| 1. |
- Besker, Terese, 1970, et al.
(författare)
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Embracing Technical Debt, from a Startup Company Perspective
- 2018
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Ingår i: PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION (ICSME). - 1063-6773. - 9781538678701 - 9781538678701 ; , s. 415-425
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Konferensbidrag (refereegranskat)abstract
- Software startups are typically under extreme pressure to get to market quickly with limited resources and high uncertainty. This pressure and uncertainty is likely to cause startups to accumulate technical debt as they make decisions that are more focused on the short-term than the long-term health of the codebase. However, most research on technical debt has been focused on more mature software teams, who may have less pressure and, therefore, reason about technical debt very differently than software startups. In this study, we seek to understand the organizational factors that lead to and the benefits and challenges associated with the intentional accumulation of technical debt in software startups. We interviewed 16 professionals involved in seven different software startups. We find that the startup phase, the experience of the developers, software knowledge of the founders, and level of employee growth are some of the organizational factors that influence the intentional accumulation of technical debt. In addition, we find the software startups are typically driven to achieve a “good enough level,” and this guides the amount of technical debt that they intentionally accumulate to balance the benefits of speed to market and reduced resources with the challenges of later addressing technical debt.
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| 2. |
- Abukwaik, H., et al.
(författare)
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Semi-Automated Feature Traceability with Embedded Annotations
- 2018
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Ingår i: Proceedings 2018 IEEE International Conference on Software Maintenance and Evolution. - : IEEE. - 9781538678701
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Konferensbidrag (refereegranskat)abstract
- Engineering software amounts to implementing and evolving features. While some engineering approaches advocate the explicit use of features, developers usually do not record feature locations in software artifacts. However, when evolving or maintaining features-especially in long-living or variant-rich software with many developers-the knowledge about features and their locations quickly fades and needs to be recovered. While automated or semi-automated feature-location techniques have been proposed, their accuracy is usually too low to be useful in practice. We propose a semi-automated, machine-learning-assisted feature-traceability technique that allows developers to continuously record feature-traceability information while being supported by recommendations about missed locations. We show the accuracy of our proposed technique in a preliminary evaluation, simulating the engineering of an open-source web-application that evolved in different, cloned variants.
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| 3. |
- Businge, J., et al.
(författare)
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Clone-Based Variability Management in the Android Ecosystem
- 2018
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Ingår i: Proceedings-IEEE International Conference on Software Maintenance. - : IEEE. - 9781538678701
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Konferensbidrag (refereegranskat)abstract
- Mobile app developers often need to create variants to account for different customer segments, payment models or functionalities. A common strategy is to clone (or fork) an existing app and then adapt it to new requirements. This form of reuse has been enhanced with the advent of social-coding platforms such as Github, cultivating a more systematic reuse. Different facilities, such as forks, pull requests, and cross-project traceability support clone-based development. Unfortunately, even though, many apps are known to be maintained in many variants, little is known about how practitioners manage variants of mobile apps. We present a study that explores clone-based reuse practices for open-source Android apps. We identified and analyzed families of apps that are maintained together and that exist both on the official app store (Google Play) as well as on Github, allowing us to analyze reuse practices in depth. We mined both repositories to identify app families and to study their characteristics, including their variabilities as well as code-propagation practices and maintainer relationships. We found that, indeed, app families exist and that forked app variants fall into the following categories: (i) re-branding and simple customizations, (ii) feature extension, (iii) supporting of the mainline app, and (iv) implementation of different, but related features. Other notable characteristic of the app families we discovered include: (i) 73% of the app families did not perform any form of code propagation, and (ii) 74% of the app families we studied do not have common maintainers.
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| 4. |
- Businge, John, et al.
(författare)
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Clone-based variability management in the android ecosystem
- 2018
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Ingår i: Proceedings - 2018 IEEE International Conference on Software Maintenance and Evolution, ICSME 2018. - 9781538678701 ; , s. 625-634
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Konferensbidrag (refereegranskat)abstract
- Mobile app developers often need to create variants to account for different customer segments, payment models or functionalities. A common strategy is to clone (or fork) an existing app and then adapt it to new requirements. This form of reuse has been enhanced with the advent of social-coding platforms such as Github, cultivating a more systematic reuse. Different facilities, such as forks, pull requests, and cross-project traceability support clone-based development. Unfortunately, even though, many apps are known to be maintained in many variants, little is known about how practitioners manage variants of mobile apps. We present a study that explores clone-based reuse practices for open-source Android apps. We identified and analyzed families of apps that are maintained together and that exist both on the official app store (Google Play) as well as on Github, allowing us to analyze reuse practices in depth. We mined both repositories to identify app families and to study their characteristics, including their variabilities as well as code-propagation practices and maintainer relationships. We found that, indeed, app families exist and that forked app variants fall into the following categories: (i) re-branding and simple customizations, (ii) feature extension, (iii) supporting of the mainline app, and (iv) implementation of different, but related features. Other notable characteristic of the app families we discovered include: (i) 72.7% of the app families did not perform any form of code propagation, and (ii) 74% of the app families we studied do not have common maintainers.
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| 5. |
- Mäntylä, Mika, et al.
(författare)
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On Rapid Releases and Software Testing
- 2013
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Ingår i: [Host publication title missing]. - Eindhoven, Netherlands. - 1063-6773. ; , s. 20-29
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Konferensbidrag (refereegranskat)abstract
- Abstract—Large open and closed source organizations like Google, Facebook and Mozilla are migrating their products towards rapid releases. While this allows faster time-to-market and user feedback, it also implies less time for testing and bug fixing. Since initial research results indeed show that rapid releases fix proportionally less reported bugs than traditional releases, this paper investigates the changes in software testing effort after moving to rapid releases. We analyze the results of 312,502 execution runs of the 1,547 mostly manual systemlevel test cases of Mozilla Firefox from 2006 to 2012 (5 major traditional and 9 major rapid releases), and triangulated our findings with a Mozilla QA engineer. In rapid releases, testing has a narrower scope that enables deeper investigation of the features and regressions with the highest risk, while traditional releases run the whole test suite. Furthermore, rapid releases make it more difficult to build a large testing community, forcing Mozilla to increase contractor resources in order to sustain testing for rapid releases.
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| 6. |
- Osman, M.H., et al.
(författare)
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An analysis of machine learning algorithms for condensing reverse engineered class diagrams
- 2013
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Ingår i: IEEE International Conference on Software Maintenance, ICSM. - : IEEE. - 1063-6773.
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Konferensbidrag (refereegranskat)abstract
- There is a range of techniques available to reverse engineer software designs from source code. However, these approaches generate highly detailed representations. The condensing of reverse engineered representations into more high-level design information would enhance the understandability of reverse engineered diagrams. This paper describes an automated approach for condensing reverse engineered diagrams into diagrams that look as if they are constructed as forward designed UML models. To this end, we propose a machine learning approach. The training set of this approach consists of a set of forward designed UML class diagrams and reverse engineered class diagrams (for the same system). Based on this training set, the method 'learns' to select the key classes for inclusion in the class diagrams. In this paper, we study a set of nine classification algorithms from the machine learning community and evaluate which algorithms perform best for predicting the key classes in a class diagram. © 2013 IEEE.
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| 7. |
- Schermann, G., et al.
(författare)
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Search-Based Scheduling of Experiments in Continuous Deployment
- 2018
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Ingår i: 2018 IEEE International Conference on Software Maintenance and Evolution. - : IEEE. - 9781538678701
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Konferensbidrag (refereegranskat)abstract
- Continuous experimentation involves practices for testing new functionality on a small fraction of the user base in production environments. Running multiple experiments in parallel requires handling user assignments (i.e., which users are part of which experiments) carefully as experiments might overlap and influence each other. Furthermore, experiments are prone to change, get canceled, or are adjusted and restarted, and new ones are added regularly. We formulate this as an optimization problem, fostering the parallel execution of experiments and making sure that enough data is collected for every experiment avoiding overlapping experiments. We propose a genetic algorithm that is capable of (re-)scheduling experiments and compare with other search-based approaches (random sampling, local search, and simulated annealing). Our evaluation shows that our genetic implementation outperforms the other approaches by up to 19% regarding the fitness of the solutions identified and up to a factor three in execution time in our evaluation scenarios.
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| 8. |
- Schermann, Gerald, et al.
(författare)
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Search-Based Scheduling of Experiments in Continuous Deployment
- 2018
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Ingår i: 2018 IEEE International Conference on Software Maintenance and Evolution (ICSME). - 9781538678701 ; , s. 485-495
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Konferensbidrag (refereegranskat)abstract
- Continuous experimentation involves practices for testing new functionality on a small fraction of the user base in production environments. Running multiple experiments in parallel requires handling user assignments (i.e., which users are part of which experiments) carefully as experiments might overlap and influence each other. Furthermore, experiments are prone to change, get canceled, or are adjusted and restarted, and new ones are added regularly. We formulate this as an optimization problem, fostering the parallel execution of experiments and making sure that enough data is collected for every experiment avoiding overlapping experiments. We propose a genetic algorithm that is capable of (re-)scheduling experiments and compare with other search-based approaches (random sampling, local search, and simulated annealing). Our evaluation shows that our genetic implementation outperforms the other approaches by up to 19% regarding the fitness of the solutions identified and up to a factor three in execution time in our evaluation scenarios.
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| 9. |
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