| 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. |
- Bennin, Kwabena Ebo, 1987-, et al.
(författare)
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Revisiting the Impact of Concept Drift on Just-in-Time Quality Assurance
- 2020
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Ingår i: Proceedings - 2020 IEEE 20th International Conference on Software Quality, Reliability, and Security, QRS 2020. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728189130 ; , s. 53-59
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Konferensbidrag (refereegranskat)abstract
- The performance of software defect prediction(SDP) models is known to be dependent on the datasets used for training the models. Evolving data in a dynamic software development environment such as significant refactoring and organizational changes introduces new concept to the prediction model, thus making improved classification performance difficult. In this study, we investigate and assess the existence and impact of concept drift on SDP performances. We empirically asses the prediction performance of five models by conducting cross-version experiments using fifty-five releases of five open-source projects. Prediction performance fluctuated as the training datasets changed over time. Our results indicate that the quality and the reliability of defect prediction models fluctuate over time and that this instability should be considered by software quality teams when using historical datasets. The performance of a static predictor constructed with data from historical versions may degrade over time due to the challenges posed by concept drift. © 2020 IEEE.
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| 3. |
- Britto, Ricardo, 1982-, et al.
(författare)
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Evaluating and strategizing the onboarding of software developers in large-scale globally distributed projects
- 2020
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Ingår i: Journal of Systems and Software. - : Elsevier Inc.. - 0164-1212 .- 1873-1228. ; 169
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Tidskriftsartikel (refereegranskat)abstract
- The combination of scale and distribution in software projects makes the onboarding of new developers problematic. To the best of our knowledge, there is no research on the relationship between onboarding strategies and the performance evolution of newcomers in large-scale, globally distributed projects. Furthermore, there are no approaches to support the development of strategies to systematically onboard developers. In this paper, we address these gaps by means of an industrial case study. We identified that the following aspects seem to be related to the observed onboarding results: the distance to mentors, the formal training approach used, the allocation of large and distributed tasks in the early stages of the onboarding process, and team instability. We conclude that onboarding must be planned well ahead and should consider avoiding the aspects mentioned above. Based on the results of this investigation, we propose a process to strategize and evaluate onboarding. To develop the process, we used business process modeling. We conducted a static validation of the proposed process utilizing interviews with experts. The static validation of the process indicates that it can help companies to deal with the challenges associated with the onboarding of newcomers through more systematic, effective, and repeatable onboarding strategies. © 2020 Elsevier Inc.
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| 4. |
- Britto, Ricardo, 1982-, et al.
(författare)
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Learning and Performance Evolution of Immature Remote Teams in Large-ScaleSoftware Projects : An Industrial Case Study
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Context: Large-scale distributed software projects with long life cycles often involve a considerable amount ofcomplex legacy code. The combination of scale and distribution challenges, and the diculty to acquire knowledgeabout large amounts of complex legacy code may make the onboarding of new developers/teams problematic. Thismay lead to extended periods of low performance.Objective: The main objective of this paper is to analyze the learning processes and performance evolutions (teamproductivity and team autonomy) of remote software development teams added late to a large-scale legacy softwareproduct development, and to propose recommendations to support the learning of remote teams.Method: We conducted a case study in Ericsson, collecting data through archival research, semi-structured interviews,and workshops. We analyzed the collected data using descriptive, inferential and graphical statistics and softqualitative analysis.Results: The results show that the productivity and autonomy of immature remote teams are on average 3.67 and2.27 times lower than the ones of mature teams, respectively. Furthermore, their performance had a steady increaseduring almost the entire first year and dropped (productivity) or got stagnated (autonomy) for a great part of the secondyear. In addition to these results, we also identified four challenges that aected the learning process and performanceevolution of immature remote teams: complexity of the product and technology stack, distance to the main source ofproduct knowledge, lack of team stability, and training expectation misalignment.Conclusion: The results indicate that scale, distribution and complex legacy code may make learning more dicultand demand a long period to achieve high performance. To support the learning of remote teams, we put forward fiverecommendations. We believe that our quantitative analysis, as well as the identified factors and recommendationscan help other companies to onboard new remote teams in large-scale legacy product development projects.
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| 5. |
- Britto, Ricardo, 1982-, et al.
(författare)
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Performance Evolution of Newcomers in Large-Scale Distributed Software Projects : An Industrial Case Study
- 2019
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Ingår i: Proceedings - 2019 ACM/IEEE 14th International Conference on Global Software Engineering, ICGSE 2019. - : Institute of Electrical and Electronics Engineers Inc.. - 9781538691960 ; , s. 1-11
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Konferensbidrag (refereegranskat)abstract
- Large-scale distributed software projects with long life cycles often involve a considerable amount of complex legacy code. The combination of scale and distribution challenges and the difficulty in acquiring knowledge about massive amounts of complex legacy code may make the onboarding of new developers/teams problematic. These problems may lead to extended periods of low performance. The primary objective of this paper is to investigate the performance evolution of offshore newcomers onboarded in a large-scale globally distributed project and how it relates to the employed onboarding strategy. To achieve our objective, we conducted a case study in Ericsson. We identified that the following aspects in the onboarding strategy employed in the investigated case seem to be related to the unexpectedly low performance evolution: i) the distance to mentors; ii) the used formal training approach, which did not fit the sociocultural background of the newcomers; iii) allocation of large and distributed tasks in the early stages of the onboarding process; and iv) team instability. We conclude that the onboarding of newcomers in globally distributed projects must be planned well ahead and should consider avoiding the aspects mentioned above. © 2019 IEEE.
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| 6. |
- Börstler, Jürgen, 1960-, et al.
(författare)
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Acceptance behavior theories and models in software engineering — A mapping study
- 2024
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Ingår i: Information and Software Technology. - : Elsevier. - 0950-5849 .- 1873-6025. ; 172
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Forskningsöversikt (refereegranskat)abstract
- Context: The adoption or acceptance of new technologies or ways of working in software development activities is a recurrent topic in the software engineering literature. The topic has, therefore, been empirically investigated extensively. It is, however, unclear which theoretical frames of reference are used in this research to explain acceptance behaviors. Objective: In this study, we explore how major theories and models of acceptance behavior have been used in the software engineering literature to empirically investigate acceptance behavior.Method: We conduct a systematic mapping study of empirical studies using acceptance behavior theories in software engineering.Results: We identified 47 primary studies covering 56 theory uses. The theories were categorized into six groups. Technology acceptance models (TAM and its extensions) were used in 29 of the 47 primary studies, innovation theories in 10, and the theories of planned behavior/ reasoned action (TPB/TRA) in six. All other theories were used in at most two of the primary studies. The usage and operationalization of the theories were, in many cases, inconsistent with the underlying theories. Furthermore, we identified 77 constructs used by these studies of which many lack clear definitions. Conclusions: Our results show that software engineering researchers are aware of some of the leading theories and models of acceptance behavior, which indicates an attempt to have more theoretical foundations. However, we identified issues related to theory usage that make it difficult to aggregate and synthesize results across studies. We propose mitigation actions that encourage the consistent use of theories and emphasize the measurement of key constructs.
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| 7. |
- Börstler, Jürgen, 1960-, et al.
(författare)
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Developers talking about code quality
- 2023
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Ingår i: Empirical Software Engineering. - : Springer. - 1382-3256 .- 1573-7616. ; 28:6
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Tidskriftsartikel (refereegranskat)abstract
- There are many aspects of code quality, some of which are difficult to capture or to measure. Despite the importance of software quality, there is a lack of commonly accepted measures or indicators for code quality that can be linked to quality attributes. We investigate software developers’ perceptions of source code quality and the practices they recommend to achieve these qualities. We analyze data from semi-structured interviews with 34 professional software developers, programming teachers and students from Europe and the U.S. For the interviews, participants were asked to bring code examples to exemplify what they consider good and bad code, respectively. Readability and structure were used most commonly as defining properties for quality code. Together with documentation, they were also suggested as the most common target properties for quality improvement. When discussing actual code, developers focused on structure, comprehensibility and readability as quality properties. When analyzing relationships between properties, the most commonly talked about target property was comprehensibility. Documentation, structure and readability were named most frequently as source properties to achieve good comprehensibility. Some of the most important source code properties contributing to code quality as perceived by developers lack clear definitions and are difficult to capture. More research is therefore necessary to measure the structure, comprehensibility and readability of code in ways that matter for developers and to relate these measures of code structure, comprehensibility and readability to common software quality attributes.
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| 8. |
- Börstler, Jürgen, 1960-, et al.
(författare)
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Double-counting in software engineering tertiary studies — An overlooked threat to validity
- 2023
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Ingår i: Information and Software Technology. - : Elsevier. - 0950-5849 .- 1873-6025. ; 158
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Forskningsöversikt (refereegranskat)abstract
- Context: Double-counting in a literature review occurs when the same data, population, or evidence is erroneously counted multiple times during synthesis. Detecting and mitigating the threat of double-counting is particularly challenging in tertiary studies. Although this topic has received much attention in the health sciences, it seems to have been overlooked in software engineering. Objective: We describe issues with double-counting in tertiary studies, investigate the prevalence of the issue in software engineering, and propose ways to identify and address the issue. Method: We analyze 47 tertiary studies in software engineering to investigate in which ways they address double-counting and whether double-counting might be a threat to validity in them. Results: In 19 of the 47 tertiary studies, double-counting might bias their results. Of those 19 tertiary studies, only 5 consider double-counting a threat to their validity, and 7 suggest strategies to address the issue. Overall, only 9 of the 47 tertiary studies, acknowledge double-counting as a potential general threat to validity for tertiary studies. Conclusions: Double-counting is an overlooked issue in tertiary studies in software engineering, and existing design and evaluation guidelines do not address it sufficiently. Therefore, we propose recommendations that may help to identify and mitigate double-counting in tertiary studies. © 2023 The Author(s)
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| 9. |
- Börstler, Jürgen, 1960-, et al.
(författare)
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Evaluating OO Example Programs for CS1
- 2008
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Ingår i: Proceedings of the 13th annual conference on Innovation and technology in computer science education. - New York, NY, USA : ACM. ; , s. 47-52
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Konferensbidrag (refereegranskat)
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| 10. |
- Börstler, Jürgen, 1960-, et al.
(författare)
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Investigating Acceptance Behavior in Software Engineering – Theoretical Perspectives
- 2023
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Ingår i: Journal of Systems and Software. - : Elsevier. - 0164-1212 .- 1873-1228. ; 198
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Tidskriftsartikel (refereegranskat)abstract
- Background: Software engineering research aims to establish software development practice on a scientific basis. However, the evidence of the efficacy of technology is insufficient to ensure its uptake in industry. In the absence of a theoretical frame of reference, we mainly rely on best practices and expert judgment from industry-academia collaboration and software process improvement research to improve the acceptance of the proposed technology. Objective: To identify acceptance models and theories and discuss their applicability in the research of acceptance behavior related to software development.Method: We analyzed literature reviews within an interdisciplinary team to identify models and theories relevant to software engineering research. We further discuss acceptance behavior from the human information processing perspective of automatic and affect-driven processes (“fast” system 1 thinking) and rational and rule-governed processes (“slow” system 2 thinking). Results: We identified 30 potentially relevant models and theories. Several of them have been used in researching acceptance behavior in contexts related to software development, but few have been validated in such contexts. They use constructs that capture aspects of (automatic) system 1 and (rational) system 2 oriented processes. However, their operationalizations focus on system 2-oriented processes indicating a rational view of behavior, thus overlooking important psychological processes underpinning behavior. Conclusions: Software engineering research may use acceptance behavior models and theories more extensively to understand and predict practice adoption in the industry. Such theoretical foundations will help improve the impact of software engineering research. However, more consideration should be given to their validation, overlap, construct operationalization, and employed data collection mechanisms when using these models and theories.
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