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Python has emerged as one of the most popular programming languages, extensively utilized in domains such as machine learning, data analysis, and web applications. Python’s dynamic nature and extensive usage make it an attractive candidate for dynamic program analysis. However, unlike for other popular languages, there currently is no comprehensive benchmark suite of executable Python projects, which hinders the development of dynamic analyses. This work addresses this gap by presenting DyPyBench, the first benchmark of Python projects that is large-scale, diverse, ready-to-run (i.e., with fully configured and prepared test suites), and ready-to-analyze (by integrating with the DynaPyt dynamic analysis framework). The benchmark encompasses 50 popular open-source projects from various application domains, with a total of 681k lines of Python code, and 30k test cases. DyPyBench enables various applications in testing and dynamic analysis, of which we explore three in this work: (i) Gathering dynamic call graphs and empirically comparing them to statically computed call graphs, which exposes and quantifies limitations of existing call graph construction techniques for Python. (ii) Using DyPyBench to build a training data set for LExecutor, a neural model that learns to predict values that otherwise would be missing at runtime. (iii) Using dynamically gathered execution traces to mine API usage specifications, which establishes a baseline for future work on specification mining for Python. We envision DyPyBench to provide a basis for other dynamic analyses and for studying the runtime behavior of Python code.

Java has emerged as a popular programming language and platform for Web applications. JavaBeans defines the software component model in the Java programming language that is used for creating reusable, coarse‐grained components. Beans are used in numerous complementary technologies including Enterprise JavaBeans, Java Abstract Windowing Toolkit, Java Database Connectivity, JavaMail, and Java Management Extensions to create software components. Beans provide a hybrid of object‐oriented and loosely coupled architectural styles, where the interaction between components is in the form of both events and method calls. This chapter focuses on the support for component technology in Java, specifically in the form of JavaBeans and its technology variants that fulfil the needs of Web application development. The chapter also discusses the role of JavaBeans and its technology variants in architecture‐based software development.

Refactoring, the process of improving the internal code structure of a software system without altering its external behavior, is widely applied during software development. Understanding how developers refactor source code can help gain better understanding of the software development process and the relationship between various versions of a system. Refactoring detection tools have been developed for many popular programming languages, such as Java (e.g., REFACTORINGMINER and REF-FINDER) but, quite surprisingly, this is not the case for Python, a widely used programming language.Inspired by REFACTORING MINER, we present PYREF, a tool that automatically detects method-level refactoring operations in Python projects. We evaluated PYREF against a manually built oracle and compared it with a PYTHON-ADAPTED REFACTOR-INGMINER, which converts Python program to Java and detects refactoring operations with REFACTORING MINER. Our results indicate that PYREF can achieve satisfactory precision and detect more refactorings than the current state-of-the-art.

The recent successful application of Datalog in a number of advanced projects, has renewed the interest in Datalog-based systems for developing real-world applications. Indeed, in the last few years Datalog has been successifully applied in many different areas of computer science, including: Artificial Intelligence, Data Extraction, Information Integration and Knowledge Management. Interestingly, besides the scientific applications, Datalog-based systems were also applied for developing some industrial systems. Nonetheless, in order to boost the adoption of Datalog-based technologies in the scientific community and especially in industry, it is important to provide effective programming tools, which support the activities of researchers and implementors and simplify users' interactions with Datalog systems. Indeed, development frameworks and tools provide indispensable means for assisting and simplifying application development. For this reason, the most popular programming languages and also commercial off-of- the-shelf software products (e.g., DBMSs) are always complemented by Integrated Development Environments (IDE) and Software Development Kits (SDK).

The ACM/ICPC is recognized as the largest and highest level international collegiate programming contest in the world, and it is one of the most important ways to train and select top students in computer science worldwide. Currently, C++ is the most popular and practical computer advanced programming language in the world. It is an important professional main course and one of the main tools for teaching programming and computer software development. It has become a programming course for universities and colleges. With further deepening of education reform, the paperless examination has become an important sign of the college examination reform, and its advantages have become more and more obvious. Also, the paperless examination has gradually become a trend of various examinations. Although there have been some paperless examination systems, but these systems usually can only automatically score four types of objective questions, including true and false questions, fill-in-the-blank questions, single-choice questions and multiple-choice questions. These paperless examination systems are still unable to conduct fair and impartial automatic scoring for programming questions which are however important subjective questions. In response to this problem, based on the ACM/ICPC platform, we propose a new design method for the C++ paperless examination system, which realizes the automatic scoring of C++ examinations. The system can greatly improve the flexibility, fairness, impartiality, credibility and work efficiency of the examination. Our design system can be an important platform for deepening the teaching reform of colleges and universities, promoting the innovation of C++ teaching, and improving the efficiency of college examinations. Therefore, it has a certain promotion and demonstration value.

ADA is a popular programming language that was named after Lady Ada Lovelace (1815-1852) and recommended by Department of Defense, USA, for development of large scale safety-critical software systems. In this Fast Abstract, ADA is reinterpreted as Autonomous, Dependable and Affordable. It is argued that future software systems should be ADA. A few affordable techniques are briefly described to highlight how to make software systems ADA.

The object-oriented theory has been widely used in software design and development and Java programming language is a popular object-oriented programming language for computer science related majors in higher education. With the huge demand for intelligent manufacturing employees in the work market, more and more universities have listed Java programming language in their curriculum for non-CS undergraduates. However, learning object-oriented programming languages, such as Java, is tough even for CS students. This paper presents how to improve non-CS undergraduate students’ learning outcomes of java language by adopting industry standard professional integrated development tool Eclipse and interactive visual educational tool BlueJ. Our Java programming language course is an alternative 8-week course including 16 h lecture and 16 h lab. Forty-seven junior students from mechanical engineering major were divided into two groups, 23 in the control group (CG) and 24 in the experimental group (EG). Students in both groups used Eclipse to write and run programs during the course while BlueJ was adopted to demonstrate the object-oriented concepts during the fifth and sixth weeks only for students in the EG. A pre-test, which was taken by students from both groups, shows no statistical differences in programming knowledge between the two groups. Results from the post-test at the end of the sixth week show students in EG achieved better performance than students in CG. Results of the survey for the EG reveal that students thought BlueJ was helpful for mastering the concepts of object-oriented programming.KeywordsJava programmingLearning outputHigher educationInteractiveVisualBlueJEclipse

Since its inception in 1996, aspect-oriented programming (AOP) has been believed to reduce the effort required to maintain software systems by replacing cross-cutting code with aspects. However, little convincing empirical evidence exists to support this claim, while several studies suggest that AOP brings new obstacles to maintainability. This paper discusses two controlled experiments conducted to evaluate the impact of AspectJ (the most mature and popular aspect-oriented programming language) versus Java on software evolvability. We consider evolvability as the ease with which a software system can be updated to fulfill new requirements. Since a minor language was compared to the mainstream, the experiments were designed so as to anticipate that the participants were much more experienced in one of the treatments. The first experiment was performed on 35 student subjects who were asked to comprehend either Java or AspectJ implementation of the same system, and perform the corresponding comprehension tasks. Participants of both groups achieved a high rate of correct answers without a statistically significant difference between the groups. Nevertheless, the Java group significantly outperformed the AspectJ group with respect to the average completion time. In the second experiment, 24 student subjects were asked to implement (in a non-invasive way) two extension scenarios to the system that they had already known. Each subject evolved either the Java version using Java or the AspectJ version using AspectJ. We found out that a typical AspectJ programmer needs significantly fewer atomic changes to implement the change scenarios than a typical Java programmer, but we did not observe a significant difference in completion time. The overall result indicates that AspectJ has a different effect on two sub-characteristics of the evolvability: understandability and changeability. While AspectJ decreases the former, it improves one aspect of the latter.

the University of Amsterdam, May 20-31, 1974.This Tract collects the lecture notes of five of the courses given.The sixth course, given by Dr. R. Kowalski on Predicate Logic as a Programming Language in Artificial Intelligence, is scheduled to appear elsewhere.We are very grateful to the Netherlands Organization for the Advancement of Pure Research (Z.W.O.)

Regular expressions (regexes) are a popular and powerful means of automatically manipulating text. Regexes are also an understudied denial of service vector (ReDoS). If a regex has super-linear worst-case complexity, an attacker may be able to trigger this complexity, exhausting the victim’s CPU resources and causing denial of service. Existing research has shown how to detect these superlinear regexes, and practitioners have identified super-linear regex anti-pattern heuristics that may lead to such complexity. In this paper, we empirically study three major aspects of ReDoS that have hitherto been unexplored: the incidence of super-linear regexes in practice, how they can be prevented, and how they can be repaired. In the ecosystems of two of the most popular programming languages — JavaScript and Python – we detected thousands of super-linear regexes affecting over 10,000 modules across diverse application domains. We also found that the conventional wisdom for super-linear regex anti-patterns has few false negatives but many false positives; these anti-patterns appear to be necessary, but not sufficient, signals of super-linear behavior. Finally, we found that when faced with a super-linear regex, developers favor revising it over truncating input or developing a custom parser, regardless of whether they had been shown examples of all three fix strategies. These findings motivate further research into ReDoS, since many modules are vulnerable to it and existing mechanisms to avoid it are insufficient. We believe that ReDoS vulnerabilities are a larger threat in practice than might have been guessed.

The object of research in the article are the tools and capabilities of the C# programming language for the implementation of cybersecurity analysis software in local computer networks and computer-integrated systems. The relevance of the study is due to the importance of information security of computer and computer-integrated systems in government, military-industrial complex, private business etc., and due to the importance of training cybersecurity professionals in higher education to consider teaching examples in popular programming languages. The goal of the work is to research the possibilities of the C# programming language for the development of software that analyzes cybersecurity in local computer networks and computer-integrated systems. The tasks to be solved are: to develop software for scanning network device ports in computer networks and computer-integrated systems for information security audit, using tools and libraries of the C# programming language, to research the benefits and possibilities of using this programming language for this task. Research methods: theory of computer networks, object-oriented programming, theory of algorithms and data structures, theory of software testing. Conclusions. In this paper the possibilities and advantages of the C# programming language for developing cybersecurity analysis software for computer and computer-integrated systems were explored. In the course of work software that analyzes information security in local computer networks and computer-integrated systems was developed. This software can be used for educational purposes in learning the C# programming language and cybersecurity of computer systems. The developed software has the potential to be further improved and applied in various fields to test the cybersecurity of local computer networks and computer-integrated technologies.

Частотні словники створюються для виявлення найбільш використовуваних слів у природній мові, мові письменника, певному творі тощо. Цими словниками послуговуються при вивченні іноземних мов; розробці інших видів словників; проектуванні мовних експериментів; проведенні досліджень у галузях лексичної семантики, психолінгвістики, морфології та інших; створенні прикладних програм, орієнтованих на опрацювання природної мови. Інформаційно-комунікаційні технології, доступ до величезних електронних лінгвістичних корпусів, національних баз даних слів, заснованих на субтитрах телевізійних програм та фільмів, значно прискорили дослідження в галузі статистичного опрацювання текстів. Зважаючи на те, що частотні словники широко використовуються в різних сферах діяльності, а їх побудова передбачає розв’язання широкого кола лінгвістичних задач, доцільно розглянути технологію створення таких словників у процесі підготовки фахівців з прикладної лінгвістики та комп’ютерних наук, учителів інформатики. У статті розглядається методика навчання студентів створенню частотних словників. Запропоновано алгоритм побудови частотного словника. Аналізуються особливості реалізації кожного кроку алгоритму з використанням мови Python, яка є популярною мовою програмування з відкритим кодом та великими бібліотеками. Автор наводить програмні коди та обґрунтовує використання відповідних модулів, методів опрацювання рядків, функцій, констант, структур даних, регулярних виразів. Запропонована методика спрямована на: 1) підвищення мотивації студентів до навчання та 2) розкриття практичної значущості засвоєних ними методів та прийомів програмування. Автор вважає, що підхід, представлений у цій статті, може бути корисним викладачам дисциплін інформатичного циклу.

Image processing is an increasingly widespread field in computer science. On the other hand, it is increasingly used both in modern business and in social communication. We will look at image manipulation methods, emphasizing approaches for comparing them. We will offer ways to process images included in popular specialized applications. We emphasize the use of the popular Python programming language, which is becoming more and more popular due to its ease of use and large range of tools. We will look at some of the image processing and analysis libraries used in Python.

The emergence of Unified Modeling Language (UML) as a standard for modeling systems has encouraged the use of automated software tools that facilitate the development process from analysis through coding. The UML state machine diagram is used for modeling the dynamic aspects of systems and includes many concepts that are not present in most popular programming languages, like Java or C++. There exists a gap between high level modeling language and a programming language. This paper proposes an approach to narrow the gap between multiple UML models and an implemented system. The narrowing of gap is achieved by generating compact and efficient Java code directly from UML state machine having sequential and concurrent substates. The code generation is achieved by creating a mapping between UML behavior and the Java programming language. Our model can work as a basis for automatic code generation for object-oriented systems.

This book provides an introduction to R programming and a summary of financial mathematics. It is not always easy for graduate students to grasp an overview of the theory of finance in an abstract form. For newcomers to the finance industry, it is not always obvious how to apply the abstract theory to the real financial data they encounter. Introducing finance theory alongside numerical applications makes it easier to grasp the subject. Popular programming languages like C++, which are used in many financial applications are meant for general-purpose requirements. They are good for implementing large-scale distributed systems for simultaneously valuing many financial contracts, but they are not as suitable for small-scale ad-hoc analysis or exploration of financial data. The R programming language overcomes this problem. R can be used for numerical applications including statistical analysis, time series analysis, numerical methods for pricing financial contracts, etc. This book provides an overview of financial mathematics with numerous examples numerically illustrated using the R programming language.