Pub Date : 2023-11-30DOI: 10.1007/s00766-023-00408-9
Marcela Ruiz, Jin Yang Hu, Fabiano Dalpiaz
Researchers have proposed numerous tools, methods, and techniques for establishing and maintaining software traceability. Despite its acknowledged importance, researchers argue that traceability is still “a sought-after, yet often elusive quality in software-intensive systems”. We have little evidence regarding how creating, managing, and using traceability links vary depending on factors such as organizational contexts, software development practices, and project types. We conduct an empirical study where software development practitioners express their perception regarding the value of software traceability. Via an online survey, 55 participants provided information related to their current traceability practices and needs. Furthermore, we interviewed 14 practitioners to gain a more in-depth understanding. Our study investigates the effect of two independent variables: the software development paradigm and the type of developed software system. Among the several identified findings, our analysis reveals that, although the traceability costs are an inhibitor for adopting more mature traceability practices, the respondents believe that the expected benefits still outweigh envisioned costs. Traceability is mainly performed manually: not only are automated trace retrieval tools scarce, but their offered automation is not expected to replace human involvement.
{"title":"Why don’t we trace? A study on the barriers to software traceability in practice","authors":"Marcela Ruiz, Jin Yang Hu, Fabiano Dalpiaz","doi":"10.1007/s00766-023-00408-9","DOIUrl":"https://doi.org/10.1007/s00766-023-00408-9","url":null,"abstract":"<p>Researchers have proposed numerous tools, methods, and techniques for establishing and maintaining software traceability. Despite its acknowledged importance, researchers argue that traceability is still “a sought-after, yet often elusive quality in software-intensive systems”. We have little evidence regarding how creating, managing, and using traceability links vary depending on factors such as organizational contexts, software development practices, and project types. We conduct an empirical study where software development practitioners express their perception regarding the value of software traceability. Via an online survey, 55 participants provided information related to their current traceability practices and needs. Furthermore, we interviewed 14 practitioners to gain a more in-depth understanding. Our study investigates the effect of two independent variables: the software development paradigm and the type of developed software system. Among the several identified findings, our analysis reveals that, although the traceability costs are an inhibitor for adopting more mature traceability practices, the respondents believe that the expected benefits still outweigh envisioned costs. Traceability is mainly performed manually: not only are automated trace retrieval tools scarce, but their offered automation is not expected to replace human involvement.</p>","PeriodicalId":20912,"journal":{"name":"Requirements Engineering","volume":"46 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138537662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-26DOI: 10.1007/s00766-023-00404-z
Laura Okpara, Colin Werner, Adam Murray, Daniela Damian
{"title":"The role of informal communication in building shared understanding of non-functional requirements in remote continuous software engineering","authors":"Laura Okpara, Colin Werner, Adam Murray, Daniela Damian","doi":"10.1007/s00766-023-00404-z","DOIUrl":"https://doi.org/10.1007/s00766-023-00404-z","url":null,"abstract":"","PeriodicalId":20912,"journal":{"name":"Requirements Engineering","volume":"8 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134907717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-11DOI: 10.1007/s00766-023-00407-w
Paulo Malcher, Eduardo Silva, Davi Viana, Rodrigo Santos
{"title":"What do we know about requirements management in software ecosystems?","authors":"Paulo Malcher, Eduardo Silva, Davi Viana, Rodrigo Santos","doi":"10.1007/s00766-023-00407-w","DOIUrl":"https://doi.org/10.1007/s00766-023-00407-w","url":null,"abstract":"","PeriodicalId":20912,"journal":{"name":"Requirements Engineering","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136210340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-21DOI: 10.1007/s00766-023-00406-x
Clara Marie Lüders, Tim Pietz, Walid Maalej
Abstract Stakeholders in software projects use issue trackers like JIRA or Bugzilla to capture and manage issues, including requirements, feature requests, and bugs. To ease issue navigation and structure project knowledge, stakeholders manually connect issues via links of certain types that reflect different dependencies, such as Epic-, Block-, Duplicate-, or Relate- links. Based on a large dataset of 16 JIRA repositories, we study the commonalities and differences in linking practices and link types across the repositories. We then investigate how state-of-the-art machine learning models can predict common link types. We observed significant differences across the repositories and link types, depending on how they are used and by whom. Additionally, we observed several inconsistencies, e.g., in how Duplicate links are used. We found that a transformer model trained on titles and descriptions of linked issues significantly outperforms other optimized models, achieving an encouraging average macro F1-score of 0.64 for predicting nine popular link types across all repositories (weighted F1-score of 0.73). For the specific Subtask- and Epic- links, the model achieves top F1-scores of 0.89 and 0.97, respectively. If we restrict the task to predict the mere existence of links, the average macro F1-score goes up to 0.95. In general, the shorter issue text, possibly indicating precise issues, seems to improve the prediction accuracy with a strong negative correlation of $$-$$ - 0.73. We found that Relate-links often get confused with the other links, which suggests that they are likely used as default links in unclear cases. Our findings particularly on the quality and heterogeinity of issue link data have implications for researching and applying issue link prediction in practice.
{"title":"On understanding and predicting issue links","authors":"Clara Marie Lüders, Tim Pietz, Walid Maalej","doi":"10.1007/s00766-023-00406-x","DOIUrl":"https://doi.org/10.1007/s00766-023-00406-x","url":null,"abstract":"Abstract Stakeholders in software projects use issue trackers like JIRA or Bugzilla to capture and manage issues, including requirements, feature requests, and bugs. To ease issue navigation and structure project knowledge, stakeholders manually connect issues via links of certain types that reflect different dependencies, such as Epic-, Block-, Duplicate-, or Relate- links. Based on a large dataset of 16 JIRA repositories, we study the commonalities and differences in linking practices and link types across the repositories. We then investigate how state-of-the-art machine learning models can predict common link types. We observed significant differences across the repositories and link types, depending on how they are used and by whom. Additionally, we observed several inconsistencies, e.g., in how Duplicate links are used. We found that a transformer model trained on titles and descriptions of linked issues significantly outperforms other optimized models, achieving an encouraging average macro F1-score of 0.64 for predicting nine popular link types across all repositories (weighted F1-score of 0.73). For the specific Subtask- and Epic- links, the model achieves top F1-scores of 0.89 and 0.97, respectively. If we restrict the task to predict the mere existence of links, the average macro F1-score goes up to 0.95. In general, the shorter issue text, possibly indicating precise issues, seems to improve the prediction accuracy with a strong negative correlation of $$-$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mo>-</mml:mo> </mml:math> 0.73. We found that Relate-links often get confused with the other links, which suggests that they are likely used as default links in unclear cases. Our findings particularly on the quality and heterogeinity of issue link data have implications for researching and applying issue link prediction in practice.","PeriodicalId":20912,"journal":{"name":"Requirements Engineering","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136131094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-12DOI: 10.1007/s00766-023-00405-y
Julian Frattini, Lloyd Montgomery, Jannik Fischbach, D. Méndez, D. Fucci, M. Unterkalmsteiner
{"title":"Requirements Quality Research: a harmonized Theory, Evaluation, and Roadmap","authors":"Julian Frattini, Lloyd Montgomery, Jannik Fischbach, D. Méndez, D. Fucci, M. Unterkalmsteiner","doi":"10.1007/s00766-023-00405-y","DOIUrl":"https://doi.org/10.1007/s00766-023-00405-y","url":null,"abstract":"","PeriodicalId":20912,"journal":{"name":"Requirements Engineering","volume":"abs/2309.10355 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"52464575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-14DOI: 10.1007/s00766-023-00401-2
M. H. Sadi, Eric Yu
{"title":"WEBAPIK: a body of structured knowledge on designing web APIs","authors":"M. H. Sadi, Eric Yu","doi":"10.1007/s00766-023-00401-2","DOIUrl":"https://doi.org/10.1007/s00766-023-00401-2","url":null,"abstract":"","PeriodicalId":20912,"journal":{"name":"Requirements Engineering","volume":"28 1","pages":"441 - 479"},"PeriodicalIF":2.8,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49245600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-10DOI: 10.1007/s00766-023-00400-3
Rene Noel, Jose Ignacio Panach, Oscar Pastor
Software-centric organisations design a loosely coupled organisation structure around strategic objectives, replicating this design to their business processes and information systems. Nowadays, dealing with business strategy in a model-driven development context is a challenge since key concepts such as the organisation's structure and strategic ends and means have been mostly addressed at the enterprise architecture level for the strategic alignment of the whole organisation, and have not been included into MDD methods as a requirements source. To overcome this issue, researchers have designed the LiteStrat, a business strategy modelling method compliant with MDD for developing information systems. This article presents an empirical comparison of LiteStrat and with i*, one of the most used models for strategic alignment in an MDD context. The article contributes with a literature review on the experimental comparison of modelling languages, the design of a study for measuring and comparing the semantic quality of modelling languages, and empirical evidence of the LiteStrat and i* differences. The evaluation consists of a 2 × 2 factorial experiment recruiting 28 undergraduate subjects. Significant differences favouring LiteStrat were found for models' accuracy and completeness, while no differences in modeller's efficiency and satisfaction were detected. These results yield evidence of the suitability of LiteStrat for business strategy modelling in a model-driven context.
{"title":"Including business strategy in model-driven methods: an experiment.","authors":"Rene Noel, Jose Ignacio Panach, Oscar Pastor","doi":"10.1007/s00766-023-00400-3","DOIUrl":"10.1007/s00766-023-00400-3","url":null,"abstract":"<p><p>Software-centric organisations design a loosely coupled organisation structure around strategic objectives, replicating this design to their business processes and information systems. Nowadays, dealing with business strategy in a model-driven development context is a challenge since key concepts such as the organisation's structure and strategic ends and means have been mostly addressed at the enterprise architecture level for the strategic alignment of the whole organisation, and have not been included into MDD methods as a requirements source. To overcome this issue, researchers have designed the LiteStrat, a business strategy modelling method compliant with MDD for developing information systems. This article presents an empirical comparison of LiteStrat and with i*, one of the most used models for strategic alignment in an MDD context. The article contributes with a literature review on the experimental comparison of modelling languages, the design of a study for measuring and comparing the semantic quality of modelling languages, and empirical evidence of the LiteStrat and i* differences. The evaluation consists of a 2 × 2 factorial experiment recruiting 28 undergraduate subjects. Significant differences favouring LiteStrat were found for models' accuracy and completeness, while no differences in modeller's efficiency and satisfaction were detected. These results yield evidence of the suitability of LiteStrat for business strategy modelling in a model-driven context.</p>","PeriodicalId":20912,"journal":{"name":"Requirements Engineering","volume":" ","pages":"1-30"},"PeriodicalIF":2.8,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9999337/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9705181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-12DOI: 10.1007/s00766-023-00397-9
Muhammad Yaseen, A. Mustapha, Muhammad Arif Shah, N. Ibrahim
{"title":"A hybrid technique using minimal spanning tree and analytic hierarchical process to prioritize functional requirements for parallel software development","authors":"Muhammad Yaseen, A. Mustapha, Muhammad Arif Shah, N. Ibrahim","doi":"10.1007/s00766-023-00397-9","DOIUrl":"https://doi.org/10.1007/s00766-023-00397-9","url":null,"abstract":"","PeriodicalId":20912,"journal":{"name":"Requirements Engineering","volume":"28 1","pages":"347 - 376"},"PeriodicalIF":2.8,"publicationDate":"2023-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47305741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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