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To assure high software quality for large-scale industrial software systems, traditional approaches of software quality assurance, such as software testing and performance engineering, have been widely used within Alibaba, the world's largest retailer, and one of the largest Internet companies in the world. However, there still exists a high demand for software quality assessment to achieve high sustainability of business growth and engineering culture in Alibaba. To address this issue, we develop an industrial solution for software quality assessment by following the GQM paradigm in an industrial setting. Moreover, we integrate multiple assessment methods into our solution, ranging from metric selection to rating aggregation. Our solution has been implemented, deployed, and adopted at Alibaba: (1) used by Alibaba's Business Platform Unit to continually monitor the quality for 60+ core software systems; (2) used by Alibaba's R&D Efficiency Unit to support group-wide quality-aware code search and automatic code inspection. This paper presents our proposed industrial solution, including its techniques and industrial adoption, along with the lessons learned during the development and deployment of our solution.
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A Comprehensive Enterprise System Metamodel for Quality Assurance
One of the biggest challenges in code quality assurance is the amount of code that needs to be reviewed at an instance before the code is deployed on production. Reviewers need to check not only coding practices and formatting but also the meaning of the code and its compliance with requirements. Enterprise systems are notoriously known for the large codebase, challenging business logic, and advanced code constructs, which require significant resources for code review. However, enterprise systems use coding constructs that reveal aspects and constraints about the business logic, such as validation, database connection, and API. We extract these aspects and their relationships into a comprehensive metamodel. Next, we persist the metamodel into a graph database and conduct quality assurance checks via database queries. This method significantly reduces the amount of information that needs to be processed while maintaining key enterprise aspects. The method enables system administrators or project managers to discover defects and inconsistencies without reading the code.
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- Award ID(s):
- 1854049
- PAR ID:
- 10310335
- Date Published:
- Journal Name:
- Information Science and Applications. Lecture Notes in Electrical Engineering
- Volume:
- 739
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1007/978-981-33-6385-4_23
