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BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 9b. Translation of a tab for all languages

After checking a few (or all!) languages for instance and pressing the Ok button , we obtain the windows shown in figure 9a, or respectively 9b for all languages. Here we can add one or more missing translations, or modify one or more of the existing translations accordingly. All the data within the view cluster can be translated into any language supported by the system.

BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 8. GoTo -> Translation Option

For example, we select in the view cluster the tab called “Forecasting” and then choose Goto -> Translation (figure 8). After selecting Goto -> Translation, we obtain a selecting window for the desired languages where the user can check one or more languages to translate those tabs or areas into.

BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 9a. Translation of a tab for certain languages

BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 7. Dialog structure of the View Cluster

Field dependency has been generated automatically and as a result the following desired structure has been achieved (figure 7). After populating the database tables with data in different languages with the help of the view cluster, the popup has been adapted in order to support the translation of the tabs and areas. Supplementary internal tables have been defined in the function module POPUP_FLEX, in order to copy data from the translation tables. The corresponding SELECT statements have been embedded in TRY-CATCH blocks, in order to prevent short dumps due to faulty selection processes.

BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 6. View cluster TAFC

For all these tables and views, table maintenance generators have been created and activated, in order to have the possibility to manage individual datasets in every table and view. The corresponding names of those function groups for the table maintenance generators are the same names as those for the views. The purpose of these maintenance views is only to take care of the input data more efficiently. These views will be used later in the view cluster, which ensures a hierarchical order of the data. Therefore, the maintenance views will also include the predecessor, in order to facilitate linking in the field dependency tab of the view cluster (Swapna, 2007). These three maintenance views are embedded in the following view cluster (figure 6)

BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 5. Maintenance Views

Beside the tabs and the areas, the database table FLD also contains the fields TABLENAME and FIELD, which suggest the related parameters, whom input may be updated at runtime. Through standard SAP functionality the tables in BASIS, respectively their fields are by default translated in the login language of the user. So in the fields TABLENAME and FIELD of the FLD table, we will obtain, in the user login language, the names of the tables and fields from BASIS via the foreign keys to the table DD03L for TABLENAME and to the table DD02L for FIELD. Beside the database tables, 3 maintenance views have been created, TABV, AREV and FLDV, for the tabs, areas and fields of the popup (figure 5). We have chosen maintenance views instead of database views to be able to use them in the view cluster.

BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 2. Content of the single database table in the previous implementation

In the previous implementation there has been used a single database table which did not provide a consistent overview of existing tabs, areas and fields, as well as of the languages, in which a specific field of an area or tab was translated. So, it was difficult to maintain this database table by the customizing end-users in different languages, because every update of a tab, area or field required a number of actions in this table which had to be done manually and very carefully, requiring much time and attention. The number of rows of this table was very large and the content looked like the one shown in figure 2.

BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 4. Table structure and relationships

The structure of the tables, primary keys and foreign keys are shown in figure 4.The names of the fields in the database tables are relevant for their content. Only the SPRAS field in the translation-tables TABT and ARET must be explained: SPRAS is a system-field which stands for the language and is used in order to maintain the languages in which the tab/area is translated into.

BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 1. Popup layout for the Material Master Data Application

The Material Master Data Application provides an update popup layout, including tabs, areas and fields (also customer-specific fields). Each tab consists of one or more areas and each area of one or more fields, similar to the example below (figure 1). The application is called flexible because the user must have the possibility to add, delete, reorder or rename tabs, areas and fields.

BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 3. The logical data model of tables and views

The five tables, named TAB, TABT, AREA, ARET and FLD, are combined within three views (TABV, AREV and FLDV) which build a cluster view, TAFC (figure 3).

opencc-by-4.0May 2024View details →

Analyzing the Dependability of Large Language Models for Code Clone Generation.

<div> data.zip:  This dataset includes a collection of ten LeetCode programming problems used in the study "Analyzing the Dependability of Large Language Models for Code Clone Generation". At the top level, you will find a CSV file containing all the initial LeetCode data. Each subdirectory at this level represents a specific LeetCode problem. Within these subdirectories, you will find the original solutions, their behaviors, the input corpus, as well as folders dedicated to various temperatures, models, and code cloning tasks. Additionally, within the "repeated" folder, you will find the original LLM-generated snippets, the preprocessed snippets with the snippet behavior, and the results. characterizing_code_clones_project.zip:  This zipped directory encompasses the core scripts and results used in the "Characterizing Code Clones of LLMs" research. The common folder was used to run the whole pipeline, the various parts of the pipeline are each in a folder as well as the various data analysis scripts!    </div>

opencc-by-4.0May 2024View details →

Analyzing the Dependability of Large Language Models for Code Clone Generation

data.zip:  This dataset includes a collection of ten LeetCode programming problems used in the study "Analyzing the Dependability of Large Language Models for Code Clone Generation". At the top level, you will find a CSV file containing all the initial LeetCode data. Each subdirectory at this level represents a specific LeetCode problem. Within these subdirectories, you will find the original solutions, their behaviors, the input corpus, as well as folders dedicated to various temperatures, models, and code cloning tasks. Additionally, within the "repeated" folder, you will find the original LLM-generated snippets, the preprocessed snippets with the snippet behavior, and the results. characterizing_code_clones_project.zip:  This zipped directory encompasses the core scripts and results used in the "Characterizing Code Clones of LLMs" research. The common folder was used to run the whole pipeline, the various parts of the pipeline are each in a folder as well as the various data analysis scripts!

opencc-by-4.0Oct 2024View details →

Artifacts for paper "CITYWALK: Enhancing LLM-Based C++ Unit Test Generation via Project-Dependency Awareness and Language-Specific Knowledge" submitted to TOSEM

The project includes the data and code used in the submitted TOSEM paper titled "CITYWALK: Enhancing LLM-Based C++ Unit Test Generation via Project-Dependency Awareness and Language-Specific Knowledge"