While program comprehension tools often use static program analysis techniques to obtain useful information, they usually work only with sufficiently scalable techniques with limited precision. A possible improvement of this approach is to let the developer interactively reduce the scope of the code being analyzed and then apply a more precise analysis technique to the reduced scope. This paper presents a new version of the tool Slicito that allows developers to perform this kind of exploration on C\# code in Visual Studio. A common usage of Slicito is to use interprocedural data-flow analysis to identify the parts of the code most relevant for the given task and then apply symbolic execution to reason about the precise behavior of these parts. Inspired by Moldable Development, Slicito provides a set of program analysis and visualization building blocks that can be used to create specialized program comprehension tools directly in Visual Studio. We demonstrate the full scope of features on a real industrial example both in the text and in the following video: https://www.slicito.com/icpc2025video.mp4

Although integrated development environments provide developers with code structure analysis tools, program comprehension tasks still require significant manual effort. A promising direction to solve this problem is Moldable Development, a way of programming which encourages developers to build custom program visualization tools during software development process. To foster this practice within the .NET development community, we provide a tool called SLICITO, capable of analyzing and visualizing a C# program structure in a highly configurable way. Since SLICITO is implemented as an extension to computational notebooks, it takes advantage of their interactivity and visualization principles used for data analysis, and applies them in the field of program comprehension. In contrast to similar tools for C#, SLICITO is more flexible and provides more detailed information in code inspection. Its usage is shown in a video located at https://www.slicito.com/icpc video.mp4.

Compiling dynamic languages to stack-based intermediate representations used in platforms such as. NET and Java proved to be useful, mainly due to the enhanced interoperability and security. To produce the best intermediate code possible, current approaches perform a detailed flow-sensitive type analysis of the original code and utilize its results to choose the most efficient operations of the target platform. As known from the traditional compilers, the standard way to further increase program performance is using a set of transformations, which increase its efficiency while preserving its semantics. However, these transformations are not directly usable in the compilers of dynamic languages, because these operate on a higher level of abstraction; moreover, dynamic languages pose specific challenges, such as those stemming from weak typing. In this paper we propose a set of transformations which fit into the architecture of a dynamic language compiler, fitting well together with the type analysis. For evaluation purposes, we implemented them to Peachpie, a compiler of PHP to. NET. Applying the transformations during compilation of WordPress resulted in improvement of 0.6 % in the generated assembly size, 1.8% in CPU time and 0.8% in memory consumption.

In this paper we propose how to design a modular, event-driven continuous integration server. Unlike many servers in use today, the proposed solution is designed to integrate seamlessly with other development tools and services. It is based on a special purpose communication platform that can be used to govern the development process itself.

At present time, the programmers may choose from a number of streaming languages. They cover various aspects of the development process of streaming applications; however, specification of complex or runtime-dependent parts of the applications still remains a great challenge. We have analysed a large amount of requirements raised by the development of multiple data streaming parallel applications and proposed a novel language called Bobolang. It contains syntactic and semantic features which allow the programmer to naturally solve most of the problems, which we met in the design of streaming applications. The language is used to specify the structure of the whole application as well as the inner structure of each operator. Thanks to the properties of the language, Bobolang can create an optimized evaluation plan which is capable of making the best use of the available hardware resources. The language has been employed in several practical problems and it has proven itself to be a very powerful tool for the development of data-intensive parallel applications.

Malicious collectives represent one of the biggest threats for secured P2P applications. In our previous work, we proposed a trust management system called Bubble Trust targeting this problem. In this paper, we investigate the most common malicious strategies as well as the resistance the Bubble Trust uses against them. We created the simulation framework suitable for testing other TMSs in the same scenarios. Our analysis shows that the success of malicious peers in the Bubble Trust depends mainly on the amount of benefit provided to the network and that the analyzed malicious strategies cannot menace the contribution provided by the P2P network.

Scheduling of lectures at a large university or a college is a complex and specialized task with many rules but no ideal solution and no formal model and quality measure for the result. This prevents the use of any automated scheduling system, requiring each lecture to be scheduled by humans. This paper describes the MetroNG application -- a visual interactive tool for multiparametric multidimensional scheduling, which we created to address the complex issues of scheduling at universities.

Most of the enormous amount of information from the internet is available just like Web pages made for a human reader. They don't have any common interface for accessing, searching or browsing the data. Hence, it's hard to extract the semantic data from the Web, categorize them and keep them updated. For this purpose we have designed and implemented a system called AgentMat. This system is designed for efficient extraction of large amount of data from the Web pages. AgentMat processing is based on an XML-based language describing the given extraction task in a declarative way. The task description consists of system components, which connected together are able to perform the desired functionality on a general Web page. Thanks to this scraping system the raw contents from the irregularly updated and unstructured Web pages can be kept categorized and accessed together with the semantic metadata. In our pilot implementation we have built the MediaPub system, which extracts the information from various Web pages, does automatic categorizing and checks for duplicities.

The trust management in P2P networks allow to establish the trust relationships among the peers and decide whether the considered transaction will be realized. It tries to ensure safety in the extremely unsafe environments of P2P networks. In this paper we focus on the formal description of requirements of trusted P2P networks and we propose the model which is able to measure them. Our model should be adaptable to the previously published methods and allows to compare them. The fundamentals of our model are trust matrices which record the trust relationships between peers. We define similarity between trust matrices for purpose of comparison of different management systems. On the basis of this similarity we propose the criterion which is able to measure successfulness of trust management.