Programming and Data Structures

Genetic programming and data structures: Geneticprogramming + datastructures = automaticprogramming: By W. B. Langdon. Kluwer Academic Publishers, Boston, MA. (1998). 278 pages. $125.00. NLG 285.00, GBP 85.00

The COVID-19 pandemic has caused the suspension of face-to-face classes; therefore, greater importance has been given to virtual education. For this reason, it is important to review the new situations in the programming teaching process. This paper aims to interpret the experiences lived by teachers in in the subjects of Fundamentals of Programming and Data Structure in the implementation of virtual education in times of COVID-19 in the Technological Institutes Decentralized from the State of Zacatecas, for this reason, the quantitative, non-experimental research was used. The instrument used was a digital survey addressed to teachers from the Technological Institutes. According to the results obtained, the main problems during virtual education were the lack of connection by geographical location and the lack of adaptation to virtual education. Teaching virtual programming was a good pedagogical experience, the teachers expressed that they gave personalized attention in small groups; however, they mentioned that it was difficult to measure the student’s progress, and the subject contents were not seen with the required degree of complexity. For teaching programming, teachers used platforms such as Moodle, Classroom and Microsoft Teams, virtual classrooms such as Meet and Zoom and digital resources such as videos, presentations and practical manuals. The most important challenges are to have the infrastructure required for the implementation of virtual classes, and the responsibility, commitment and initiative by teachers and students.

Development of a course and textbook focusing on implementation of a spreadsheet program is proposed. The semester-long course will be suitable as a senior elective or graduate course for students with a background in C programming, Unix, and data structures. It will bring together aspects of compiler construction, parser design using Flex and Bison, parse trees, linked lists, function tables, function callbacks, symbol tables, and functional programming. The emphasis will be on the computational internals, so the spreadsheet will operate in ldquobatchrdquo mode, with simple text output, and a separate backend processor will be used to create a web-based GUI.

In the computing education community, there are common understandings regarding what topics should be covered in some specific subjects and their corresponding courses and the preferred sequence in which the topics is presented. Published textbooks written by university educators are indications of such practices. Frequently, developing a new course needs to select a relatively "better" textbook from a large number of similar textbooks based on criteria such as readability and clarity. Majority of the textbooks present the conceptual topics for different aspects of their intended subjects in a progressive manner. That is, the concept of a topic is discussed, coupled with several small examples, and followed by some small exercises such as end of chapter problems. In computing courses, often a term project is assigned to students with the expectation that they will apply the knowledge learned in different topics to one place to solve a problem of relatively large scale. Computing courses such as object-oriented programming and data structures can both be taught using this approach. The author names this the "topic-based approach". However, in mobile programming courses, the ultimate goal is to empower the students with skills for application development. This gives rise to the so-called "app-driven" approach as mentioned in some books. The author had the opportunity to teach a mobile programming course for Android application development recently. This paper introduces how the author prepared the course and is a reflection on the use of the "app-driven" approach in teaching the mobile programming course. Comparisons are made to map out the pros and cons of the more common "topic-based approach" and the "app-driven approach".

At present, the most effective teaching tool is the interactive visualization platform, which directly or indirectly promotes the development of the education field. In addition, the development of this technology will affect many existing fields. The purpose of visual education is to help learners grasp relevant concepts in teaching more clearly. At the same time, visualization technology has a wide range of applications in various teaching fields of computer technology. In programming and data structure courses, the use of visualization teaching platform can deepen the understanding of learners. Based on the visualization information technology, this paper makes an in-depth study on the grading model of minority students in colleges and universities. This paper designs a scoring model by using visualization technology, and uses the model to collect teachers’ scoring results of various indicators of ethnic minority students in colleges and universities, and finally analyses the data.

Students are facing various difficulties in courses like Programming and Data Structure through undergraduate programs, which is why failure rates and dropouts in these courses are high. Identifying students at risk of failure at an early stage of a semester is a serious challenge in higher education, so predicting students' academic performance is one of the most essential research topics to reduce failure rates, and to improve the performance of students by the end of a semester. We are developing a predictive model based on a deep artificial neural network to predict students' academic performance of upcoming courses based on their grades in previous courses of the first academic year. We have used one of the most common resampling methods, which is the SMOTE approach to handle the problem of the imbalanced dataset. The preliminary results show that our proposed model has achieved 86% accuracy. To put our system in context, we compared our results to some traditional machine learning techniques such as Decision Tree, K-Nearest Neighbor, and Random Forest, which were applied to an online dataset that has been widely used in some previous works. The comparison showed that our experimental results have achieved better results than the other traditional models. In future work, we will use a larger dataset to improve the accuracy of our models. Using other oversampling techniques such as SVM-SMOTE and Random Over Sampler will be used to evaluate their performance in comparison to the algorithms used in our work.

The creation of a new modeling and simulation engineering program presented the opportunity to evaluate the core skills desirable in a well-rounded graduate. Software was identified as an often neglected aspect of modeling and simulation programs and an attempt was made to remedy this. This paper discusses the software skills identified as necessary/desirable in a graduate. The focus is on discrete event simulation (DES), though the skills are transferable to other paradigms. The discussion is partitioned into discussing skills appropriate for simulation application development and simulation tool development. The discussion is further partitioned to discuss core computer science skills (object-oriented programming and data structures), software architecture, graphics development, implementing DES worldviews, and an ability to work with open source software. The result is a graduate that is desirable to industry and graduate research.

JavaScript is the de facto programming language for the Web. It is used to implement mail clients, office applications, or IDEs, that can weight hundreds of thousands of lines of code. The language itself is prototype based, but to master the complexity of their application, practitioners commonly rely on informal class abstractions. This practice has never been the target of empirical research in JavaScript. Yet, understanding it is key to adequately tuning programming environments and structure libraries such that they are accessible to programmers. In this paper we report on a large and in-depth study to understand how class emulation is employed in JavaScript applications. We propose a strategy to statically detect class-based abstractions in the source code of JavaScript systems. We used this strategy in a dataset of 50 popular JavaScript applications available from GitHub. We found four types of JavaScript software: class-free (systems that do not make any usage of classes), class-aware (systems that use classes, but marginally), class-friendly (systems that make a relevant usage of classes), and class-oriented (systems that have most of their data structures implemented as classes). The systems in these categories represent, respectively, 26%, 36%, 30%, and 8% of the systems we studied.

A higher level language derives its great power from the fact that it tends to impose structure on the problem solving behavior of the user. Besides providing a library of useful subroutines with a uniform calling sequence, the author of a higher level language imposes his theory of problem solving on the user. By choosing what primitive data structures, control structures, and operators he presents, he makes the implementation of some algorithms more difficult than others, thus discouraging some techniques and encouraging others. So, to be good, a higher level language must not only simplify the job of programming, by providing features which package programming structures commonly found in the domain for which the language was designed, it must also do its best to discourage the use of structures which lead to bad algorithms.