Procedural modeling is used to generate virtual content in organized layouts of exterior and interior elements. There is a large number of existing layout generation methods, and newer approaches propose the generation of multiple layout types within the same generation session. This introduces additional constraints when manually created layout elements need to be combined with the automatically generated content. Existing approaches are either designed to work with existing elements for a single layout type, or require a high amount of manual work for adding existing elements within multiple layouts. This paper presents a method that enables the application of existing subdivision methods on multiple layout types by inserting existing content into the generation result. This method can generate test cases by creating variations of partially generated layouts for procedural modeling methods that can work with existing content.

Professional football players often need legal help in managing disputes with football clubs. The Professional Football Players Syndicate of Bosnia and Herzegovina is an organization founded with this purpose. Due to an increasing need for legal help and a large number of cases, their legal associates need systematic management of data. This work presents the first information system entirely intended for the usage by sports law professionals. It contains a desktop application where legal disputes are shown in the form of an organized dispute table. Real-time information about football players is acquired by using the TransferMarkt web API. The system was successfully used for two years, resulting in 103 documented cases involving 87 players and 31 clubs. As a result, 69.90% of disputes were archived and 43.69% of disputes resulted in agreements, indicating that the productivity of legal associates and the mediator role of the Syndicate were improved.

The visual layout has an enormous influence on human perception and is a subject of many studies, including research on web page similarity comparison. Structure-based approaches use the possibility of direct access to HTML content, whereas visual methods have widespread usage due to the ability to analyze image screenshots of entire web pages. A solution described within this paper will focus on extracting web page layout in forms needed by both above-mentioned approaches.

Subdivision of 2D polygons is the basis of many computational geometry algorithms and procedural modeling methods. Existing tools for space subdivision often require the assistance of users and cannot perform subdivision on all types of shapes (rectangular, axis-aligned, convex, and irregular). In this work, an open-source graphical desktop tool for drawing and automatic subdivision of arbitrary 2D polygons is introduced. An algorithm for subdivision of all shape types was developed. The algorithm is based on the usage of polygon bounding boxes, intersection edges and detection of polygons from newly formed edges. A dataset of 60 examples of all shape types was collected and successfully drawn by using the tool. Iterative subdivision was performed on all examples. Shape simplification was fully successful only for axis-aligned shapes. Partial simplification with leftover elements taking up less than 5% of overall polygon area was successful after 5 iterations for axis-aligned, and 10 iterations for convex and irregular shapes on average. This indicates that the tool and subdivision algorithm can be used for simplification of complex shape types with arbitrarily small leftover element area.

As virtual worlds continue to rise in popularity, so do the expectations of users for the content of virtual scenes. Virtual worlds must be large in scope and offer enough freedom of movement to keep the audience occupied at all times. For content creators, it is difficult to keep up by manually producing the surrounding content. Therefore, the application of procedural modelling techniques is required. Virtual worlds often mimic the real world, which is composed of organized and connected outdoor and indoor layouts. It is expected that all content is present on the virtual scene and that a user can navigate streets, enter buildings, and interact with furniture within a single virtual world. While there are many procedural methods for generating different layout types, they mostly focus only on one layout type, whereas complete scene generation is greatly underrepresented. This paper aims to identify the coverage of layout types by different methods because similar issues exist for the generation of content of different layout types. When creating a new method for layout generation, it is important to know if the results of existing methods can be appended to other methods. This paper presents a survey of existing procedural modelling methods, which were organized into five categories based on the core approach: pure subdivision, grammar‐based, data‐driven, optimization, and simulation. Information about the covered layout types, the possibility of user interaction during the generation process, and the input and output shape types of the generated content is provided for each surveyed method. The input and output shape types of the generated content can be useful to identify which methods can continue the generation by using the output of other methods as their input. It was concluded that all surveyed methods work for only a few different layout types simultaneously. Moreover, only 35% of the surveyed methods offer interaction with the user after completing the initial process of space generation. Most existing approaches do not perform transformations of shape types. A significant number of methods use the irregular shape type as input and generate the same shape type as the output, which is sufficient for coverage of all layout types when generating a complete virtual world.

Cause-effect graphs are a commonly used black-box testing method, and many different algorithms for converting system requirements to cause-effect graph specifications and deriving test case suites have been proposed. However, in order to test the efficiency of black-box testing algorithms on a variety of cause-effect graphs containing different numbers of nodes, logical relations and dependency constraints, a dataset containing a collection of cause-effect graph specifications created by authors of existing papers is necessary. This paper presents CEGSet, the first collection of existing cause-effect graph specifications. The dataset contains a total of 65 graphs collected from the available relevant literature. The specifications were created by using the ETF-RI-CEG graphical software tool and can be used by future authors of papers focusing on the cause-effect graphing technique. The collected graphs can be re-imported in the tool and used for the desired purposes. The collection also includes the specification of system requirements in the form of natural language from which the cause-effect graphs were derived where possible. This will encourage future work on automatizing the process of converting system requirements to cause-effect graph specifications.

Many different methods are used for generating blackbox test case suites. Test case minimization is used for reducing the feasible test case suite size in order to minimize the cost of testing while ensuring maximum fault detection. This paper presents an optimization of the existing test case minimization algorithm based on forward-propagation of the cause-effect graphing method. The algorithm performs test case prioritization based on test case strength, a newly introduced test case selection metric. The optimized version of the minimization algorithm was evaluated by using thirteen different examples from the available literature. In cases where the existing algorithm did not generate the minimum test case subsets, significant improvements of test effect coverage metric values were achieved. Test effect coverage metric values were not improved only in cases where maximum optimization was already achieved by using the existing algorithm.

Methods for automatic analysis of user interfaces are essential for a wide range of applications in computer science and software engineering. These methods are used in software security, document archiving, human-computer interaction, software engineering, and data science. Even though these methods are essential, no single research systematically lists most of the methods and their characteristics. This paper aims to give an overview of different solutions and their applications in the separate processes of automatic analysis of user interfaces. The main focus is on the techniques that analyze web page layouts and web page structure. Web pages’ style, type of content, and even structure constantly (often drastically) change, as do methods that analyze them. The fact that most methods use very different datasets and web pages of various complexities are some of the reasons that the direct comparison of methods is difficult, if not impossible. Another fact is that the vast applications of methods practically solve similar problems. With these facts in mind, in the paper, we surveyed relevant scientific articles, categorized them, and provided an overview of how these methods have developed over time.

Cause-effect graphs are often used as a method for deriving test case suites for black-box testing different types of systems. This paper represents a survey focusing entirely on the cause-effect graphing technique. A comparison of different available algorithms for converting cause-effect graph specifications to test case suites and problems which may arise when using different approaches are explained. Different types of graphical notation for describing nodes, logical relations and constraints used when creating cause-effect graph specifications are also discussed. An overview of available tools for creating cause-effect graph specifications and deriving test case suites is given. The systematic approach in this paper is meant to offer aid to domain experts and end users in choosing the most appropriate algorithm and, optionally, available software tools, for deriving test case suites in accordance to specific system priorities. A presentation of proposed graphical notation types should help in gaining a better level of understanding of the notation used for specifying cause-effect graphs. In this way, the most common mistakes in the usage of graphical notation while creating cause-effect graph specifications can be avoided.

— Cause-effect graphing is a commonly used black-box technique with many applications in practice. It is important to be able to create accurate cause-effect graph specifications from system requirements before converting them to test case tables used for black-box testing. In this paper, a new graphical software tool for creating cause-effect graph specifications is presented. The tool uses standardized graphical notation for describing different types of nodes, logical relations and constraints, resulting in a visual representation of the desired cause-effect graph which can be exported for later usage and imported in the tool. The purpose of this work is to make the cause-effect graph specification process easier for users in order to solve some of the problems which arise due to the insufficient amount of understanding of cause-effect graph elements. The proposed tool was successfully used for creating cause-effect graph specifications for small, medium and large graphs. It was also successfully used for performing different types of tasks by users without any prior knowledge of the functionalities of the tool, indicating that the tool is easy to use, helpful and intuitive. The results indicate that the usage of standardized notation is easier to understand than non-standardized approaches from other tools.

Cause-effect graphs are a popular black-box testing technique. The most commonly used approach for generating test cases from cause-effect graph specifications uses backward-propagation of forced effect activations through the graph in order to get the values of causes for the desired test case. Many drawbacks have been identified when using this approach for different testing requirements. Several algorithms for automatically generating test case suites from cause-effect graph specifications have been proposed. However, many of these algorithms do not solve the main drawbacks of the initial back-propagation approach and offer only minor improvements for specific purposes. This work proposes two new algorithms for deriving test cases from cause-effect graph representations. Forward-propagation of cause values is used for generating the full feasible test case suite, whereas multiple effect activations are taken into account for reducing the feasible test case suite size. Evaluation of the test case suites generated by using the proposed algorithms was performed by using the newly introduced test effect coverage and fault detection rate effectiveness metrics. The evaluation shows that the proposed algorithms work in real time even for a very large number of cause nodes. The results also indicate that the proposed algorithm for generating all feasible test cases generates a larger test case suite, whereas the proposed algorithm for test case suite minimization generates a smaller test case subset than the originally proposed approaches while ensuring the maximum effect coverage, fault detection rate effectiveness and a better test effect coverage ratio.