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international conference on the Quality of Information and Communications Technology (QUATIC)

作者： Fabian Kortum Jil Klünder Software Engineering Group Leibniz Universität Hannover Hannover Germany

ISBN: (纸本)9781509035823

Effective team communication is a prerequisite for software quality and project success. It implies correctly elicited customer requirements, conduction of occurring change requests and to adhere releases. Team communication is a complex construct that consists of numerous characteristics, individual styles, influencing factors and dynamic intensities during a project. these elements are complicated to be measured or scheduled, especially in newly formed teams. According to software developers with few experiences in teams, it would be highly desirable to recognize dysfunctional or underestimated communication behaviors already in early project phases. Otherwise, negative affects may cause delay of releases or even endanger software quality. We introduce an approach on the feasibility of forecasting team's communication behavior in student software projects. We build a very first forecasting model that involves software engineering and industrial psychological terms to extract multi week communication forecasts with accurate results. the model consists of a k-nearest neighbor machine learning algorithm and is trained and evaluated with 34 student software projects from a previously taken field study. this study is an encouraging first step towards forecasting team communication to reveal potential miscommunications during a project. It is our aim to give young software developing teams an experience-based assistance about their information flow and enable adjustment for dysfunctional communication, to avoid fire fighting situation or even risks of alternating software qualities.

关键词： predictive models Data models Forecasting software engineering software quality Psychology

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Extending Survivability models for Global software Development with Media Synchronicity theory 10

Extending Survivability Models for Global Software Developme...

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10th IEEE international conference on Global software engineering (ICGSE)

作者： Avritzer, Alberto Beecham, Sarah Britto, Ricardo Kroll, Josiane Menasche, Daniel S. Noll, John Paasivaara, Maria Siemens Corp Corp Technol Princeton NJ 08540 USA Lero Irish Software Engn Res Ctr Limerick Ireland Blekinge Inst Technol Karlskrona Sweden Pontificia Univ Catolica Rio Grande do Sul Porto Alegre RS Brazil Univ Fed Rio de Janeiro BR-21941 Rio De Janeiro RJ Brazil Aalto Univ Helsinki Finland

ISBN: (纸本)9781479984091

In this paper we propose a new framework to assess survivability of software projects accounting for media capability details as introduced in Media Synchronicity theory (MST). Specifically, we add to our global engineering framework the assessment of the impact of inadequate conveyance and convergence available in the communication infrastructure selected to be used by the project, on the system ability to recover from project disasters. We propose an analytical model to assess how the project recovers from project disasters related to process and communication failures. Our model is based on media synchronicity theory to account for how information exchange impacts recovery. then, using the proposed model we evaluate how different interventions impact communication effectiveness. Finally, we parameterize and instantiate the proposed survivability model based on a data gathering campaign comprising thirty surveys collected from senior global software development experts at ICGSE' 2014 and GSD' 2015.

关键词： media synchronicity theory survivability

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Information leak detection in business process models: theory, application, and tool support

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INFORMATION SYSTEMS 2015年第0期47卷 244-257页

作者： Accorsi, Rafael Lehmann, Andreas Lohmann, Niels Univ Freiburg Dept Telemat D-79098 Freiburg Germany Univ Rostock Inst Informat D-18051 Rostock Germany

Despite the correct deployment of access control mechanisms, information leaks can persist and threaten the reliability of business process execution. this paper presents an automated and effective approach for the verification of information flow control for business process models. Building on the concept of place-based non-interference and declassification, the core contribution of this paper is the application of Petri net reachability to detect places in which information leaks occur. Such a feature allows for the use of state-of-the-art tool support to model-check business process models and detect leaks. We show that the approach is sound and complete, and present the Anica tool to identify leaks. An extensive evaluation comprising over 550 industrial process models is carried out and shows that information flow analysis of process models can be done in milliseconds. this motivates a tight integration of business process modeling and non-interference checking. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Business process security software and process engineering Automated analysis

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Towards Gamification in software Traceability: Between Test and Code Artifacts 10

Towards Gamification in Software Traceability: Between Test ...

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10th international conference on software Technologies (ICSOFT)

作者： Parizi, Reza Meimandi Kasem, Asem Abdullah, Azween Taylors Univ Sch Comp & IT Subang Jaya 47500 Selangor Malaysia

ISBN: (纸本)9789897581397

With the ever-increasing dependence of our civil and social infrastructures to the correct functioning of software systems, the need for approaches to engineer reliable and validated software systems grows rapidly. Traceability is the ability to trace the influence of one software artifact on another by linking dependencies. Test-to-code traceability (relationships between test and system code) plays a vital role in the production, verification, reliability and certification of highly software-intensive dependable systems. Prior work on test-to-code traceability in contemporary software engineering environments and tools is not satisfactory and is limited with respect to the need regarding results accuracy, lack of motivation, and high required effort by developers/testers. this paper argues that a new research is necessary to tackle the above weaknesses. thus, it advocates for the induction of gamification concepts in software traceability, and takes a position that the use of gamificaiton metrics can contribute to software traceability tasks in validating software and critical systems. We propose a research agenda to execute this position by providing a unifying foundation for gamified software traceability that combines self-adaptive, visualization, and predictive features for trace links.

关键词： software Traceability software Testing Validation Gamification Reliability

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What is the impact of imbalance on software defect prediction performance? 15

What is the impact of imbalance on software defect predictio...

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11th international conference on predictive models and Data Analytics in software engineering, promise 2015

作者： Mahmood, Zaheed Bowes, David Lane, Peter C.R. Hall, Tracy School of Technology Research Institute Hatfield HertfordshireAL10 9AB United Kingdom Dept. of Computer Science Brunel University Uxbridge Middlesex LondonUB8 3PH United Kingdom

ISBN: (纸本)9781450337151

software defect prediction performance varies over a large range. Menzies suggested there is a ceiling effect of 80% Recall [8]. Most of the data sets used are highly imbalanced. this paper asks, what is the empirical effect of using different datasets with varying levels of imbalance on predictive performance? We use data synthesised by a previous meta-analysis of 600 fault prediction models and their results. Four model evaluation measures (the Mathews Correlation Coeficient (MCC), F-Measure, Precision and Re- call ) are compared to the corresponding data imbalance ratio. When the data are imbalanced, the predictive performance of software defect prediction studies is low. As the data become more balanced, the predictive performance of prediction models increases, from an average MCC of 0.15, until the minority class makes up 20% of the instances in the dataset, where the MCC reaches an average value of about 0.34. As the proportion of the minority class increases above 20%, the predictive performance does not significantly increase. Using datasets with more than 20% of the instances being defective has not had a significant impact on the predictive performance when using MCC. We conclude that comparing the results of defect prediction studies should take into account the imbalance of the data. © 2015 ACM.

关键词： Forecasting

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An empirical study on predicting defect numbers 27

An empirical study on predicting defect numbers

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27th international conference on software engineering and Knowledge engineering, SEKE 2015

作者： Chen, Mingming Ma, Yutao State Key Laboratory of Software Engineering Wuhan University Wuhan430072 China School of Computer Wuhan University Wuhan430072 China WISET Automation Co. Ltd. Wuhan Iron and Steel Group Corporation Wuhan430080 China

ISBN: (纸本)1891706373

Defect prediction is an important activity to make software testing processes more targeted and efficient. Many methods have been proposed to predict the defect-proneness of software components using supervised classification techniques in within- and cross-project scenarios. However, very few prior studies address the above issue from the perspective of predictive analytics. How to make an appropriate decision among different prediction approaches in a given scenario remains unclear. In this paper, we empirically investigate the feasibility of defect numbers prediction with typical regression models in different scenarios. the experiments on six open-source software projects in promise repository show that the prediction model built with Decision Tree Regression seems to be the best estimator in both of the scenarios, and that for all the prediction models, the results yielded in the cross-project scenario can be comparable to (or sometimes better than) those in the within-project scenario when choosing suitable training data. therefore, the findings provide a useful insight into defect numbers prediction for those new and inactive projects.

关键词： predictive analytics

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Interoperable data models for infrastructural artefacts - A novel IFC extension method using RDF vocabularies exemplified with quay wall structures for harbors

Interoperable data models for infrastructural artefacts - A ...

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10th European conference on Product and Process Modelling, ECPPM 2014

作者： Beetz, J. Coebergh Van Den Braak, W. Botter Eindhoven, R. Zlatanova, S. De Laat, R. University of Technology Eindhoven Netherlands Delft University of Technology Delft Netherlands Logic Labs. The Hague Netherlands

ISBN: (纸本)9781138027107

Currently, only a limited number of dedicated data models for infrastructural artefacts exist. To cover information exchange and interoperability requirements, a number of international initiatives have been started under the umbrella of the buildingSMART organization to extend the predominant IFC model. In this paper, we are introducing a light-weight approach that allows the flexible extension of the IFC model with RDF vocabularies and ontologies. Using real-world quay wall models from the port of Rotterdam we show how information from multiple networked data sources can be seamlessly integrated with IFC models as the main carrier of geometric representation. We demonstrate how these semantically enriched models can be used with unmodified legacy software systems to facilitate a number of interoperability scenarios throughout different lifecycle phases. © 2015 Taylor & Francis Group.

关键词： Interoperability

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Extending Survivability models for Global software Development with Media Synchronicity theory

Extending Survivability Models for Global Software Developme...

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international conference on Global software engineering (ICGSE)

作者： Alberto Avritzer Sarah Beecham Ricardo Britto Josiane Kroll Daniel Sadoc Menasche John Noll Maria Paasivaara Siemens Corporation Corporate Technology Princeton NJ Lero Irish Software Engineering Research Centre Limerick Ireland Blekinge Institute of Technology Karlskrona Sweden PUCRS Porto Alegre RS Brazil Federal University of Rio de Janeiro Brazil Aalto University Helsinki Finland

关键词： Media software Convergence Cultural differences software engineering Global communication Analytical models

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Mitigating insider threats in a cloud using a knowledgebase approach while maintaining data availability

Mitigating insider threats in a cloud using a knowledgebase ...

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international conference for Internet Technology and Secured Transactions (ICITST)

作者： Qutaibah Althebyan Rami Mohawesh Qussai Yaseen Yaser Jararweh Software Engineering Department Jordan University of Science and Technology Irbid Jordan Computer Department Science Jordan University of Science and Technology Irbid Jordan Jordan University of Science and Technology Irbid Jordan

ISBN: (纸本)9781467383370

Most security related research for cloud computing focuses on attacks generated outside the cloud system. However, insider attackers are more challenging and can cause severe impacts on the cloud system stability and quality of service. In this paper, we propose an insider threat model using a knowledgebase approach. Knowledgebase models were used earlier in preventing insider threats in both the system level and the database level. We extend this work to cloud computing systems. the proposed model insures an early detection (and hence, the prevention) of possible insider breaches by correlating system administrators knowledge who may grant undesired privileges to insiders of the underlying cloud data center. the proposed model handles the insider threat in a cloud data center at its several levels: the host level and the network level where insiders are categorized several levels of privileges according to their locations within the cloud data center. the concentration will be insider threats at the host (database) level. the conducted simulation shows that the proposed model works well in predicting malicious acts of insiders of the cloud.

关键词： Cloud computing Databases Computational modeling Data models Security Knowledge engineering predictive models

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Mining Shoppers Data Streams to Predict Customers Loyalty

Mining Shoppers Data Streams to Predict Customers Loyalty

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international conference on Intelligent System and Knowledge engineering, ISKE

作者： Vladimir Nikulin Tian-Hsiang Huang Jian-De Lu Department of Mathematical Methods in Economy Vyatka State University Kirov Russia Cloud Computing Research Center National Sun Yat-Sen University Kaohsiung City Taiwan Department of Business Management National Sun Yat-Sen University Kaohsiung City Taiwan

For a consumer brand, the most valuable customers are those who return after this purchase. therefore, we want to know if it is possible to predict which shoppers will buy a new item with enough purchase history. Fortunately, while dealing with Big Data and with data streams in particular, it is a common practice to summarize or aggregate customers' transaction history to the periods of few months. As an outcome, we compress the given huge volume of data, and transfer the data stream to the standard rectangular format. Consequently, we can explore a variety of practically or theoretically motivated tasks. For example, we can rank the given field of customers in accordance to their loyalty or intension to repurchase in the near future. this objective has very important practical application. It leads to preferential treatment of the right customers. We tested our model (with competitive results) online during Kaggle-based Acquire Valued Shoppers Challenge in 2014.

关键词： Companies Data mining History predictive models Databases Smoothing methods

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