| 1. |
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| 2. |
- Al Mamun, Md Abdullah, 1982, et al.
(författare)
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Improving Code Smell Predictions in Continuous Integration by Differentiating Organic from Cumulative Measures
- 2019
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Ingår i: The Fifth International Conference on Advances and Trends in Software Engineering. - 2519-8394. - 9781510883741 ; , s. 62-71
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Konferensbidrag (refereegranskat)abstract
- Continuous integration and deployment are enablers of quick innovation cycles of software and systems through incremental releases of a product within short periods of time. If software qualities can be predicted for the next release, quality managers can plan ahead with resource allocation for concerning issues. Cumulative metrics are observed to have much higher correlation coefficients compared to non-cumulative metrics. Given the difference in correlation coefficients of cumulative and noncumulative metrics, this study investigates the difference between metrics of these two categories concerning the correctness of predicting code smell which is internal software quality. This study considers 12 metrics from each measurement category, and 35 code smells collected from 36,217 software revisions (commits) of 242 open source Java projects. We build 8,190 predictive models and evaluate them to determine how measurement categories of predictors and targets affect model accuracies predicting code smells. To further validate our approach, we compared our results with Principal Component Analysis (PCA), a statistical procedure for dimensionality reduction. Results of the study show that within the context of continuous integration, non-cumulative metrics as predictors build better predictive models with respect to model accuracy compared to cumulative metrics. When the results are compared with models built from extracted PCA components, we found better results using our approach.
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| 3. |
- Al Sabbagh, Khaled, 1987, et al.
(författare)
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A classification of code changes and test types dependencies for improving machine learning based test selection
- 2021
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Ingår i: SIGPLAN Notices (ACM Special Interest Group on Programming Languages). - New York, NY, USA : ACM. - 0730-8566. ; , s. 40-49
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Konferensbidrag (refereegranskat)abstract
- Machine learning has been increasingly used to solve various software engineering tasks. One example of their usage is in regression testing, where a classifier is built using historical code commits to predict which test cases require execution. In this paper, we address the problem of how to link specific code commits to test types to improve the predictive performance of learning models in improving regression testing. We design a dependency taxonomy of the content of committed code and the type of a test case. The taxonomy focuses on two types of code commits: changing memory management and algorithm complexity. We reviewed the literature, surveyed experienced testers from three Swedish-based software companies, and conducted a workshop to develop the taxonomy. The derived taxonomy shows that memory management code should be tested with tests related to performance, load, soak, stress, volume, and capacity; the complexity changes should be tested with the same dedicated tests and maintainability tests. We conclude that this taxonomy can improve the effectiveness of building learning models for regression testing.
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| 4. |
- Al Sabbagh, Khaled, 1987, et al.
(författare)
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Improving Data Quality for Regression Test Selection by Reducing Annotation Noise
- 2020
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Ingår i: Proceedings - 46th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2020. ; , s. 191-194
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Konferensbidrag (refereegranskat)abstract
- Big data and machine learning models have been increasingly used to support software engineering processes and practices. One example is the use of machine learning models to improve test case selection in continuous integration. However, one of the challenges in building such models is the identification and reduction of noise that often comes in large data. In this paper, we present a noise reduction approach that deals with the problem of contradictory training entries. We empirically evaluate the effectiveness of the approach in the context of selective regression testing. For this purpose, we use a curated training set as input to a tree-based machine learning ensemble and compare the classification precision, recall, and f-score against a non-curated set. Our study shows that using the noise reduction approach on the training instances gives better results in prediction with an improvement of 37% on precision, 70% on recall, and 59% on f-score.
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| 5. |
- Al Sabbagh, Khaled, 1987, et al.
(författare)
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Improving Software Regression Testing Using a Machine Learning-Based Method for Test Type Selection
- 2022
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 13709 LNCS, s. 480-496
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Konferensbidrag (refereegranskat)abstract
- Since only a limited time is available for performing software regression testing, a subset of crucial test cases from the test suites has to be selected for execution. In this paper, we introduce a method that uses the relation between types of code changes and regression tests to select test types that require execution. We work closely with a large power supply company to develop and evaluate the method and measure the total regression testing time taken by our method and its effectiveness in selecting the most relevant test types. The results show that the method reduces the total regression time by an average of 18,33% when compared with the approach used by our industrial partner. The results also show that using a medium window size in the method configuration results in an improved recall rate from 61,11% to 83,33%, but not in considerable time reduction of testing. We conclude that our method can potentially be used to steer the testing effort at software development companies by guiding testers into which regression test types are essential for execution.
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| 6. |
- Al-Sabbagh, Khaled, et al.
(författare)
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Improving test case selection by handling class and attribute noise
- 2022
-
Ingår i: Journal of Systems and Software. - : Elsevier BV. - 0164-1212. ; 183
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Tidskriftsartikel (refereegranskat)abstract
- Big data and machine learning models have been increasingly used to support software engineering processes and practices. One example is the use of machine learning models to improve test case selection in continuous integration. However, one of the challenges in building such models is the large volume of noise that comes in data, which impedes their predictive performance. In this paper, we address this issue by studying the effect of two types of noise, called class and attribute, on the predictive performance of a test selection model. For this purpose, we analyze the effect of class noise by using an approach that relies on domain knowledge for relabeling contradictory entries and removing duplicate ones. Thereafter, an existing approach from the literature is used to experimentally study the effect of attribute noise removal on learning. The analysis results show that the best learning is achieved when training a model on class-noise cleaned data only - irrespective of attribute noise. Specifically, the learning performance of the model reported 81% precision, 87% recall, and 84% f-score compared with 44% precision, 17% recall, and 25% f-score for a model built on uncleaned data. Finally, no causality relationship between attribute noise removal and the learning of a model for test case selection was drawn. (C) 2021 The Author(s). Published by Elsevier Inc.
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| 7. |
- Al Sabbagh, Khaled, 1987, et al.
(författare)
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Predicting build outcomes in continuous integration using textual analysis of source code commits
- 2022
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Ingår i: PROMISE 2022 - Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering, co-located with ESEC/FSE 2022. - New York, NY, USA : ACM. ; , s. 42-51
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Konferensbidrag (refereegranskat)abstract
- Machine learning has been increasingly used to solve various software engineering tasks. One example of its usage is to predict the outcome of builds in continuous integration, where a classifier is built to predict whether new code commits will successfully compile. The aim of this study is to investigate the effectiveness of fifteen software metrics in building a classifier for build outcome prediction. Particularly, we implemented an experiment wherein we compared the effectiveness of a line-level metric and fourteen other traditional software metrics on 49,040 build records that belong to 117 Java projects. We achieved an average precision of 91% and recall of 80% when using the line-level metric for training, compared to 90% precision and 76% recall for the next best traditional software metric. In contrast, using file-level metrics was found to yield a higher predictive quality (average MCC for the best software metric= 68%) than the line-level metric (average MCC= 16%) for the failed builds. We conclude that file-level metrics are better predictors of build outcomes for the failed builds, whereas the line-level metric is a slightly better predictor of passed builds.
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| 8. |
- Al Sabbagh, Khaled, 1987, et al.
(författare)
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Predicting Test Case Verdicts Using TextualAnalysis of Commited Code Churns
- 2019
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Ingår i: CEUR Workshop Proceedings. - 1613-0073. ; 2476, s. 138-153
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Konferensbidrag (refereegranskat)abstract
- Background: Continuous Integration (CI) is an agile software development practice that involves producing several clean builds of the software per day. The creation of these builds involve running excessive executions of automated tests, which is hampered by high hardware cost and reduced development velocity. Goal: The goal of our research is to develop a method that reduces the number of executed test cases at each CI cycle.Method: We adopt a design research approach with an infrastructure provider company to develop a method that exploits Ma-chine Learning (ML) to predict test case verdicts for committed sourcecode. We train five different ML models on two data sets and evaluate their performance using two simple retrieval measures: precision and recall. Results: While the results from training the ML models on the first data-set of test executions revealed low performance, the curated data-set for training showed an improvement on performance with respect to precision and recall. Conclusion: Our results indicate that the method is applicable when training the ML model on churns of small sizes
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| 9. |
- Al Sabbagh, Khaled, 1987, et al.
(författare)
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Selective Regression Testing based on Big Data: Comparing Feature Extraction Techniques
- 2020
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Ingår i: IEEE Software. - 1937-4194 .- 0740-7459. ; , s. 322-329
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Konferensbidrag (refereegranskat)abstract
- Regression testing is a necessary activity in continuous integration (CI) since it provides confidence that modified parts of the system are correct at each integration cycle. CI provides large volumes of data which can be used to support regression testing activities. By using machine learning, patterns about faulty changes in the modified program can be induced, allowing test orchestrators to make inferences about test cases that need to be executed at each CI cycle. However, one challenge in using learning models lies in finding a suitable way for characterizing source code changes and preserving important information. In this paper, we empirically evaluate the effect of three feature extraction algorithms on the performance of an existing ML-based selective regression testing technique. We designed and performed an experiment to empirically investigate the effect of Bag of Words (BoW), Word Embeddings (WE), and content-based feature extraction (CBF). We used stratified cross validation on the space of features generated by the three FE techniques and evaluated the performance of three machine learning models using the precision and recall metrics. The results from this experiment showed a significant difference between the models' precision and recall scores, suggesting that the BoW-fed model outperforms the other two models with respect to precision, whereas a CBF-fed model outperforms the rest with respect to recall.
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| 10. |
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| 11. |
- Al Sabbagh, Khaled, 1987, et al.
(författare)
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The Effect of Class Noise on Continuous Test Case Selection: A Controlled Experiment on Industrial Data
- 2020
-
Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 1611-3349 .- 0302-9743. ; 12562, s. 287-303
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Konferensbidrag (refereegranskat)abstract
- Continuous integration and testing produce a large amount of data about defects in code revisions, which can be utilized for training a predictive learner to effectively select a subset of test suites. One challenge in using predictive learners lies in the noise that comes in the training data, which often leads to a decrease in classification performances. This study examines the impact of one type of noise, called class noise, on a learner’s ability for selecting test cases. Understanding the impact of class noise on the performance of a learner for test case selection would assist testers decide on the appropriateness of different noise handling strategies. For this purpose, we design and implement a controlled experiment using an industrial data-set to measure the impact of class noise at six different levels on the predictive performance of a learner. We measure the learning performance using the Precision, Recall, F-score, and Mathew Correlation Coefficient (MCC) metrics. The results show a statistically significant relationship between class noise and the learners performance for test case selection. Particularly, a significant difference between the three performance measures (Precision, F-score, and MCC)under all the six noise levels and at 0% level was found, whereas a similar relationship between recall and class noise was found at a level above30%. We conclude that higher class noise ratios lead to missing out more tests in the predicted subset of test suite and increases the rate of false alarms when the class noise ratio exceeds 30%
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| 12. |
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| 13. |
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| 14. |
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| 15. |
- Bainomugisha, Engineer, et al.
(författare)
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Emerging Software Engineering Research Networks in (East) Africa
- 2021
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Ingår i: ACM SIGSOFT Software Engineering Notes. - : Association for Computing Machinery (ACM). - 0163-5948. ; 46:2, s. 18-22
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Software engineering (SE) researchers and research networks from emerging communities are often not visible in already established Software Engineering venues for a multitude of reasons. This limits the opportunities and mutual bene ts that can arise from collaborations between global and emerging Software Engineer- ing networks. This article focuses on a rst attempt to provide a map of the African software engineering research community with focus on the networks of two big East African Universities. We hope that this very initial mapping e ort will help to raise aware- ness in the international community about the variety of software engineering research in Africa. We formulate some suggestions for making our academic Software Engineering community more inclusive.
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| 16. |
- Bainomugisha, Engineer, et al.
(författare)
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Sustainable Capacity Building in Software Engineering Research in Africa: The Example of the BRIGHT Project
- 2020
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Ingår i: ACM SIGSOFT Software Engineering Notes. - : Association for Computing Machinery (ACM). - 0163-5948. ; 45:3
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- The software industry is a key engine of economic growth in Africa, which calls for sustainable and innovative approaches to build capacities in software engineering research and education for the continent. This paper presents the BRIGHT project as an example for a collaboration that aims to build such capacity. The collaboration includes institutions in Sweden and Uganda. The goal of the collaboration is to train faculty in software en- gineering and to build a supporting research environment, which includes the creation of networks with the software engineering community at a global scale as well as connecting academia and the local software industry. So far, the project has resulted in 50 publications, a software engineering research centre, software engineering summer schools, and conferences.
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| 17. |
- Chaudron, Michel, 1969, et al.
(författare)
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Diversity in UML modeling explained: Observations, classifications and theorizations
- 2018
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 10706 LNCS, s. 47-66
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Konferensbidrag (refereegranskat)abstract
- Modeling is a common part of modern day software engineering practice. Little evidence exists about how models are used in software development and how they help in producing better software. In this talk we introduce a classification-matrix and a theoretical framework that helps explain the large variety of models and modeling styles found in industrial practice. As part of this explanation, we will explore empirical findings on the uses of UML modeling in practice. We intersperse this paper with some insights about modeling in software development that may be common to some, but certainly not generally accepted throughout the software engineering community.
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| 18. |
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| 19. |
- 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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| 20. |
- Hebig, Regina, et al.
(författare)
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Approaches to Co-Evolution of Metamodels and Models: A Survey
- 2017
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Ingår i: IEEE Transactions on Software Engineering. - 0098-5589 .- 1939-3520. ; 43:5, s. 396-414
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Tidskriftsartikel (refereegranskat)abstract
- Modeling languages, just as all software artifacts, evolve. This poses the risk that legacy models of a company get lost, when they become incompatible with the new language version. To address this risk, a multitude of approaches for metamodel-model co-evolution were proposed in the last 10 years. However, the high number of solutions makes it difficult for practitioners to choose an appropriate approach. In this paper, we present a survey on 31 approaches to support metamodel-model co-evolution. We introduce a taxonomy of solution techniques and classify the existing approaches. To support researchers, we discuss the state of the art, in order to better identify open issues. Furthermore, we use the results to provide a decision support for practitioners, who aim to adopt solutions from research.
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| 21. |
- Hebig, Regina, 1984, et al.
(författare)
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How Do Process and Team Interaction Depend on Development Technologies?: A Case Study on a Combined Setting of Model-driven Development and Classical C Coding
- 2016
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Ingår i: International Conference on Software and System Process, ICSSP 2016; Austin; United States; 14 May 2016 through 15 May 2016. - New York, NY, USA : ACM. - 9781450341882 ; , s. 16-25
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Konferensbidrag (refereegranskat)abstract
- Context: To be more flexible, companies call more and more for an independence between development tools and processes. To enable this form of decoupling we need to understand the interrelation of processes and development tools. However, knowledge about that field is rare. Goal: The goal of this study is to better understand how technologies in use might impact the processes and team interaction. Method: Therefore, we conducted a case study at Ericsson using grounded theory, performing a series of interviews among 6 senior developers and architects. The investigated case is special in that alternative tooling/language settings are used to build the different parts of the same system. Results: As a result we identified several relations between process and tooling. We further report on additional observation about human factors involved in development. Conclusion: The findings show that a bad choice of technologies can lead to unexpected impacts on team dynamics.
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| 22. |
- Hebig, Regina, 1984, et al.
(författare)
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How do students experience and judge software comprehension techniques?
- 2020
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Ingår i: IEEE International Conference on Program Comprehension. - New York, NY, USA : ACM. ; , s. 425-435
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Konferensbidrag (refereegranskat)abstract
- Today, there is a wide range of techniques to support softwarecomprehension. However, we do not fully understand yet whattechniques really help novices, to comprehend a software system.In this paper, we present a master level project course on softwareevolution, which has a large focus on software comprehension. Wecollected data about student's experience with diverse comprehension techniques during focus group discussions over the course oftwo years. Our results indicate that systematic code reading canbe supported by additional techniques to guiding reading efforts.Most techniques are considered valuable for gaining an overviewand some techniques are judged to be helpful only in later stagesof software comprehension efforts.
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| 23. |
- Hebig, Regina, et al.
(författare)
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Hybrid and evolving processes for software and systems—ICSSP 2019 special issue
- 2021
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Ingår i: Journal of Software: Evolution and Process. - : Wiley. - 2047-7481 .- 2047-7473. ; 33:1
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- © 2020 The Authors. Journal of Software: Evolution and Process published by John Wiley & Sons Ltd The volume at hand presents the special issue of the 12th International Conference on Software and Systems Process (ICSSP) 2019, which was held in Montreal, Canada, from May 25 to 26, 2019. ICSSP 2019 is the latest in a series of conferences that have been organized by the International Software and Systems Process Association. In our evolving landscape, many companies are making efforts to move towards new technologies and tools, agile principles, and continuous integration and delivery. In doing so, they find opportunity, flexibility, and strength in evolving towards hybrid processes, which are neither purely traditional nor can count as textbook agile. This special issue focuses on hybrid processes.
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| 24. |
- Hebig, Regina, et al.
(författare)
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Identifying Metrics' Biases When Measuring or Approximating Size in Heterogeneous Languages.
- 2015
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Ingår i: Empirical Software Engineering and Measurement (ESEM 2015), ACM/IEEE International Symposium on.. - 1938-6451 .- 1949-3789 .- 1949-3770. - 9781467378994
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Konferensbidrag (refereegranskat)abstract
- To compare the effectiveness of development techniques, the size of compared software systems needs to be taken into account. However, in industry new development techniques often come with changes in the applied programming languages. Goal: Our goal is to investigate how different size metrics and approximations are biased towards the languages c and c++. Further, we investigate whether triangulation of metrics has the potential to compensate for biases. Method: We identify crucial preconditions for a triangulation and investigate on 34 open source projects, whether a set of 16 size metrics fulfills these preconditions for the languages c and c++. Results: We identify how metrics differ in their biases and find that the preconditions for triangulation are fulfilled. Conclusion: Triangulation has the potential to address language biases, but high variance among metrics and tools need to be taken into account, too.
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| 25. |
- Hebig, Regina, et al.
(författare)
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Lessons Learned from Co-Evolution of Software Process and Model-Driven Engineering
- 2016
-
Ingår i: Managing Software Process Evolution. - Cham : Springer. - 9783319315454 ; , s. 257-280
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Bokkapitel (refereegranskat)abstract
- Software companies need to cope with permanent changes in market. To stay competitive it is often inevitable to improve processes and adopt to new technologies. Indeed, it is well know that software processes and model-driven engineering (MDE) are subject to evolution. Simultaneously, it is known that MDE can affect process tailoring, which makes it possible that evolution in MDE triggers process evolution and vice versa. This can lead to undesired process changes and additional cost, when process adaptations constitute a need for further investments in MDE tooling. However, there is little knowledge so far whether this co-evolution exists and how it looks like. In this chapter, we present two industrial case studies on co-evolution of MDE and software process. Based on these case studies, we present an initial list of co-evolution drivers and observations made on co-evolution of software processes and MDE. Furthermore, we compile our lessons learned to directly help process managers dealing with co-evolution.
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| 26. |
- Hebig, Regina, 1984, et al.
(författare)
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Lessons Learned from Co-Evolution of Software Process and Model-Driven Engineering
- 2016
-
Ingår i: Managing Software Process Evolution. - Cham : Springer International Publishing. - 9783319315454 ; , s. 257-280
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Software companies need to cope with permanent changes in market. To stay competitive it is often inevitable to improve processes and adopt to new technologies. Indeed, it is well know that software processes and model-driven engineering (MDE) are subject to evolution. Simultaneously, it is known that MDE can affect process tailoring, which makes it possible that evolution in MDE triggers process evolution and vice versa. This can lead to undesired process changes and additional cost, when process adaptations constitute a need for further investments in MDE tooling. However, there is little knowledge so far whether this co-evolution exists and how it looks like. In this chapter, we present two industrial case studies onco-evolution of MDE and software process. Based on these case studies, we present an initial list of co-evolution drivers and observations made on co-evolution of softwareprocesses and MDE. Furthermore, we compile our lessons learned to directly help process managers dealing with co-evolution.
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| 27. |
- Hebig, Regina, 1984, et al.
(författare)
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Lessons learned from co-evolution of software process and model-driven engineering
- 2016
-
Ingår i: Managing Software Process Evolution: Traditional, Agile and Beyond - How to Handle Process Change. - Cham : Springer International Publishing. - 9783319315454 ; , s. 257-280
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Software companies need to cope with permanent changes in market. To stay competitive it is often inevitable to improve processes and adopt to new technologies. Indeed, it is well known that software processes and model-driven engineering (MDE) are subject to evolution. Simultaneously, it is known that MDE can affect process tailoring, which makes it possible that evolution in MDE triggers process evolution and vice versa. This can lead to undesired process changes and additional cost, when process adaptations constitute a need for further investments in MDE tooling. However, there is little knowledge so far whether this co-evolution exists and how it looks like. In this chapter, we present two industrial case studies on co-evolution of MDE and software process. Based on these case studies, we present an initial list of co-evolution drivers and observations made on co-evolution of software processes and MDE. Furthermore, we compile our lessons learned to directly help process managers dealing with co-evolution.
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| 28. |
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| 29. |
- Hebig, Regina, 1984, et al.
(författare)
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On tackling quality threats for the assessment of measurement programs: A case study on the distribution of metric usage and knowledge
- 2017
-
Ingår i: Science of Computer Programming. - : Elsevier BV. - 0167-6423. ; 135, s. 45-74
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Tidskriftsartikel (refereegranskat)abstract
- Context Measurement programs are subject to changing requirements, causing the need for a robustness to compensate these changes. Existing methods enable the assessment of measurement programs and their robustness with the help of company representatives. Goal: However, it is not clear how much the spread of knowledge among roles and differences between company internal organizations influence the result and quality of the assessment. Thus, it is not known today who and how many representatives should be interviewed to get reliable results. Method: To address these points we performed a case study on the assessment method MeSRAM, spanning 18 interviews with 14 representatives of 4 different organizations within a large international communication company. Results: Managers are able to answer more questions and their answers are more often correct than those of engineers. Furthermore, most errors occur for questions about the use of concrete metrics, while for aspects about the metrics' infrastructure no conflicting answers occurred. We also identified 6 reasons for gaining incorrect answers. Conclusion: The assessment of measurement programs requires additional care to ensure the quality of the results. (C) 2016 Elsevier B.V. All rights reserved.
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| 30. |
- Hebig, Regina, et al.
(författare)
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Surveying the Corpus of Model Resolution Strategies for Metamodel Evolution
- 2015
-
Ingår i: 22nd Asia-Pacific Software Engineering Conference, APSEC 2015; Holiday Inn Hotel at International AirportNew Delhi; India; 1 December 2015 through 4 December 2015. - 1530-1362. - 9781467396448 ; , s. 135-142
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Konferensbidrag (refereegranskat)abstract
- Modeling languages evolve regularly. Companies need to maintain all those models that are used in running projects, which can cause these projects to fall back in their schedules. Since 10 years research addresses this issue with approaches for automating co-evolution. The dominant core of these approaches are model resolution strategies. They define 1) how models have to be changed in reaction to specific metamodel changes, 2) what degree of automation can be reached, and 3) to what extent the user can control the resolution outcome. In this paper, we survey existing co-evolution approaches and analyze model resolution strategies. We present a corpus of more than 200 resolution strategies for 116 types of metamodel changes and discuss degree of automation and choices that users have today.
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| 31. |
- Hebig, Regina, et al.
(författare)
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The changing balance of technology and process: A case study on a combined setting of model-driven development and classical C coding
- 2017
-
Ingår i: Journal of Software: Evolution and Process. - : Wiley. - 2047-7481 .- 2047-7473. ; 29:11
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Tidskriftsartikel (refereegranskat)abstract
- © 2017 John Wiley & Sons, Ltd. The increasing flexibility in industry leads to an ecosystem of change, affecting the balance of processes and technology as well as the developers who have to cope with the change. Furthermore, the change itself might impact the ability to use quantitative methods to learn from previous experience. The goal of this study is to better understand the ecosystem of mutual impacts and changes of process and technologies as well as how developers perceive a technology setting and deal with its change. Therefore, we conducted a case study at Ericsson, performing a series of interviews among 6 employees (senior developers and architects). We identified a time line of changes that happened over 7years. A set of observations about the relation between processes and tooling, and observations about developer's perceptions of the technology settings, and their strategy to deal with these changing technology settings. We discuss how the observed change impacts the ability to perform quantitative evaluations of technology and processes. The findings show that a bad choice of technologies can lead to unexpected impact on team dynamics. Furthermore, change happens so regular that it needs to be considered when collecting data for a quantitative evaluation of, eg, productivity.
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| 32. |
- Hebig, Regina, 1984, et al.
(författare)
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The quest for open source projects that use UML: mining GitHub.
- 2016
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Ingår i: Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems (MODELS '16). - New York, NY, USA : ACM. - 9781450343213 ; , s. 173-183
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Konferensbidrag (refereegranskat)abstract
- Context: While industrial use of UML was studied intensely, little is known about UML use in Free/Open Source Software (FOSS) projects. Goal: We aim at systematically mining GitHub projects to answer the question when models, if used, are created and updated throughout the whole project's life-span. Method: We present a semi-automated approach to collect UML stored in images, .xmi, and .uml files and scanned ten percent of all GitHub projects (1.24 million). Our focus was on number and role of contributors that created/updated models and the time span during which this happened. Results: We identified and studied 21 316 UML diagrams within 3 295 projects. Conclusion: Creating/updating of UML happens most often during a very short phase at the project start. For 12% of the models duplicates were found, which are in average spread across 1.88 projects. Finally, we contribute a list of GitHub projects that include UML files.
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| 33. |
- Hebig, Regina
(författare)
-
UI-Tracer
- 2018
-
Ingår i: Software Engineering und Software Management. - Bonn : Gesellschaft für Informatik. - 1617-5468. - 9783885796732
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Konferensbidrag (refereegranskat)
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| 34. |
- Ho-Quang, Truong, 1989, et al.
(författare)
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Challenges and directions for a community infrastructure for Big Data-driven research in software architecture
- 2020
-
Ingår i: Model Management and Analytics for Large Scale Systems. - : Elsevier. ; , s. 13-35
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Research into software architecture and design has become more and more prominent since the 1990s. Since then, companies have reported how software architecting helped them to tackle various challenges in system design, especially related to system-level quality properties such as scalability and maintainability. Academic research in software architecture has focused on several areas, including architecture description through views and architecture description languages, and on methods for evaluating architectural designs. While much of the contribution of research in software architecture was inspired by industrial experiences, little of the research was validated beyond individual case studies. Many scientific disciplines are currently harvesting fruits from large-scale data collection about their subjects of study. Therefore, this chapter contributes a discussion of challenges and directions for Big Data-driven studies of software architecture. Given the large amount of effort that is needed for this type of research, a promising direction is to look into a community-based infrastructure for enabling and supporting this type of research. We share lessons learned through building various tools that could form building blocks in such an infrastructure. Based on these, we synthesize a reference architecture for creating such a community-wide infrastructure for Big Data-based research in software architecture.
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| 35. |
- Ho-Quang, Truong, et al.
(författare)
-
Practices and perceptions of UML use in open source projects
- 2017
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Ingår i: Proceedings - 2017 IEEE/ACM 39th International Conference on Software Engineering: Software Engineering in Practice Track, ICSE-SEIP 2017.
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Konferensbidrag (refereegranskat)abstract
- © 2017 IEEE. Context: Open Source is getting more and more collaborative with industry. At the same time, modeling is today playing a crucial role in development of, e.g., safety critical software. Goal: However, there is a lack of research about the use of modeling in Open Source. Our goal is to shed some light into the motivation and benefits of the use of modeling and its use within project teams. Method: In this study, we perform a survey among Open Source developers. We focus on projects that use the Unified Modeling Language (UML) as a representative for software modeling. Results: We received 485 answers of contributors of 458 different Open Source projects. Conclusion: Collaboration seems to be the most important motivation for using UML. It benefits new contributors and contributors who do not create models. Teams use UML during communication and planning of joint implementation efforts.
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| 36. |
- Jolak, Rodi, et al.
(författare)
-
Software engineering whispers: The effect of textual vs. graphical software design descriptions on software design communication
- 2020
-
Ingår i: Empirical Software Engineering. - : Springer Science and Business Media LLC. - 1382-3256 .- 1573-7616. ; 25, s. 4427-4471
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Tidskriftsartikel (refereegranskat)abstract
- Context Software engineering is a social and collaborative activity. Communicating and sharing knowledge between software developers requires much effort. Hence, the quality of communication plays an important role in influencing project success. To better understand the effect of communication on project success, more in-depth empirical studies investigating this phenomenon are needed. Objective We investigate the effect of using a graphical versus textual design description on co-located software design communication. Method Therefore, we conducted a family of experiments involving a mix of 240 software engineering students from four universities. We examined how different design representations (i.e., graphical vs. textual) affect the ability toExplain,Understand,Recall, andActively Communicateknowledge. Results We found that the graphical design description is better than the textual in promotingActive Discussionbetween developers and improving theRecallof design details. Furthermore, compared to its unaltered version, a well-organized and motivated textual design description-that is used for the same amount of time-enhances the recall of design details and increases the amount of active discussions at the cost of reducing the perceived quality of explaining.
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| 37. |
- Jolak, Rodi, 1985, et al.
(författare)
-
The influence of software design representation on the design communication of teams with diverse personalities
- 2022
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Ingår i: Proceedings - 25th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2022. - New York, NY, USA : ACM. ; , s. 255-265
-
Konferensbidrag (refereegranskat)abstract
- Software is the main driver of added-value in many of the systems that surround us. While its complexity is increasing, so is the diversity of systems driven by software. To meet the challenges emerging from this combination, it is necessary to mobilize increasingly large and heterogeneous multidisciplinary teams, comprising software experts, as well as experts from various domains related to the systems driven by software. Hence, the quality of communication about software between stakeholders of different domains and with different personalities is becoming a key issue for successfully engineering software-intensive systems. The goal of this study, thus, is to investigate the effect of the representation of software design models on the communication of design decisions between stakeholders with diverse personality traits. As a result, this study finds that graphical representations of software design models are better than textual representations in enhancing the communication and increasing the productivity of stakeholders with diverse personalities.
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| 38. |
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| 39. |
- Kamulegeya, G., et al.
(författare)
-
Measurements in the Early Stage Software Start-ups: A Multiple Case Study in a Nascent Ecosystem
- 2018
-
Ingår i: Foundations of Computing and Decision Sciences. - : Walter de Gruyter GmbH. - 0867-6356 .- 2300-3405. ; 43:4, s. 251-280
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Tidskriftsartikel (refereegranskat)abstract
- Context: Software measurement is crucial to stay competitive and deliver quality software products. Problem: While much research has been done on measurement in large companies in developed countries, there is limited research on measurement in start-ups. So far there are no studies on whether these results apply to nascent ecosystems, such as those in East Africa. Goal: The aim of this study is to understand the use and perceived benefits of measurement in software start-ups in East Africa. Method: We performed a multi-case study on 19 software start-ups in hubs in Uganda and Kenya, through conducting semi-structured interviews. We transcribed and analyzed them using the content analysis technique. Results: We identified that start-ups are using a number of business and product-oriented metrics. Furthermore, we found no evidence on the use of design-oriented metrics. Nonetheless, start-ups have considerable expectations on the benefits of measuring. Finally, metrics found in this study partially differ from metrics used in start-ups in developed countries. Conclusion: There is a need to create a more inclusive characterization for measurement as early start-ups in East Africa cannot yet be represented with known models.
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| 40. |
- Kamulegeya, Grace, et al.
(författare)
-
Requirements for Measurement Dashboards and Their Benefits: A Study of Start-ups in an Emerging Ecosystem
- 2019
-
Ingår i: Proceedings - 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019, Kallithea, Greece, 28-30 Aug. 2019. - : IEEE. - 9781728134215
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Konferensbidrag (refereegranskat)abstract
- © 2019 IEEE. Metrics, often visualized with dashboards, are considered crucial to help software start-ups focus on the right aspects during the first years. However, earlier research indicates, metric choices in emerging ecosystems are not necessarily the same as in literature, which mostly focuses on developed countries. More knowledge is required to provide dashboards that suite East African software startups. The aim of this study is to identify key requirements for measurement dashboards for early software start-ups that can be used to monitor the daily health of a start-up and how these dashboards are expected to benefit the start-ups. We performed semi-structured interviews with 36 software start-ups in Uganda and Kenya to identify and categorize requirements for measurement dashboards as well as hopes associated with the use of such dashboards. Our results show that most start-ups want measurements dashboards to visualise performance.
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| 41. |
- Kamulegeya, Grace, et al.
(författare)
-
The Character of Software Startup Hubs in an Emerging Ecosystem
- 2020
-
Ingår i: Proceedings - 46th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2020.
-
Konferensbidrag (refereegranskat)abstract
- © 2020 IEEE. Software startups face numerous challenges and many fail in the first two years. Hubs, as nurturing spaces provide incubation, acceleration and co-working space as services to startups to alleviate these challenges. Previous studies have highlighted how early-stage software startups operate internally. However, given that many early-stage startups are nurtured in hubs, there is a need to understand the hub operations in respect to the startups. Using semi-structured interviews with 10 hubs in Uganda and Kenya, we characterize and analyze their current practices and operations. The results show that most hubs combine incubation, acceleration and /or co-working space as services. They offer networking and team building events in addition to value addition activities. They also provide mainly business growth incentives and notice the business and organizational effects of their incentives. They too have varied selection checklists, provide incentives to alumni startups, and measure business, and scalability metrics. Startup hubs in East Africa are therefore prepared in addressing the business aspects of startups. They too may need to improve technical mentorship and can still learn from each other's practices.
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| 42. |
- Khelladi, Djamel Eddine, et al.
(författare)
-
A semi-automatic maintenance and co-evolution of OCL constraints with (meta)model evolution
- 2017
-
Ingår i: Journal of Systems and Software. - : Elsevier BV. - 0164-1212. ; 134, s. 242-260
-
Tidskriftsartikel (refereegranskat)abstract
- © 2017 Elsevier Inc. Metamodels are core components of modeling languages to define structural aspects of a business domain. As a complement, OCL constraints are used to specify detailed aspects of the business domain, e.g. more than 750 constraints come with the UML metamodel. As the metamodel evolves, its OCL constraints may need to be co-evolved too. Our systematic analysis shows that semantically different resolutions can be applied depending not only on the metamodel changes, but also on the user intent and on the structure of the impacted constraints. In this paper, we first investigate the syntactical reasons that lead to apply different resolutions. We then propose a co-evolution approach that offers alternative resolutions while allowing the user to choose the best applicable one. We evaluated our approach on six case studies of metamodel evolution and their OCL constraints co-evolution. The results show the usefulness of alternative resolutions along with user decision to cope with real co-evolution scenarios. Within our six case studies our approach led to an average of 92% (syntactically) and 93% (semantically) matching co-evolution w.r.t. the user intent.
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| 43. |
- Khelladi, Djamel Eddine, et al.
(författare)
-
Coadapting multidimension process properties
- 2017
-
Ingår i: Journal of Software: Evolution and Process, 29 (11). - : Wiley. - 2047-7481 .- 2047-7473.
-
Konferensbidrag (refereegranskat)abstract
- © 2017 John Wiley & Sons, Ltd. In the last decades, process verification has been intensively addressed and has become an essential activity to correct and to remove errors before process execution. Typical process verification ecosystems propose to express properties to be verified on the process. A property expresses a desired behavior that must hold or not in the process execution. Processes during their lifespan are continuously adapted for several purposes: enriching, correcting, and refactoring the process. When a process is adapted, the existing properties must naturally be rechecked to ensure that no errors have been introduced, ie, the properties still hold. However, the properties may become outdated and must be coadapted w.r.t. the adapted process before to be rechecked. Otherwise, the verification may raise false alarms or may not detect newly introduced errors. In this paper, we propose a coadaptation approach of properties while considering process adaptation for the different dimensions, namely, control flow, object flow, resources, and timing. We systematically studied process changes in the multiple dimensions to identify those that do impact properties and for which we propose resolution strategies. Our preliminary evaluation shows that our resolutions strategies allow to support users in correctly coadapting impacted properties.
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| 44. |
- Khelladi, Djamel Eddine, et al.
(författare)
-
Detecting complex changes and refactorings during (Meta)model evolution
- 2016
-
Ingår i: Elsevier - Information Systems. - : Elsevier BV. - 0306-4379. ; 62, s. 220-241
-
Tidskriftsartikel (refereegranskat)abstract
- Evolution of metamodels can be represented at the finest grain by the trace of atomic changes such as add, delete, and update of elements. For many applications, like automatic correction of models when the metamodel evolves, a higher grained trace must be inferred, composed of complex changes, each one aggregating several atomic changes. Complex change detection is a challenging task since multiple sequences of atomic changes may define a single user intention and complex changes may overlap over the atomic change trace. In this paper, we propose a detection engine of complex changes that simultaneously addresses these two challenges of variability and overlap. We introduce three ranking heuristics to help users to decide which overlapping complex changes are likely to be correct. In our approach, we record the trace of atomic changes rather than computing them with the difference between the original and evolved metamodel. Thus, we have a complete and an ordered sequence of atomic changes without hidden changes. Furthermore, we consider the issue of undo operations (i.e. change canceling actions) while recording the sequence of atomic changes, and we illustrate how we cope with it. We validate our approach on 8 real case studies demonstrating its feasibility and its applicability. We observe that a full recall is always reached in all case studies and an average precision of 70.75%. The precision is improved by the heuristics up to 91% and 100% in some cases.
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| 45. |
- Khelladi, Djamel Eddine, et al.
(författare)
-
Metamodel and constraints co-evolution: A semi automatic maintenance of ocl constraints
- 2016
-
Ingår i: International Conference on Software Reuse. - Cham : Springer International Publishing. - 0302-9743 .- 1611-3349. - 9783319351216 ; 9679, s. 333-349
-
Konferensbidrag (refereegranskat)abstract
- Metamodels are core components of modeling languages to define structural aspects of a business domain. As a complement, OCL constraints are used to specify detailed aspects of the business domain, e.g. more than 750 constraints come with the UML metamodel. As the metamodel evolves, its OCL constraints may need to be co-evolved too. Our systematic analysis shows that semantically different resolutions can be applied depending not only on the metamodel changes, but also on the user intent and on the structure of the impacted constraints. In this paper, we investigate the reasons that lead to apply different resolutions. We then propose a co-evolution approach that offers alternative resolutions while allowing the user to choose the best applicable one. We evaluated our approach on the evolution of the UML case study. The results confirm the need of alternative resolutions along with user decision to cope with real co-evolution scenarios. The results show that our approach reaches 80 % of semantically correct co-evolution
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| 46. |
- Khelladi, Djamel Eddine, et al.
(författare)
-
Supporting the Co-adaption of Process Properties
- 2016
-
Ingår i: Proceedings of the International Conference on Software and Systems Process (ICSSP). - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450341882
-
Konferensbidrag (refereegranskat)abstract
- Process verification has become an essential activity to correct and to remove errors before process execution. Typical process verification ecosystems propose to express properties to be verified on the process. When a process is adapted, the existing properties must naturally be re-checked to ensure that no errors have been introduced. However, the properties may become outdated and must be co-adapted w.r.t. the adapted process before to be re-checked. Otherwise, the verification may raise false alarms or may not detect newly introduced errors. In this paper, we propose a co-adaptation approach for control-flow process properties. We systematically studied control-flow process changes to identify those that do impact properties, and for which we propose resolution strategies. Our preliminary evaluation shows that our resolutions strategies allow to support users in correctly co-adapting impacted properties.
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| 47. |
- Klunder, J., et al.
(författare)
-
Catching up with Method and Process Practice: An Industry-Informed Baseline for Researchers
- 2019
-
Ingår i: IEEE/ACM 41st International Conference on Software Engineering, 25-31 May 2019: Software Engineering in Practice (ICSE-SEIP). - : IEEE. - 9781728117607
-
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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| 48. |
- Klünder, Jil, et al.
(författare)
-
Catching up with Method and Process Practice: An Industry-Informed Baseline for Researchers
- 2019
-
Ingår i: Proceedings - 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice, ICSE-SEIP 2019. ; May 2019, s. 255-264
-
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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| 49. |
- Klünder, Jil, et al.
(författare)
-
Determining context factors for hybrid development methods with trained models
- 2020
-
Ingår i: Proceedings - 2020 IEEE/ACM International Conference on Software and System Processes, ICSSP 2020. - New York, NY, USA : ACM.
-
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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| 50. |
- Krueger, Jacob, et al.
(författare)
-
Where is my feature and what is it about? A case study on recovering feature facets
- 2019
-
Ingår i: Journal of Systems and Software. - : Elsevier BV. - 0164-1212. ; 152, s. 239-253
-
Tidskriftsartikel (refereegranskat)abstract
- Developers commonly use features to define, manage, and communicate functionalities of a system. Unfortunately, the locations of features in code and other characteristics (feature facets), relevant for evolution and maintenance, are often poorly documented. Since developers change, and knowledge fades with time, such information often needs to be recovered. Modern projects boast a richness of information sources, such as pull requests, release logs, and otherwise specified domain knowledge. However, it is largely unknown from what sources the features, their locations, and their facets can be recovered. We present an exploratory study on identifying such information in two popular, variant-rich, and long-living systems: The 3D-printer firmware Marlin and the Android application Bitcoin-wallet. Besides the available information sources, we also investigated the projects' communities, communications, and development cultures. Our results show that a multitude of information sources (e.g., commit messages and pull requests) is helpful to recover features, locations, and facets to different extents. Pull requests were the most valuable source to recover facets, followed by commit messages and the issue tracker. As many of the studied information sources are, so far, rarely exploited in techniques for recovering features and their facets, we hope to inspire researchers and tool builders with our results. (C) 2019 Elsevier Inc. All rights reserved.
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