| 1. |
- Abbas, Muhammad, et al.
(författare)
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Automated Reuse Recommendation of Product Line Assets Based on Natural Language Requirements
- 2020
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Ingår i: Lecture Notes in Computer Science. - Cham : Springer Science and Business Media Deutschland GmbH. - 9783030646936 ; , s. 173-189, s. 173-189, s. 173-189
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Konferensbidrag (refereegranskat)abstract
- Software product lines (SPLs) are based on reuse rationale to aid quick and quality delivery of complex products at scale. Deriving a new product from a product line requires reuse analysis to avoid redundancy and support a high degree of assets reuse. In this paper, we propose and evaluate automated support for recommending SPL assets that can be reused to realize new customer requirements. Using the existing customer requirements as input, the approach applies natural language processing and clustering to generate reuse recommendations for unseen customer requirements in new projects. The approach is evaluated both quantitatively and qualitatively in the railway industry. Results show that our approach can recommend reuse with 74% accuracy and 57.4% exact match. The evaluation further indicates that the recommendations are relevant to engineers and can support the product derivation and feasibility analysis phase of the projects. The results encourage further study on automated reuse analysis on other levels of abstractions.
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| 2. |
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| 3. |
- Abbas, Muhammad, et al.
(författare)
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Is Requirements Similarity a Good Proxy for Software Similarity? : An Empirical Investigation in Industry
- 2021
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Ingår i: <em>Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) </em>27th International Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2021, 12 April 2021 - 15 April 2021. - Cham : Springer Science and Business Media Deutschland GmbH. - 9783030731274 ; , s. 3-18, s. 3-18
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Konferensbidrag (refereegranskat)abstract
- [Context and Motivation] Content-based recommender systems for requirements are typically built on the assumption that similar requirements can be used as proxies to retrieve similar software. When a new requirement is proposed by a stakeholder, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn identify previously developed code. [Question/problem] Several NLP approaches for similarity computation are available, and there is little empirical evidence on the adoption of an effective technique in recommender systems specifically oriented to requirements-based code reuse. [Principal ideas/results] This study compares different state-of-the-art NLP approaches and correlates the similarity among requirements with the similarity of their source code. The evaluation is conducted on real-world requirements from two industrial projects in the railway domain. Results show that requirements similarity computed with the traditional tf-idf approach has the highest correlation with the actual software similarity in the considered context. Furthermore, results indicate a moderate positive correlation with Spearman’s rank correlation coefficient of more than 0.5. [Contribution] Our work is among the first ones to explore the relationship between requirements similarity and software similarity. In addition, we also identify a suitable approach for computing requirements similarity that reflects software similarity well in an industrial context. This can be useful not only in recommender systems but also in other requirements engineering tasks in which similarity computation is relevant, such as tracing and categorization.
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| 4. |
- Abbas, Muhammad, et al.
(författare)
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Keywords-based test categorization for Extra-Functional Properties
- 2020
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Ingår i: 2020 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW). - : IEEE. - 9781728110752 ; , s. 153-156
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Konferensbidrag (refereegranskat)abstract
- Categorizing existing test specifications can provide insights on coverage of the test suite to extra-functional properties. Manual approaches for test categorization can be time-consuming and prone to error. In this short paper, we propose a semi-automated approach for semantic keywords-based textual test categorization for extra-functional properties. The approach is the first step towards coverage-based test case selection based on extra-functional properties. We report a preliminary evaluation of industrial data for test categorization for safety aspects. Results show that keyword-based approaches can be used to categorize tests for extra-functional properties and can be improved by considering contextual information of keywords.
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| 5. |
- Abbas, Muhammad, et al.
(författare)
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Making Sense of Failure Logs in an Industrial DevOps Environment
- 2023
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Ingår i: Advances in Intelligent Systems and Computing book series (AISC,volume 1445). - : Springer International Publishing. ; , s. 217-226
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Konferensbidrag (refereegranskat)abstract
- Processing and reviewing nightly test execution failure logs for large industrial systems is a tedious activity. Furthermore, multiple failures might share one root/common cause during test execution sessions, and the review might therefore require redundant efforts. This paper presents the LogGrouper approach for automated grouping of failure logs to aid root/common cause analysis and for enabling the processing of each log group as a batch. LogGrouper uses state-of-art natural language processing and clustering approaches to achieve meaningful log grouping. The approach is evaluated in an industrial setting in both a qualitative and quantitative manner. Results show that LogGrouper produces good quality groupings in terms of our two evaluation metrics (Silhouette Coefficient and Calinski-Harabasz Index) for clustering quality. The qualitative evaluation shows that experts perceive the groups as useful, and the groups are seen as an initial pointer for root cause analysis and failure assignment.
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| 6. |
- Abbas, Muhammad, et al.
(författare)
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MBRP : Model-Based Requirements Prioritization Using PageRank Algorithm
- 2019
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Ingår i: 2019 26th Asia-Pacific Software Engineering Conference (APSEC). - : IEEE conference proceedings. - 9781728146485 ; , s. 31-38
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Konferensbidrag (refereegranskat)abstract
- Requirements prioritization plays an important role in driving project success during software development. Literature reveals that existing requirements prioritization approaches ignore vital factors such as interdependency between requirements. Existing requirements prioritization approaches are also generally time-consuming and involve substantial manual effort. Besides, these approaches show substantial limitations in terms of the number of requirements under consideration. There is some evidence suggesting that models could have a useful role in the analysis of requirements interdependency and their visualization, contributing towards the improvement of the overall requirements prioritization process. However, to date, just a handful of studies are focused on model-based strategies for requirements prioritization, considering only conflict-free functional requirements. This paper uses a meta-model-based approach to help the requirements analyst to model the requirements, stakeholders, and inter-dependencies between requirements. The model instance is then processed by our modified PageRank algorithm to prioritize the given requirements. An experiment was conducted, comparing our modified PageRank algorithm's efficiency and accuracy with five existing requirements prioritization methods. Besides, we also compared our results with a baseline prioritized list of 104 requirements prepared by 28 graduate students. Our results show that our modified PageRank algorithm was able to prioritize the requirements more effectively and efficiently than the other prioritization methods.
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| 7. |
- Abbas, Muhammad, et al.
(författare)
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On the relationship between similar requirements and similar software : A case study in the railway domain
- 2023
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Ingår i: Requirements Engineering. - : Springer Science and Business Media Deutschland GmbH. - 0947-3602 .- 1432-010X. ; 28, s. 23-47
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Tidskriftsartikel (refereegranskat)abstract
- Recommender systems for requirements are typically built on the assumption that similar requirements can be used as proxies to retrieve similar software. When a stakeholder proposes a new requirement, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn, identify previously developed code. Several NLP approaches for similarity computation between requirements are available. However, there is little empirical evidence on their effectiveness for code retrieval. This study compares different NLP approaches, from lexical ones to semantic, deep-learning techniques, and correlates the similarity among requirements with the similarity of their associated software. The evaluation is conducted on real-world requirements from two industrial projects from a railway company. Specifically, the most similar pairs of requirements across two industrial projects are automatically identified using six language models. Then, the trace links between requirements and software are used to identify the software pairs associated with each requirements pair. The software similarity between pairs is then automatically computed with JPLag. Finally, the correlation between requirements similarity and software similarity is evaluated to see which language model shows the highest correlation and is thus more appropriate for code retrieval. In addition, we perform a focus group with members of the company to collect qualitative data. Results show a moderately positive correlation between requirements similarity and software similarity, with the pre-trained deep learning-based BERT language model with preprocessing outperforming the other models. Practitioners confirm that requirements similarity is generally regarded as a proxy for software similarity. However, they also highlight that additional aspect comes into play when deciding software reuse, e.g., domain/project knowledge, information coming from test cases, and trace links. Our work is among the first ones to explore the relationship between requirements and software similarity from a quantitative and qualitative standpoint. This can be useful not only in recommender systems but also in other requirements engineering tasks in which similarity computation is relevant, such as tracing and change impact analysis.
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| 8. |
- Abbas, Muhammad, et al.
(författare)
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Product line adoption in industry : an experience report from the railway domain
- 2020
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Ingår i: SPLC '20: Proceedings of the 24th ACM Conference on Systems and Software Product Line: Volume A. - New York, NY, USA : Association for Computing Machinery. - 9781450375696 ; , s. 130-141, s. 130-141
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Konferensbidrag (refereegranskat)abstract
- The software system controlling a train is typically deployed on various hardware architectures and must process various signals across those deployments. The increase of such customization scenarios and the needed adherence of the software to various safety standards in different application domains has led to the adoption of product line engineering within the railway domain. This paper explores the current state-of-practice of software product line development within a team developing industrial embedded software for a train propulsion control system. Evidence is collected using a focus group session with several engineers and through inspection of archival data. We report several benefits and challenges experienced during product line adoption and deployment. Furthermore, we identify and discuss improvement opportunities, focusing mainly on product line evolution and test automation.
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| 9. |
- Abbas, Muhammad, et al.
(författare)
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Requirements dependencies-based test case prioritization for extra-functional properties
- 2019
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Ingår i: Proceedings - 2019 IEEE 12th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2019. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728108889 ; , s. 159-163
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Konferensbidrag (refereegranskat)abstract
- The use of requirements' information in testing is a well-recognized practice in the software development life cycle. Literature reveals that existing tests prioritization and selection approaches neglected vital factors affecting tests priorities, like interdependencies between requirement specifications. We believe that models may play a positive role in specifying these inter-dependencies and prioritizing tests based on these inter-dependencies. However, till date, few studies can be found that make use of requirements inter-dependencies for test case prioritization. This paper uses a meta-model to aid modeling requirements, their related tests, and inter-dependencies between them. The instance of this meta-model is then processed by our modified PageRank algorithm to prioritize the requirements. The requirement priorities are then propagated to related test cases in the test model and test cases are selected based on coverage of extra-functional properties. We have demonstrated the applicability of our proposed approach on a small example case.
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| 10. |
- Abbas, Muhammad, et al.
(författare)
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Requirements-Driven Reuse Recommendation
- 2021
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Ingår i: Proceedings of the 25th ACM International Systems and Software Product Line Conference - Volume A. - New York, NY, USA : Association for Computing Machinery.
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Konferensbidrag (refereegranskat)abstract
- This tutorial explores requirements-based reuse recommendation for product line assets in the context of clone-and-own product lines.
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