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NALABS Natural Language Analysis of Bad Smells in Incremental Engineering
- Project
- 20023 SmartDelta
- Type
- New product
- Description
NALABS is designed to analyze software requirements and identify potential bad smells that may indicate issues in the requirement's quality or clarity. The tool reads requirements from Excel or JSON files, processes them using various linguistic techniques, and outputs report files containing the detected bad smells for each requirement.
- Contact
- Eduard Paul Enoiu
- eduard.paul.enoiu@mdu.se
- Research area(s)
- incremental requirements engineering
- Technical features
NALABS performs the following analysis on each requirement:
- Detects ambiguous words
- Measures readability using the Flesch Reading Ease score
- Calculates subjectivity to identify potential weaknesses in the requirement
- Ensures that the requirement contains specific keywords
- Check if the requirement is security-related
- Integration constraints
NALABSpy: Dependencies pandas openpyxl spacy textstat textblob
- Targeted customer(s)
Requirements Engineers, Designers
- Conditions for reuse
NALABS's source code is released under the MIT license
- Confidentiality
- Public
- Publication date
- 12-10-2023
- Involved partners
- Mälardalen University (SWE)
- ALSTOM Rail Sweden AB (SWE)
