| 1. |
- Bennin, Kwabena Ebo, et al.
(författare)
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An empirical study on the effectiveness of data resampling approaches for cross‐project software defect prediction
- 2022
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Ingår i: IET Software. - : John Wiley & Sons. - 1751-8806 .- 1751-8814. ; 16:2, s. 185-199
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Tidskriftsartikel (refereegranskat)abstract
- Cross‐project defect prediction (CPDP), where data from different software projects are used to predict defects, has been proposed as a way to provide data for software projects that lack historical data. Evaluations of CPDP models using the Nearest Neighbour (NN)Filter approach have shown promising results in recent studies. A key challenge with defect‐prediction datasets is class imbalance, that is, highly skewed datasets where nonbuggy modules dominate the buggy modules. In the past, data resampling approaches have been applied to within‐projects defect prediction models to help alleviate the negative effects of class imbalance in the datasets. To address the class imbalance issue in CPDP, the authors assess the impact of data resampling approaches on CPDP models after the NN Filter is applied. The impact on prediction performance of five oversampling approaches (MAHAKIL, SMOTE, Borderline‐SMOTE, Random Oversamplingand ADASYN) and three undersampling approaches (Random Undersampling, Tomek Links and One‐sided selection) is investigated and results are compared to approaches without data resampling. The authors examined six defect prediction models on34 datasets extracted from the PROMISE repository. The authors' results show that there is a significant positive effect of data resampling on CPDP performance, suggesting that software quality teams and researchers should consider applying data resampling approaches for improved recall (pd) and g‐measure prediction performance. However, if the goal is to improve precision and reduce false alarm (pf) then data resampling approaches should be avoided.
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| 2. |
- Felizardo, Katia Romero, et al.
(författare)
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Using visual text mining to support the study selection activity in systematic literature reviews
- 2011
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Ingår i: 2011 Fifth International Symposium on Empirical Software Engineering and Measurement, ESEM 2011. - Washington : IEEE. - 9781457722035 - 9780769546049 ; , s. 77-86
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Konferensbidrag (refereegranskat)abstract
- Background: A systematic literature review (SLR) is a methodology used to aggregate all relevant existing evidence to answer a research question of interest. Although crucial, the process used to select primary studies can be arduous, time consuming, and must often be conducted manually.Objective: We propose a novel approach, known as 'Systematic Literature Review based on Visual Text Mining' or simply SLR-VTM, to support the primary study selection activity using visual text mining (VTM) techniques. Method: We conducted a case study to compare the performance and effectiveness of four doctoral students in selecting primary studies manually and using the SLR-VTM approach. To enable the comparison, we also developed a VTM tool that implemented our approach. We hypothesized that students using SLR-VTM would present improved selection performance and effectiveness.Results: Our results show that incorporating VTM in the SLR study selection activity reduced the time spent in this activity and also increased the number of studies correctly included.Conclusions: Our pilot case study presents promising results suggesting that the use of VTM may indeed be beneficial during the study selection activity when performing an SLR.
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| 3. |
- Klünder, Jil, et al.
(författare)
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Catching up with Method and Process Practice: An Industry-Informed Baseline for Researchers
- 2019
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Ingår i: Proceedings - 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice, ICSE-SEIP 2019. ; May 2019, s. 255-264
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Konferensbidrag (refereegranskat)abstract
- Software development methods are usually not applied by the book.companies are under pressure to continuously deploy software products that meet market needs and stakeholders' requests. To implement efficient and effective development processes, companies utilize multiple frameworks, methods and practices, and combine these into hybrid methods. A common combination contains a rich management framework to organize and steer projects complemented with a number of smaller practices providing the development teams with tools to complete their tasks. In this paper, based on 732 data points collected through an international survey, we study the software development process use in practice. Our results show that 76.8% of the companies implement hybrid methods.company size as well as the strategy in devising and evolving hybrid methods affect the suitability of the chosen process to reach company or project goals. Our findings show that companies that combine planned improvement programs with process evolution can increase their process' suitability by up to 5%.
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| 4. |
- Klünder, Jil, et al.
(författare)
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Determining context factors for hybrid development methods with trained models
- 2020
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Ingår i: Proceedings - 2020 IEEE/ACM International Conference on Software and System Processes, ICSSP 2020. - New York, NY, USA : ACM.
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Konferensbidrag (refereegranskat)abstract
- © 2020 ACM. Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. Every project is unique and, thus, many context factors have to be considered. Recent research took some initial steps towards statistically constructing hybrid development methods, yet, paid little attention to the peculiarities of context factors influencing method and practice selection. In this paper, we utilize exploratory factor analysis and logistic regression analysis to learn such context factors and to identify methods that are correlated with these factors. Our analysis is based on 829 data points from the HELENA dataset. We provide five base clusters of methods consisting of up to 10 methods that lay the foundation for devising hybrid development methods. The analysis of the five clusters using trained models reveals only a few context factors, e.g., project/product size and target application domain, that seem to significantly influence the selection of methods. An extended descriptive analysis of these practices in the context of the identified method clusters also suggests a consolidation of the relevant practice sets used in specific project contexts.
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| 5. |
- Kuhrmann, Marco, et al.
(författare)
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Walking through the method zoo: Does higher education really meet software industry demands?
- 2019
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Ingår i: Proceedings - 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering Education and Training, ICSE-SEET 2019. - : IEEE. ; , s. 1-11
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Konferensbidrag (refereegranskat)abstract
- Software engineering educators are continually challenged by rapidly evolving concepts, technologies, and industry demands. Due to the omnipresence of software in a digitalized society, higher education institutions (HEIs) have to educate the students such that they learn how to learn, and that they are equipped with a profound basic knowledge and with latest knowledge about modern software and system development. Since industry demands change constantly, HEIs are challenged in meeting such current and future demands in a timely manner. This paper analyzes the current state of practice in software engineering education. Specifically, we want to compare contemporary education with industrial practice to understand if frameworks, methods and practices for software and system development taught at HEIs reflect industrial practice. For this, we conducted an online survey and collected information about 67 software engineering courses. Our findings show that development approaches taught at HEIs quite closely reflect industrial practice. We also found that the choice of what process to teach is sometimes driven by the wish to make a course successful. Especially when this happens for project courses, it could be beneficial to put more emphasis on building learning sequences with other courses.
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| 6. |
- Tanveer, Awais, et al.
(författare)
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Designing Actively Secure, Highly Available Industrial Automation Applications
- 2019
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Ingår i: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). - : IEEE. ; , s. 374-379
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Programmable Logic Controllers (PLCs) execute critical control software that drives Industrial Automation and Control Systems (IACS). PLCs can become easy targets for cyber-adversaries as they are resource-constrained and are usually built using legacy, less-capable security measures. Security attacks can significantly affect system availability, which is an essential requirement for IACS. We propose a method to make PLC applications more security-aware. Based on the well-known IEC 61499 function blocks standard for developing IACS software, our method allows designers to annotate critical parts of an application during design time. On deployment, these parts of the application are automatically secured using appropriate security mechanisms to detect and prevent attacks. We present a summary of availability attacks on distributed IACS applications that can be mitigated by our proposed method. Security mechanisms are achieved using IEC 61499 Service-Interface Function Blocks (SIFBs) embedding Intrusion Detection and Prevention System (IDPS), added to the application at compile time. This method is more amenable to providing active security protection from attacks on previously unknown (zero-day) vulnerabilities. We test our solution on an IEC 61499 application executing on Wago PFC200 PLCs. Experiments show that we can successfully log and prevent attacks at the application level as well as help the application to gracefully degrade into safe mode, subsequently improving availability.
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