論文英語単語帳
リンク†
形容詞†
猛烈な†
- fierce
- Due to the fierce competition,
最新の†
- up-to-date
- it is also error-prone because online
code examples might not be up-to-date to the latest changes of
the mobile API frameworks.
- latest
- the latest changes of
the mobile API frameworks.
特色のある†
- distinctive
- our approach has
three distinctive characteristics.
まとめられた†
- clustered
- Android
application framework contains over 3,400 classes and 35,000
methods, clustered in more than 250 packages
指定の†
- specified
- it can generate a method call
and change to another state with specified probabilities.
必須の†
- essential
- A good understanding of the impact of different types of bugs on various project aspects is essential to improve software quality research and practice.
- Such models are essential to properly manage the major software development outcomes (e.g., cost, schedule, quality) and to build up organizational knowledge.
必要な†
software development to resulting quality in terms of defects.
異種の†
- heterogeneous
- Aggregating heterogenous data from different sources is always difficult, especially when the data definitions use different terminology or formats.
重要な†
- significant
- To be effective, however, the models must be built using a significant base of historical
data that describes numerous variations within the domain of the model (e.g., an organizational unit).
多数の†
- numerous
- To be effective, however, the models must be built using a significant base of historical
data that describes numerous variations within the domain of the model (e.g., an organizational unit).
同一の†
- identical
- Often, such data, collected over a period of time by different people, and in different
projects, do not have identical structures.
直交の<数学>†
- orthogonal
- Some categorizations are orthogonal, i.e., they address different dimensions of interest (e.g., severity vs. technical cause), so combining them results in categories that are not mutually exclusive.
排他的な†
- exclusive
- Some categorizations are orthogonal, i.e., they address different dimensions of interest (e.g., severity vs. technical cause), so combining them results in categories that are not mutually exclusive.
離散の，別々の†
- discrete
- So instead one must choose a set of discrete categories and devise mapping rules to convert the data consistently and coherently into the new categories.
![[PukiWiki]](image/wadanyan.png "[PukiWiki]")
