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  1. Proceedings of the Second International Workshop on Requirements Engineering and Testing (RET '15)
  2. Configuring latent semantic indexing for requirements tracing
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Aligning quality requirements and test results with QUPER's roadmap view for improved high-level decision-making
It's the activities, stupid!: a new perspective on RE quality
Configuring latent semantic indexing for requirements tracing
Requirement-centric reactive testing for safety-related automotive software
Weekly round trips from norms to requirements and tests: an industrial experience report
Towards automatic constraints elicitation in pair-wise testing based on a linguistic approach: elicitation support using coupling strength
Play-testing and requirements engineering: implications for research and teaching
Visual requirements specification and automated test generation for digital applications

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Configuring latent semantic indexing for requirements tracing

Content Provider ACM Digital Library
Author Hauptmann, Benedikt Femmer, Henning Junker, Maximilian Eder, Sebastian
Abstract Latent Semantic Indexing (LSI) is an accepted technique for information retrieval that is used in requirements tracing to recover links between artifacts, e.g., between requirements documents and test cases. However, configuring LSI is difficult, because the number of possible configurations is huge. The configuration of LSI, which depends on the underlying dataset, greatly influences the accuracy of the results. Therefore, one of the key challenges for applying LSI is finding an appropriate configuration. Evaluating results for each configuration is time consuming, and therefore, automatically determining an appropriate configuration for LSI improves the applicability of LSI based methods. We propose a fully automated technique to determine appropriate configurations for LSI to recover links between requirements artifacts. We evaluate our technique on six sets of requirements artifacts from industry and academia and show that the configurations selected by our approach yield results that are almost as accurate as results from configurations based on a ground truth like known links or expert knowledge. Our approach improves the applicability of LSI in industry and academia, as researchers and practitioners do not need to determine appropriate configurations manually or provide a ground truth.
Starting Page 27
Ending Page 33
Page Count 7
File Format PDF
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2015-05-16
Access Restriction Subscribed
Content Type Text
Resource Type Article
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