonarQube挖掘Github项目和识别技术债务项的工具

2022 IEEE/ACM International Conference on Technical Debt (TechDebt) Pub Date : 2022-05-01 DOI: 10.1145/3524843.3528098

Diogo Pina, A. Goldman, C. Seaman

引用次数: 4

TD Classifier: Automatic Identification of Java Classes with High Technical Debt TD Classifier:具有高技术债务的Java类的自动识别

2022 IEEE/ACM International Conference on Technical Debt (TechDebt) Pub Date : 2022-05-01 DOI: 10.1145/3524843.3528094

D. Tsoukalas, A. Chatzigeorgiou, Apostolos Ampatzoglou, N. Mittas, Dionisis D. Kehagias

{"title":"TD Classifier: Automatic Identification of Java Classes with High Technical Debt","authors":"D. Tsoukalas, A. Chatzigeorgiou, Apostolos Ampatzoglou, N. Mittas, Dionisis D. Kehagias","doi":"10.1145/3524843.3528094","DOIUrl":"https://doi.org/10.1145/3524843.3528094","url":null,"abstract":"To date, the identification and quantification of Technical Debt (TD) rely heavily on a few sophisticated tools that check for violations of certain predefined rules, usually through static analysis. Different tools result in divergent TD estimates calling into question the reliability of findings derived by a single tool. To alleviate this issue, we present a tool that employs machine learning on a dataset built upon the convergence of three widely-adopted TD Assessment tools to automatically assess the class-level TD for any arbitrary Java project. The proposed tool is able to classify software classes as high-TD or not, by synthesizing source code and repository ac-tivity information retrieved by employing four popular open source analyzers. The classification results are combined with proper vi-sualization techniques, to enable the identification of classes that are more likely to be problematic. To demonstrate the proposed tool and evaluate its usefulness, a case study is conducted based on a real-world open-source software project. The proposed tool is expected to facilitate TD management activities and enable fur-ther experimentation through its use in an academic or industrial setting. Video: https://youtu.be/umgXU8u7lIA Running Instance: http://160.40.52.130:3000/tdclassifier Source Code: https://gitlab.seis.iti.gr/root/td-classifier.git","PeriodicalId":149335,"journal":{"name":"2022 IEEE/ACM International Conference on Technical Debt (TechDebt)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114248258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

MultiDimEr : A Multi-Dimensional bug analyzEr MultiDimEr:一个多维错误分析器

2022 IEEE/ACM International Conference on Technical Debt (TechDebt) Pub Date : 2022-05-01 DOI: 10.1145/3524843.3528099

Lakmal Silva, M. Unterkalmsteiner, K. Wnuk

{"title":"MultiDimEr : A Multi-Dimensional bug analyzEr","authors":"Lakmal Silva, M. Unterkalmsteiner, K. Wnuk","doi":"10.1145/3524843.3528099","DOIUrl":"https://doi.org/10.1145/3524843.3528099","url":null,"abstract":"Background: Bugs and bug management consumes a significant amount of time and effort from software development organizations. A reduction in bugs can significantly improve the capacity for new feature development. Aims: We categorize and visualize dimensions of bug reports to identify accruing technical debt. This evidence can serve practitioners and decision makers not only as an argumentative basis for steering improvement efforts, but also as a starting point for root cause analysis, reducing overall bug inflow. Method: We implemented a tool, MultiDimEr, that analyzes and visualizes bug reports. The tool was implemented and evaluated at Ericsson. Results: We present our preliminary findings using the MultiDimEr for bug analysis, where we successfully identified components generating most of the bugs and bug trends within certain components. Conclusions: By analyzing the dimensions provided by MultiDimEr, we show that classifying and visualizing bug reports in different dimensions can stimulate discussions around bug hot spots as well as validating the accuracy of manually entered bug report attributes used in technical debt measurements such as fault slip through.","PeriodicalId":149335,"journal":{"name":"2022 IEEE/ACM International Conference on Technical Debt (TechDebt)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116879258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Architecture Smell Knowledge Base for Managing Architecture Technical Debt 管理架构技术债务的架构嗅觉知识库

2022 IEEE/ACM International Conference on Technical Debt (TechDebt) Pub Date : 2022-05-01 DOI: 10.1145/3524843.3528092

Paula Rachow, Matthias Riebisch

引用次数: 1

Comprehending the Use of Intelligent Techniques to Support Technical Debt Management 理解使用智能技术来支持技术债务管理

2022 IEEE/ACM International Conference on Technical Debt (TechDebt) Pub Date : 2022-05-01 DOI: 10.1145/3524843.3528097

D. Albuquerque, Everton T. Guimarães, G. Tonin, M. Perkusich, H. Almeida, A. Perkusich

{"title":"Comprehending the Use of Intelligent Techniques to Support Technical Debt Management","authors":"D. Albuquerque, Everton T. Guimarães, G. Tonin, M. Perkusich, H. Almeida, A. Perkusich","doi":"10.1145/3524843.3528097","DOIUrl":"https://doi.org/10.1145/3524843.3528097","url":null,"abstract":"Technical Debt (TD) refers to the consequences of taking shortcuts when developing software. Technical Debt Management (TDM) becomes complex since it relies on a decision process based on multiple and heterogeneous data, which are not straightforward to be synthesized. In this context, there is a promising opportunity to use Intelligent Techniques to support TDM activities since these techniques explore data for knowledge discovery, reasoning, learning, or supporting decision-making. Although these techniques can be used for improving TDM activities, there is no empirical study exploring this research area. This study aims to identify and analyze solutions based on Intelligent Techniques employed to sup-port TDM activities. A Systematic Mapping Study was performed, covering publications between 2010 and 2020. From 2276 extracted studies, we selected 111 unique studies. We found a positive trend in applying Intelligent Techniques to support TDM activities, being Machine Learning, Reasoning Under Uncertainty, and Natu-ral Language Processing the most recurrent ones. Identification, measurement, and monitoring were the more recurrent TDM ac-tivities, whereas Design, Code, and Architectural were the most frequently investigated TD types. Although the research area is up-and-coming, it is still in its infancy, and this study provides a baseline for future research.","PeriodicalId":149335,"journal":{"name":"2022 IEEE/ACM International Conference on Technical Debt (TechDebt)","volume":"524 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133733590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Investigating the Point of View of Project Management Practitioners on Technical Debt - A Preliminary Study on Stack Exchange 项目管理从业者对技术债务的看法调查——堆栈交换的初步研究

2022 IEEE/ACM International Conference on Technical Debt (TechDebt) Pub Date : 2022-05-01 DOI: 10.1145/3524843.3528095

Felipe G. S. Gomes, Eder Pereira dos Santos, Sávio Freire, Manoel G. Mendonça, T. Mendes, R. Spínola

{"title":"Investigating the Point of View of Project Management Practitioners on Technical Debt - A Preliminary Study on Stack Exchange","authors":"Felipe G. S. Gomes, Eder Pereira dos Santos, Sávio Freire, Manoel G. Mendonça, T. Mendes, R. Spínola","doi":"10.1145/3524843.3528095","DOIUrl":"https://doi.org/10.1145/3524843.3528095","url":null,"abstract":"Context: Technical debt (TD) can bring short-term benefits to software projects, but its presence is also associated with is-sues such as decreasing product quality. Recent literature has proposed indicator-based strategies for TD identification and different approaches for TD management, but most of them focused on the point of view of software developers. Little is still known about how project management practition-ers actually discuss, experience, and manage TD. Goal: This work investigates, from the point of view of project manage-ment practitioners, how they commonly discuss, experience, and manage TD. Method: We mined, curated, and selected a total of 42 TD discussions on Stack Exchange Project Man-agement (SEPM), totaling 583 messages. We analyzed this data set quantitatively and qualitatively. Results: The most commonly discussed types of debt are process and people, revealing 47 indicators for recognizing debt items. We also found 72 practices related to TD management. Conclusion: The perspective considered by project management practitioners to analyze the TD phenomenon is different from the one considered by other roles in the software development process. This work organizes the TD indicators and manage-ment practices identified in SEPM into a Sankey diagram, which may assist practitioners and serve as guidance for future research.","PeriodicalId":149335,"journal":{"name":"2022 IEEE/ACM International Conference on Technical Debt (TechDebt)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130559389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Technical Debt Prioritization: A Developer's Perspective 技术债务优先级:开发人员的视角

2022 IEEE/ACM International Conference on Technical Debt (TechDebt) Pub Date : 2022-05-01 DOI: 10.1145/3524843.3528096

Diogo Pina, C. Seaman, A. Goldman

{"title":"Technical Debt Prioritization: A Developer's Perspective","authors":"Diogo Pina, C. Seaman, A. Goldman","doi":"10.1145/3524843.3528096","DOIUrl":"https://doi.org/10.1145/3524843.3528096","url":null,"abstract":"Background: The prioritization of technical debt is an essen-tial task in managing software projects because, with current analysis tools, it is possible to find thousands of technical debt items in the software that would take months or even years to be fully paid. Aims: In this study, we aim to under-stand which criteria software developers use to prioritize code technical debt in real software projects. Methods: We performed a survey to collect data from open-source soft-ware projects in order to reach a large and diverse set of ex-periences. We analyzed the data using Straussian Grounded Theory techniques: open coding, axial coding, and selective coding. Results: We grouped the criteria into 15 categories and divided them into 2 super-categories related to paying off the technical debt and 3 related to not paying it. Conclusions: When participants decided to pay off technical debt, they wanted to do it soon. However, when they decided not to pay it, it is often because the debt occurred intentionally due to a project decision. Also, participants using similar criteria for their decisions tended to choose similar priority levels for those decisions. Finally, we observed that each software project needs to tailor the rules used to identify code technical debt to their project context.","PeriodicalId":149335,"journal":{"name":"2022 IEEE/ACM International Conference on Technical Debt (TechDebt)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129640263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Merging Smell Detectors: Evidence on the Agreement of Multiple Tools 合并气味探测器:关于多种工具一致性的证据

2022 IEEE/ACM International Conference on Technical Debt (TechDebt) Pub Date : 2022-05-01 DOI: 10.1145/3524843.3528089

Apostolos Ichtsis, N. Mittas, Apostolos Ampatzoglou, A. Chatzigeorgiou

{"title":"Merging Smell Detectors: Evidence on the Agreement of Multiple Tools","authors":"Apostolos Ichtsis, N. Mittas, Apostolos Ampatzoglou, A. Chatzigeorgiou","doi":"10.1145/3524843.3528089","DOIUrl":"https://doi.org/10.1145/3524843.3528089","url":null,"abstract":"Technical Debt estimation relies heavily on the use of static anal-ysis tools looking for violations of pre-defined rules. Largely, Technical Debt principal is attributed to the presence of low-level code smells, unavoidably tying the effort for fixing the problems with mere coding inefficiencies. At the same time, despite their simple definition, the detection of most code smells is non-trivial and subjective, rendering the assessment of Technical Debt prin-cipal dubious. To this end, we have revisited the literature on code smell detection approaches backed by tools and developed an Eclipse plugin that incorporates six code smell detection ap-proaches. The combined application of various smell detectors can increase the certainty of identifying actual code smells that matter to the development team. We also conduct a case study to investigate the agreement among the employed code smell detec-tors. To our surprise the level of agreement is quite low even for relatively simple code smells, threating the validity of existing TD analysis tools and calling for increased attention to the precise specification of code and design level issues. Source code: https://github.com/apostolisich/SmellDetectorMerger","PeriodicalId":149335,"journal":{"name":"2022 IEEE/ACM International Conference on Technical Debt (TechDebt)","volume":"916 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117059535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2