![]() Updating classes implementing an interface: defines the behaviour of the automatic model update after a modification on an interface. Generate "in" parameters as "final": indicates the "final" java keyword is generated for all parameters having an "in" access mode. For example, "java.io.File" instead of "File". Generate full name for used classes: indicates that the fully qualified name should be used for used classes. ![]() You must generate again after getting a lock in order to make the according files writable. Generate read only files: indicates all sources files generated from read only model elements will also be read only, to avoid unwanted modifications. In this way, you can run the generation command on the root package in read only mode, in order to only generated elements that have been checked-out. However, generation is carried out recursively on all sub-elements. If this tickbox is checked, the Java file is not generated if the element has not been checked-out. For example, generate a class containing an attribute without type.ĭo not generate read-only elements: indicates whether or not Java source generation is deactivated for elements in read only mode. When active, generation is stopped for each file containing a warning, rather than ignoring it. Treat warnings as errors: indicates if the specific Java consistency controls during generation are active. Modelio Java Designer uses a specific XML file to define the mapping of base types, containers and the default creation of accessors.Ĭopyright file: indicates a file’s content that will be added at the beginning of each generated class.It must contain the word "Copyright" to avoid beeing reversed. In the evaluation and analyzing the suitable integration method, we applied the different methods on homogeneous mobile applications and found that using ontology increased the detection percentage approximately by 11.3% in addition to guaranteed consistency.Customization file: indicates where the default behaviour can be found in the "javaCustomizationFile" XML file, located in the module’s installation directory, into the workspace. The results showed that there was a high positive relation between Modelio and Protégé which implies that the combination between both increases the accuracy level of the detection of anti-patterns. The results also showed the correlation between the selected tools which we used as Modelio, the Protégé platform, and the OLED editor of the OntoUML. "The anti-patterns in the class group" is the most group that has the maximum occurrences of anti-patterns and "The anti-patterns in the operation group" is the smallest one that has the minimum occurrences of the anti-patterns which are detected by the proposed method. The proposed method introduced a new classification of the anti-patterns divided into four groups. Results The proposed method detected 15 semantic and structural design anti-patterns which have appeared 1,262 times in a random sample of 29 mobile applications. We demonstrate a semantic integration method to reduce the incidence of anti-patterns using the ontology merging on mobile applications. Selecting a browser is not a criterion in this method because the proposed method is applied on a design level. We choose 29 mobile applications randomly. We present and test a new method that generates the OWL ontology of mobile applications and analyzes the relationships among object-oriented anti-patterns and offer methods to resolve the anti-patterns by detecting and treating 15 different design's semantic and structural anti-patterns that occurred in analyzing of 29 mobile applications. The proposed method is via reverse-engineering and ontology by using a UML modeling environment, an OWL ontology-based platform and ontology-driven conceptual modeling. Methods We proposed a general method to detect mobile applications' anti-patterns that can detect both semantic and structural design anti-patterns. Additionally, it guides developers to refactor their applications and consequently enhance their quality. Thus, the automatic detection of anti-patterns is a vital process that facilitates both maintenance and evolution tasks. However, catering to these imperatives may bring about poor outline decisions on design choices, known as anti-patterns, which may possibly corrupt programming quality and execution. Applications must be produced rapidly and advance persistently in order to fit new client requirements and execution settings. Abstract : Background Portable-devices applications (Android applications) are becoming complex software systems that must be developed quickly and continuously evolved to fit new user requirements and execution contexts.
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