SwePub - search: WFRF:(Nilson Mayra)

Enumeration	Reference	Cover	Find
1.	Nilson, Mayra, et al. (author) Do Internal Software Quality Tools Measure Validated Metrics? 2019 In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 11915 LNCS, s. 637-648 Conference paper (peer-reviewed)abstract Internal software quality determines the maintainability of the software product and influences the quality in use. There is a plethora of metrics which purport to measure the internal quality of software, and these metrics are offered by static software analysis tools. To date, a number of reports have assessed the validity of these metrics. No data are available, however, on whether metrics offered by the tools are somehow validated in scientific studies. The current study covers this gap by providing data on which tools and how many validated metrics are provided. The results show that a range of metrics that the tools provided do not seem to be validated in the literature and that only a small percentage of metrics are validated in the provided tools.

Nilson, Mayra, et al. (author)
Do Internal Software Quality Tools Measure Validated Metrics?
2019
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 11915 LNCS, s. 637-648
Conference paper (peer-reviewed)abstract
- Internal software quality determines the maintainability of the software product and influences the quality in use. There is a plethora of metrics which purport to measure the internal quality of software, and these metrics are offered by static software analysis tools. To date, a number of reports have assessed the validity of these metrics. No data are available, however, on whether metrics offered by the tools are somehow validated in scientific studies. The current study covers this gap by providing data on which tools and how many validated metrics are provided. The results show that a range of metrics that the tools provided do not seem to be validated in the literature and that only a small percentage of metrics are validated in the provided tools.

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