Knowledge Transfer in Global Software Development - Leveraging Ontologies, Tools and Assessments

Salger, Frank; Sauer, Stefan; Engels, Gregor; Baumann, Andrea

doi:10.1109/icgse.2010.46

Cited by 15 publications

(7 citation statements)

References 7 publications

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“…In our case, the meta-model acts as a reference model for behavioural requirements and as a general model of the object structure that needs to be implemented by our supporting tools. The meta-model of the relevant software engineering concepts in a particular domain is the backbone of a coherent software engineering methodology that combines engineering and quality assurance methods, modeling languages, and tools (compare Salger et al 2010;Engels and Sauer 2010). For testing behavioural requirements, we refine them into actions.…”

Section: Meta-model Of the Approachmentioning

confidence: 99%

TORC: test plan optimization by requirements clustering

et al. 2011

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Acceptance testing is a time-consuming task for complex software systems that have to fulfill a large number of requirements. To reduce this effort, we have developed a widely automated method for deriving test plans from requirements that are expressed in natural language. It consists of three stages: annotation, clustering, and test plan specification. The general idea is to exploit redundancies and implicit relationships in requirements specifications. Multi-viewpoint techniques based on RM-ODP (Reference Model for Open Distributed Processing) are employed for specifying the requirements. We then use linguistic analysis techniques, requirements clustering algorithms, and pattern-based requirements collection to reduce the total effort of testing against the requirements specification. In particular, we use linguistic analysis for extracting and annotating the actor, process and object of a requirements statement. During clustering, a similarity function is computed as a measure for the overlap of requirements. In the test plan specification stage, our approach provides capabilities for semi-automatically deriving test plans and acceptance criteria from the clustered informal textual requirements. Two patterns are applied to compute a suitable order of test activities. The generated test plans consist of a sequence of test steps and asserts that are executed or checked in the given order. We also present the supporting prototype tool TORC, which is available open source. For the evaluation of the approach, we have conducted a case study in the field of acceptance testing of a national electronic identification system. In summary, we report on lessons learned how linguistic analysis and clustering techniques can help testers in understanding the relations between requirements and for improving test planning.

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Section: Meta-model Of the Approachmentioning

confidence: 99%

TORC: test plan optimization by requirements clustering

et al. 2011

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“…Many collaborative KM solutions in SD have been introduced thus far. Some examples include ontology-based solution [3], [4], multi-agent-based [11], [12], and semantic web [13], [14]. It is found that the number of EF based approach for SD process are still insignificant [1].…”

Section: A Conceptual Modelmentioning

confidence: 99%

“…In the previous work, via a systematic literature review [1], it has been identified that there are issues in knowledge management for SD, and it is even more challenging for distributed teams. The main challenges identified are inefficient knowledge transfer and information flow [2], [3], misinterpretation, and inconsistencies [4], [5], and additionally, organizations fail to learn [6]. Due to the importance of knowledge retention and reuse, it is therefore essential to facilitate knowledge management for software process improvements in software organization [2], [7].…”

Section: Introductionmentioning

confidence: 99%

The Development and Evaluation of Experience-Based Factory Model for Software Development Process

Hanafiah¹,

Abdullah²,

Murad³

et al. 2020

Int. J. Adv. Sci. Eng. Inf. Technol.

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Knowledge, and experiences in software development have been accumulated over time throughout the project lifecycle. Previous studies have shown that the management of knowledge and experiences in software development has always been an issue. Therefore, the knowledge transfer and information flow are inefficient, misinterpretation, and inconsistencies always occur between individuals or teams, and the organization fails to learn from past projects. It is understood that efficient knowledge and experience management for software development organizations is crucial for the purpose of sharing and future reuse. This paper discusses the prototype development for a proposed model, which is based on the experience factory approach, to manage knowledge and experiences for the software development process. Discussions include the system functionalities and design, infrastructure requirements, and implementation approach. The efficiency and effectiveness of the prototype are evaluated as survey research based on Jennex & Olfman knowledge management success model. Rasch analysis is used for data reliability and validity. Results show positive feedback on the model's efficiency and effectiveness. Additionally, as agreed by most respondents, the top three of the model contributions are: to encourage learning organization, to prevent knowledge loss and to aid in decision making.

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“…Knowledge Transfer (KT) is a crucial activity in GDSD, and it can span across the entire development process [3]. Knowledge Transfer doesn't happen only between stakeholders and the development team but inside the team as well, for instance when a senior programmer mentors junior staff.…”

Section: Fig 2 Typical Software Development Activitiesmentioning

confidence: 99%

Software Quality Validation for Web Applications Developed Using Geographically Distributed Human Resources

Gheorghe¹

2015

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Developing web applications using Geographically Distributed Team Members has seen an increased popularity during the last years mainly because the rise of Open Source technologies, fast penetration of the Internet in emerging economies, the continuous quest for reduced costs as well for the fast adoption of online platforms and services which successfully address project planning, coordination and other development tasks. This paper identifies general software process stages for both collocated and distributed development and analyses the impact the use of planning, management and testing online services has on the duration, cost and quality of each stage. Given that Quality Assurance is one of the most important concerns in Geographically Distributed Software Development (GDSD), the focus is on Software Quality Validation.

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Knowledge Transfer in Global Software Development - Leveraging Ontologies, Tools and Assessments

Cited by 15 publications

References 7 publications

TORC: test plan optimization by requirements clustering

TORC: test plan optimization by requirements clustering

The Development and Evaluation of Experience-Based Factory Model for Software Development Process

Software Quality Validation for Web Applications Developed Using Geographically Distributed Human Resources

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