| 1. |
- David, I., et al.
(författare)
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Blended modeling in commercial and open-source model-driven software engineering tools: A systematic study
- 2023
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Ingår i: Software and Systems Modeling. - : Springer Science and Business Media LLC. - 1619-1366 .- 1619-1374. ; 22, s. 415-447
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Tidskriftsartikel (refereegranskat)abstract
- Blended modeling aims to improve the user experience of modeling activities by prioritizing the seamless interaction with models through multiple notations over the consistency of the models. Inconsistency tolerance, thus, becomes an important aspect in such settings. To understand the potential of current commercial and open-source modeling tools to support blended modeling, we have designed and carried out a systematic study. We identify challenges and opportunities in the tooling aspect of blended modeling. Specifically, we investigate the user-facing and implementation-related characteristics of existing modeling tools that already support multiple types of notations and map their support for other blended aspects, such as inconsistency tolerance, and elevated user experience. For the sake of completeness, we have conducted a multivocal study, encompassing an academic review, and grey literature review. We have reviewed nearly 5000 academic papers and nearly 1500 entries of grey literature. We have identified 133 candidate tools, and eventually selected 26 of them to represent the current spectrum of modeling tools.
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| 2. |
- Blanch, Krister, 1991
(författare)
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Beyond-application datasets and automated fair benchmarking
- 2023
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Beyond-application perception datasets are generalised datasets that emphasise the fundamental components of good machine perception data. When analysing the history of perception datatsets, notable trends suggest that design of the dataset typically aligns with an application goal. Instead of focusing on a specific application, beyond-application datasets instead look at capturing high-quality, high-volume data from a highly kinematic environment, for the purpose of aiding algorithm development and testing in general. Algorithm benchmarking is a cornerstone of autonomous systems development, and allows developers to demonstrate their results in a comparative manner. However, most benchmarking systems allow developers to use their own hardware or select favourable data. There is also little focus on run time performance and consistency, with benchmarking systems instead showcasing algorithm accuracy. By combining both beyond-application dataset generation and methods for fair benchmarking, there is also the dilemma of how to provide the dataset to developers for this benchmarking, as the result of a high-volume, high-quality dataset generation is a significant increase in dataset size when compared to traditional perception datasets. This thesis presents the first results of attempting the creation of such a dataset. The dataset was built using a maritime platform, selected due to the highly dynamic environment presented on water. The design and initial testing of this platform is detailed, as well as as methods of sensor validation. Continuing, the thesis then presents a method of fair benchmarking, by utilising remote containerisation in a way that allows developers to present their software to the dataset, instead of having to first locally store a copy. To test this dataset and automatic online benchmarking, a number of reference algorithms were required for initial results. Three algorithms were built, using the data from three different sensors captured on the maritime platform. Each algorithm calculates vessel odometry, and the automatic benchmarking system was utilised to show the accuracy and run-time performance of these algorithms. It was found that the containerised approach alleviated data management concerns, prevented inflated accuracy results, and demonstrated precisely how computationally intensive each algorithm was.
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| 3. |
- John, Meenu Mary, et al.
(författare)
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Towards an AI-driven business development framework: A multi-case study
- 2023
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Ingår i: Journal of Software: Evolution and Process. - : Wiley. - 2047-7481 .- 2047-7473. ; 35:6
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Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence (AI) and the use of machine learning (ML) and deep learning (DL) technologies are becoming increasingly popular in companies. These technologies enable companies to leverage big quantities of data to improve system performance and accelerate business development. However, despite the appeal of ML/DL, there is a lack of systematic and structured methods and processes to help data scientists and other company roles and functions to develop, deploy and evolve models. In this paper, based on multi-case study research in six companies, we explore practices and challenges practitioners experience in developing ML/DL models as part of large software-intensive embedded systems. Based on our empirical findings, we derive a conceptual framework in which we identify three high-level activities that companies perform in parallel with the development, deployment and evolution of models. Within this framework, we outline activities, iterations and triggers that optimize model design as well as roles and company functions. In this way, we provide practitioners with a blueprint for effectively integrating ML/DL model development into the business to achieve better results than other (algorithmic) approaches. In addition, we show how this framework helps companies solve the challenges we have identified and discuss checkpoints for terminating the business case.
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| 4. |
- Abrahao, Silvia, et al.
(författare)
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Open Source Software: Communities and Quality
- 2023
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Ingår i: IEEE Software. - 1937-4194 .- 0740-7459. ; 40:4, s. 96-99
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Tidskriftsartikel (refereegranskat)abstract
- This edition of the Practitioner's Digest features recent papers on open source software related to toxicity in open source discussions, newcomers in open source projects, quality of ansible scripts, code review practices, orphan vulnerabilities in open source software, and the relationship between community and design smells.
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| 5. |
- Michael Ayas, Hamdy, 1994, et al.
(författare)
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An empirical study of the systemic and technical migration towards microservices
- 2023
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Ingår i: Empirical Software Engineering. - 1382-3256 .- 1573-7616. ; 28:4
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Tidskriftsartikel (refereegranskat)abstract
- ContextAs many organizations modernize their software architecture and transition to the cloud, migrations towards microservices become more popular. Even though such migrations help to achieve organizational agility and effectiveness in software development, they are also highly complex, long-running, and multi-faceted.ObjectiveIn this study we aim to comprehensively map the journey towards microservices and describe in detail what such a migration entails. In particular, we aim to discuss not only the technical migration, but also the long-term journey of change, on a systemic level.MethodOur research method is an inductive, qualitative study on two data sources. Two main methodological steps take place - interviews and analysis of discussions from StackOverflow. The analysis of both, the 19 interviews and 215 StackOverflow discussions, is based on techniques found in grounded theory.ResultsOur results depict the migration journey, as it materializes within the migrating organization, from structural changes to specific technical changes that take place in the work of engineers. We provide an overview of how microservices migrations take place as well as a deconstruction of high level modes of change to specific solution outcomes. Our theory contains 2 modes of change taking place in migration iterations, 14 activities and 53 solution outcomes of engineers. One of our findings is on the architectural change that is iterative and needs both a long and short term perspective, including both business and technical understanding. In addition, we found that a big proportion of the technical migration has to do with setting up supporting artifacts and changing the paradigm that software is developed.
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| 6. |
- Saadatmand, Mehrdad, PhD, 1980-, et al.
(författare)
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SmartDelta project : Automated quality assurance and optimization across product versions and variants
- 2023
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Ingår i: Microprocessors and microsystems. - : Elsevier. - 0141-9331 .- 1872-9436. ; 103
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Tidskriftsartikel (refereegranskat)abstract
- Software systems are often built in increments with additional features or enhancements on top of existing products. This incremental development may result in the deterioration of certain quality aspects. In other words, the software can be considered an evolving entity emanating different quality characteristics as it gets updated over time with new features or deployed in different operational environments. Approaching software development with this mindset and awareness regarding quality evolution over time can be a key factor for the long-term success of a company in today's highly competitive market of industrial software-intensive products. Therefore, it is important to be able to accurately analyze and determine the quality implications of each change and increment to a software system. To address this challenge, the multinational SmartDelta project develops automated solutions for the quality assessment of product deltas in a continuous engineering environment. The project provides smart analytics from development artifacts and system executions, offering insights into quality degradation or improvements across different product versions, and providing recommendations for the next builds. This paper presents the challenges in incremental software development tackled in the scope of the SmartDelta project, and the solutions that are produced and planned in the project, along with the industrial impact of the project for software-intensive industrial systems.
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| 7. |
- Camara, J., et al.
(författare)
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ExTrA: Explaining architectural design tradeoff spaces via dimensionality reduction
- 2023
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Ingår i: Journal of Systems and Software. - : Elsevier BV. - 0164-1212. ; 198
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Tidskriftsartikel (refereegranskat)abstract
- In software design, guaranteeing the correctness of run-time system behavior while achieving an acceptable balance among multiple quality attributes remains a challenging problem. Moreover, providing guarantees about the satisfaction of those requirements when systems are subject to uncertain environments is even more challenging. While recent developments in architectural analysis techniques can assist architects in exploring the satisfaction of quantitative guarantees across the design space, existing approaches are still limited because they do not explicitly link design decisions to satisfaction of quality requirements. Furthermore, the amount of information they yield can be overwhelming to a human designer, making it difficult to see the forest for the trees. In this paper we present ExTrA (Explaining Tradeoffs of software Architecture design spaces), an approach to analyzing architectural design spaces that addresses these limitations and provides a basis for explaining design tradeoffs. Our approach employs dimensionality reduction techniques employed in machine learning pipelines like Principal Component Analysis (PCA) and Decision Tree Learning (DTL) to enable architects to understand how design decisions contribute to the satisfaction of extrafunctional properties across the design space. Our results show feasibility of the approach in two case studies and evidence that combining complementary techniques like PCA and DTL is a viable approach to facilitate comprehension of tradeoffs in poorly-understood design spaces.(c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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| 8. |
- Penzenstadler, Birgit, 1981, et al.
(författare)
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AI, Tech, Energy, and Collaboration
- 2023
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Ingår i: IEEE Software. - 1937-4194 .- 0740-7459. ; 40:3, s. 80-83
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Tidskriftsartikel (refereegranskat)abstract
- This edition of the “Practitioner’s Digest” features recent papers on artificial intelligence (AI) and machine learning (ML), along with papers on tech debt, energy consumption, and collaboration between industry and academia.
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| 9. |
- Säwén, Toivo, 1993
(författare)
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Early Stage Architectural Design Practice Perspectives on Life Cycle Building Performance Assessment
- 2023
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Architectural practitioners can avoid negative social and environmental impacts of new construction by making decisions supported by impact quantification during design processes. However, most software tools developed for such quantification see little use in practice, especially in early design stages when decisions have the greatest influence. To identify ways for software developers to overcome this situation, a thorough literature meta-review of previously performed tool reviews was combined with interviews applying a practice lens. The first key finding is that a possible explanation for the low tool uptake in practice could be a missing practice perspective in previous tool development efforts. In a literature meta-review of publications on life cycle building performance tools identifying previously applied perspectives, most previous tool reviews were found to support tool development and selection, while disregarding how tools can be integrated in existing practices and design processes. As a proposed solution, a framework for defining software requirements using a practice perspective was developed. The second key finding is that a practice perspective could be applied during software development by implementing qualitative methodologies. Nine architectural practitioners in Sweden, Norway and France were interviewed using the interview to the double, a projective technique in which the interviewee is asked to describe their next workday in detail so that their tasks can be assumed by an imagined body double. The design activities described by the respondents were sequenced into user narratives which could serve as starting points for participatory software development processes within the architectural practice. The outcomes - a proposed framework for practice-centric software requirements, and a proposed methodology for collecting these requirements using a practice lens - indicate a research direction toward software development efforts which aligns with design process, architectural practice, and tool user needs. In the next stage of the research this direction will be pursued through application of the developed methodologies in participatory development case studies in early-stage architectural design practice.
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| 10. |
- Kim, Jinhan, et al.
(författare)
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Learning test-mutant relationship for accurate fault localisation
- 2023
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Ingår i: Information and Software Technology. - 0950-5849. ; 162
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Tidskriftsartikel (refereegranskat)abstract
- Context: Automated fault localisation aims to assist developers in the task of identifying the root cause of the fault by narrowing down the space of likely fault locations. Simulating variants of the faulty program called mutants, several Mutation Based Fault Localisation (MBFL) techniques have been proposed to automatically locate faults. Despite their success, existing MBFL techniques suffer from the cost of performing mutation analysis after the fault is observed. Method: To overcome this shortcoming, we propose a new MBFL technique named SIMFL (Statistical Inference for Mutation-based Fault Localisation). SIMFL localises faults based on the past results of mutation analysis that has been done on the earlier version in the project history, allowing developers to make predictions on the location of incoming faults in a just-in-time manner. Using several statistical inference methods, SIMFL models the relationship between test results of the mutants and their locations, and subsequently infers the location of the current faults. Results: The empirical study on DEFECTS4J dataset shows that SIMFL can localise 113 faults on the first rank out of 224 faults, outperforming other MBFL techniques. Even when SIMFL is trained on the predicted kill matrix, SIMFL can still localise 95 faults on the first rank out of 194 faults. Moreover, removing redundant mutants significantly improves the localisation accuracy of SIMFL by the number of faults localised at the first rank up to 51. Conclusion: This paper proposes a new MBFL technique called SIMFL, which exploits ahead-of-time mutation analysis to localise current faults. SIMFL is not only cost-effective, as it does not need a mutation analysis after the fault is observed, but also capable of localising faults accurately.
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