Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference最新文献

Cost-Effective Traceability Links for Architecture-Level Software Understanding: A Controlled Experiment 架构级软件理解的成本效益跟踪链接:一个受控实验

Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference Pub Date : 2015-09-28 DOI: 10.1145/2811681.2811695

M. Javed, S. Stevanetic, Uwe Zdun

{"title":"Cost-Effective Traceability Links for Architecture-Level Software Understanding: A Controlled Experiment","authors":"M. Javed, S. Stevanetic, Uwe Zdun","doi":"10.1145/2811681.2811695","DOIUrl":"https://doi.org/10.1145/2811681.2811695","url":null,"abstract":"An important architectural challenge is to recover traceability links between the software architecture and artifacts produced in the other activities of the development process, such as requirements, detailed design, architectural knowledge, and implementation. This is challenging because, on the one hand, it is desirable to recover traceability links of a high quality and at the right quantity for aiding the software architect or developer, but, on the other hand, the costs and efforts spent for recovering should be as low as possible. The literature suggests manual, semi-automatic, and automatic recovery methods, each of which exhibits different impacts on costs as well as quantity and quality of the recovered links. To date, however, none of the published empirical studies have comparatively examined the automation alternatives of traceability link recovery. This paper reports on a controlled experiment that was conducted to investigate how well typical results produced by the three automation alternatives support human software developers in architecture-level understanding of the software system. The results provide statistical evidence that a focus on automated information retrieval (IR) based traceability recovery methods significantly reduces the quantity and quality of the elements retrieved by the software developers, whereas no significant differences between manual and semi-automatic traceability link recovery were found.","PeriodicalId":292017,"journal":{"name":"Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference","volume":"299 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124278742","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: 4

Looking Closer at Compositional Symbolic Execution 仔细观察组合符号执行

Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference Pub Date : 2015-09-28 DOI: 10.1145/2811681.2817758

Yude Lin, Tim Miller

引用次数: 1

Performance Evaluation of Ensemble Methods For Software Fault Prediction: An Experiment 集成方法在软件故障预测中的性能评价:一个实验

Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference Pub Date : 2015-09-28 DOI: 10.1145/2811681.2811699

Shahid Hussain, J. Keung, A. Khan, K. E. Bennin

{"title":"Performance Evaluation of Ensemble Methods For Software Fault Prediction: An Experiment","authors":"Shahid Hussain, J. Keung, A. Khan, K. E. Bennin","doi":"10.1145/2811681.2811699","DOIUrl":"https://doi.org/10.1145/2811681.2811699","url":null,"abstract":"In object-oriented software development, a plethora of studies have been carried out to present the application of machine learning algorithms for fault prediction. Furthermore, it has been empirically validated that an ensemble method can improve classification performance as compared to a single classifier. But, due to the inherent differences among machine learning and data mining approaches, the classification performance of ensemble methods will be varied. In this study, we investigated and evaluated the performance of different ensemble methods with itself and base-level classifiers, in predicting the faults proneness classes. Subsequently, we used three ensemble methods AdaboostM1, Vote and StackingC with five base-level classifiers namely Naivebayes, Logistic, J48, VotedPerceptron and SMO in Weka tool. In order to evaluate the performance of ensemble methods, we retrieved twelve datasets of open source projects from PROMISE repository. In this experiment, we used k-fold (k=10) cross-validation and ROC analysis for validation. Besides, we used recall, precision, accuracy, F-value measures to evaluate the performance of ensemble methods and base-level Classifiers. Finally, we observed significant performance improvement of applying ensemble methods as compared to its base-level classifier, and among ensemble methods we observed StackingC outperformed other selected ensemble methods for software fault prediction.","PeriodicalId":292017,"journal":{"name":"Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131120926","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: 17

An Ontology-Based Multi-Agent System to Support Requirements Traceability in Multi-Site Software Development Environment 基于本体的多代理系统支持多站点软件开发环境中的需求可追溯性

Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference Pub Date : 2015-09-28 DOI: 10.1145/2811681.2811700

U. Pakdeetrakulwong, P. Wongthongtham, Naveed Khan

{"title":"An Ontology-Based Multi-Agent System to Support Requirements Traceability in Multi-Site Software Development Environment","authors":"U. Pakdeetrakulwong, P. Wongthongtham, Naveed Khan","doi":"10.1145/2811681.2811700","DOIUrl":"https://doi.org/10.1145/2811681.2811700","url":null,"abstract":"With the advent of the Internet, many software companies have adopted the multi-site software development approach that enables project team members to work across multiple sites. A globally dispersed project offers several advantages; however, it creates additional challenges in regard to communication, coordination and information sharing and can lead to the failure of software projects. We propose a conceptual architecture for an ontology-based multi-agent system to provide active support to access software engineering domain knowledge and to recommend software development project captured in the Software Engineering Ontology. The Software Engineering Ontology is used as a communication framework to enable knowledge sharing and reuse while the multi-agent provides the autonomy and the reactive and proactive features to the multi-site software development environment. In this paper we focus on utilizing the proposed framework to support automated requirements traceability tasks. When there is a change in requirement, software agents work cooperatively to trace and identify potentially affected software artifacts and notify the relevant team members to make them aware of any changes.","PeriodicalId":292017,"journal":{"name":"Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128146355","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: 4

Designing a Mobile Digital Backchannel System for Monitoring Sentiments and Emotions in Large Lectures 大型讲座中情绪和情绪监测的移动数字反向通道系统设计

Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference Pub Date : 2015-09-28 DOI: 10.1145/2811681.2824994

P. Jiranantanagorn, Parveen Bhardwaj, Ruilun Li, Haifeng Shen, R. Goodwin, Kung-Keat Teoh

引用次数: 0

Threshold-based prediction of schedule overrun in software projects 基于阈值的软件项目进度超支预测

Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference Pub Date : 2015-09-28 DOI: 10.1145/2811681.2811697

Morakot Choetkiertikul, K. Dam, A. Ghose

{"title":"Threshold-based prediction of schedule overrun in software projects","authors":"Morakot Choetkiertikul, K. Dam, A. Ghose","doi":"10.1145/2811681.2811697","DOIUrl":"https://doi.org/10.1145/2811681.2811697","url":null,"abstract":"Risk identification is the first critical task of risk management for planning measures to deal with risks. While, software projects have a high risk of schedule overruns, current practices in risk management mostly rely on high level guidance and the subjective judgements of experts. In this paper, we propose a novel approach to support risk identification using historical data associated with a software project. Specifically, our approach identifies patterns of abnormal behaviours that caused project delays and uses this knowledge to develop an interpretable risk predictive model to predict whether current software tasks (in the form of issues) will cause a schedule overrun. The abnormal behaviour identification is based on a set of configurable threshold-based risk factors. Our approach aims to provide not only predictive models, but also an interpretable outcome that can be inferred as the patterns of the combinations between risk factors. The evaluation results from two case studies (Moodle and Duraspace) demonstrate the effectiveness of our predictive models, achieving 78% precision, 56% recall, 65% F-measure, 84% Area Under the ROC Curve.","PeriodicalId":292017,"journal":{"name":"Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126963393","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

Spatio-Temporal Architecture-Based Framework for Testing Services in the Cloud 基于时空架构的云服务测试框架

Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference Pub Date : 2015-09-28 DOI: 10.1145/2811681.2811685

Huai Liu, M. Spichkova, H. Schmidt, T. Sellis, M. Duckham

引用次数: 5

An Aspect-Oriented Feature Modelling Framework for Software Product Line Engineering 面向方面的软件产品线工程特征建模框架

Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference Pub Date : 2015-09-28 DOI: 10.1145/2811681.2811703

Lei Tan, Yuqing Lin

引用次数: 3

Examining Value-Based Factors in Software Development: A Survey Study in Malaysian Public Sector 检视软件开发中基于价值的因素:马来西亚公共部门的调查研究

Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference Pub Date : 2015-09-28 DOI: 10.1145/2811681.2811684

N. A. Zakaria, S. Ibrahim, M. N. Mahrin

{"title":"Examining Value-Based Factors in Software Development: A Survey Study in Malaysian Public Sector","authors":"N. A. Zakaria, S. Ibrahim, M. N. Mahrin","doi":"10.1145/2811681.2811684","DOIUrl":"https://doi.org/10.1145/2811681.2811684","url":null,"abstract":"Software development plays a major role in the production of software products. This process must be carefully designed in order to successfully deliver the end product, and at the same time fulfill the values desired. Value-Based Software Engineering (VBSE) aims to convert the value-neutral setting in developing software to become a more value-centric approach. This study presents exploratory survey results for the purpose of examining value-based factors that are most commonly used in software development. The survey conducted at the Malaysian public sector involving a software development team as the target population. Exploratory factor analysis was used as the main data analysis strategy in this study. The results reveal that there are 28 value-based factors that are most commonly used in software development which can be classified into four classifications (success-critical stakeholders, business strategy, project characteristics and product characteristics). Our objective in further research is to develop value-based factors profile as imperative input to conduct software process tailoring.","PeriodicalId":292017,"journal":{"name":"Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129206588","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

Distributed Open Source Software-Defined GPS 分布式开源软件定义的GPS

Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference Pub Date : 2015-09-28 DOI: 10.1145/2811681.2811690

A. D. Arnold, K. Bialkowski

引用次数: 2