Extreme Programming in the University

This paper summarises our experiences teaching Extreme Programming to undergraduate students over a period of 8 years. We describe an approach in which students learn about the Extreme Programming (XP) method by using it on real software development projects. This experiential learning technique has been effective in helping students understand how XP works in practice and helped them to develop the skills to reflect on their current approaches to software development and critically evaluate agile methods. Problems, including a steep learning curve for some XP practices and difficulties scheduling pair-programming time in a university environment are also Identified

PEMANFAATAN QR-CODE VAKSIN COVID-19 UNTUK ABSENSI MENGGUNAKAN METODE EXTREME PROGRAMMING

The digital attendance system enables more efficient data processing, real-time time monitoring, and reduces human errors in the recording process. One of the schools that has developed this technology is SMK Negeri 4 Kota Sorong. This is related to the last two years, where almost everyone has been required to receive the COVID-19 vaccine for prevention and monitoring of student attendance at school. To support the monitoring of student attendance at school, a web-based COVID-19 Vaccine QR-Code utilization system is needed at SMK Negeri 4 Sorong, Southwest Papua. This student attendance system has three access levels, which are divided into admin, teachers, and parents. This research uses PHP programming language and MySQL database. The development of this system is carried out using the Extreme Programming method, which includes steps such as problem identification, data collection, applying the Extreme Programming method, and implementation. The school attendance system, which has been built with its features, has been proven to work perfectly through feature testing using black-box testing with a 100% success rate. From the results of this testing, the utilization of the COVID-19 Vaccine QR-Code can be used for attendance and departure monitoring.Sistem absensi digital memungkinkan pengolahan data yang lebih efisien, pemantauan waktu secara real-time, dan mengurangi kesalahan manusia dalam proses pencatatan. Salah satu sekolah yang di kembangkan teknologi tersebuat adalah SMK Negeri 4 Kota Sorong. Hal ini berkaitan dengan 2 tahun terakhir hampir semua orang diwajibkan menerima vaksin covid-19 dan untuk pencegahan,serta pemantauan kehadiran siswa disekolah. Untuk mendukung proses pemantuan kehadiran siswa disekolah maka diperlukan sistem pemanfaatan QR-Code Vaksin Covid-19 berbasis web di SMK Negeri 4 Sorong Papua Barat Daya. Sistem absensi siswa ini memiliki tiga akses yang terbagi menjadi admin, guru, dan orang tua. Penelitian ini menggunakan bahasa pemrograman PHP dan database MySQL. Pembuatan sistem ini, menggunakan metode Extreme Programming di dalamnya dilakukan dengan langkah penelitian diantaranya mengidentifikasi masalah, mengumpulkan data, menerapkan metode Extreme Programming, dan melakukan implementasi. Sistem absensi sekolah yang telah di bangun dengan fitur-fitur berhasil sempurna di buktikan dengan pengujian fitur sistem menggunakan black box testing dengan tingkat keberhasilan 100%. Dari hasil pengujian tersebut pemanfaatan QR-Code Vaksin Covid-19 dapat digunakan untuk absensi kehadiran dan kepulangan

Bayesian extreme quantile regression for hidden Markov models

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityThe main contribution of this thesis is the introduction of Bayesian quantile regression for hidden Markov models, especially when we have to deal with extreme quantile regression analysis, as there is a limited research to inference conditional quantiles for hidden Markov models, under a Bayesian approach. The first objective is to compare Bayesian extreme quantile regression and the classical extreme quantile regression, with the help of simulated data generated by three specific models, which only differ in the error term’s distribution. It is also investigated if and how the error term’s distribution affects Bayesian extreme quantile regression, in terms of parameter and confidence intervals estimation. Bayesian extreme quantile regression is performed by implementing a Metropolis-Hastings algorithm to update our parameters, while the classical extreme quantile regression is performed by using linear programming. Moreover, the same analysis and comparison is performed on a real data set. The results provide strong evidence that our method can be improved, by combining MCMC algorithms and linear programming, in order to obtain better parameter and confidence intervals estimation. After improving our method for Bayesian extreme quantile regression, we extend it by including hidden Markov models. First, we assume a discrete time finite state-space hidden Markov model, where the distribution associated with each hidden state is a) a Normal distribution and b) an asymmetric Laplace distribution. Our aim is to explore the number of hidden states that describe the extreme quantiles of our data sets and check whether a different distribution associated with each hidden state can affect our estimation. Additionally, we also explore whether there are structural changes (breakpoints), by using break-point hidden Markov models. In order to perform this analysis we implement two new MCMC algorithms. The first one updates the parameters and the hidden states by using a Forward-Backward algorithm and Gibbs sampling (when a Normal distribution is assumed), and the second one uses a Forward-Backward algorithm and a mixture of Gibbs and Metropolis-Hastings sampling (when an asymmetric Laplace distribution is assumed). Finally, we consider hidden Markov models, where the hidden state (latent variables) are continuous. For this case of the discrete-time continuous state-space hidden Markov model we implement a method that uses linear programming and the Kalman filter (and Kalman smoother). Our methods are used in order to analyze real interest rates by assuming hidden states, which represent different financial regimes. We show that our methods work very well in terms of parameter estimation and also in hidden state and break-point estimation, which is very useful for the real life applications of those methods

Development of Mobile Application to Report Criminal Acts in Young Areas of Peru

This research work entitled "Design of a mobile application for complaints in real time to the national police", being that the police officer must be in his office or in front of a computer with an Internet connection so that he can see the complaints that are in charge, or manually search for documents, cases, folders.For this reason, a mobile application called "mobile application" was proposed and developed; as a solution proposal. Its purpose is to solve different problems without having to be in the police station and / or in the office. We want to help the population to carry out any complaint in a more EASY AND QUICK way, and this will be achieved through the application "MOBILE APPLICATION", with Android operating system, resulting in a friendly and easy-to-use mobile complaint management application.For the present project, XP Extreme Programming (eXtreme programming) methodology was used, which adapts to the necessary characteristics required for the application to have optimal performance, in addition to facilitating the development and design work of the application. We made use of a series of technologies and tools for the development and design work of the application, we will use IDE (integrated development environment) Android Studio that provides us with comprehensive services, which facilitates the task in time of programming our mobile application

Numerical Verification of Affine Systems with up to a Billion Dimensions

Affine systems reachability is the basis of many verification methods. With further computation, methods exist to reason about richer models with inputs, nonlinear differential equations, and hybrid dynamics. As such, the scalability of affine systems verification is a prerequisite to scalable analysis for more complex systems. In this paper, we improve the scalability of affine systems verification, in terms of the number of dimensions (variables) in the system. The reachable states of affine systems can be written in terms of the matrix exponential, and safety checking can be performed at specific time steps with linear programming. Unfortunately, for large systems with many state variables, this direct approach requires an intractable amount of memory while using an intractable amount of computation time. We overcome these challenges by combining several methods that leverage common problem structure. Memory is reduced by exploiting initial states that are not full-dimensional and safety properties (outputs) over a few linear projections of the state variables. Computation time is saved by using numerical simulations to compute only projections of the matrix exponential relevant for the verification problem. Since large systems often have sparse dynamics, we use Krylov-subspace simulation approaches based on the Arnoldi or Lanczos iterations. Our method produces accurate counter-examples when properties are violated and, in the extreme case with sufficient problem structure, can analyze a system with one billion real-valued state variables

Intelligent Systems Development in a Non Engineering Curriculum

Much of computer system development today is programming in the large - systems of millions of lines of code distributed across servers and the web. At the same time, microcontrollers have also become pervasive in everyday products, economical to manufacture, and represent a different level of learning about system development. Real world systems at this level require integrated development of custom hardware and software. How can academic institutions give students a view of this other extreme - programming on small microcontrollers with specialized hardware? Full scale system development including custom hardware and software is expensive, beyond the range of any but the larger engineering oriented universities, and hard to fit into a typical length course. The course described here is a solution using microcontroller programming in high level language, small hardware components, and the Arduino open source microcontroller. The results of the hands-on course show that student programmers with limited hardware knowledge are able to build custom devices, handle the complexity of basic hardware design, and learn to appreciate the differences between large and small scale programming

A discovery and analysis of influencing factors of pair programming

The exploration into the underlying psychosocial links of pair programming. a new and unorthodox programming paradigm in which two programmers share one keyboard and monitor during real-time programming sessions, is undertaken. These complex psychosocial relationships, along with cognitive process exchanges, ultimately mold the programming output as well as determine the level of communication, satisfaction. confidence and compatibility. Laying the framework for this research, a through review of traditional and contemporary paradigms with a special focus on their limitations and a list of current software development problems are presented. Next, a detailed summary of pair programming and related agile software paradigms, such as extreme programming, which lists pair programming as one of its twelve principles, is given. From earlier pair programming studies, a number of programming benefits have been unveiled and these are listed and discussed. However, a lack of formal studies pertaining to the psychosocial aspects of pair programming exists. Given this void, a field survey is administered to a group of professional programmers and a resulting list of influencing factors on pair programming emerges. From the list, the most popular factor, personality, and two other factors, communication and gender, have been selected in order to study their impact on pair programming product outcome and the level of communication, satisfaction, confidence and compatibility. An experiment focusing on these factors is designed and implemented. From the experimental findings, the personality of the two partners in pair programming is found to have a significant impact on the pair programming output. Also, it is discovered that same gender pairs exhibited an unusually high level of communication, satisfaction and compatibility between each other, especially among female-female pairs. A detailed statistical experiment result based on research hypotheses is reported

Incorporating Agile with MDA Case Study: Online Polling System

Nowadays agile software development is used in greater extend but for small organizations only, whereas MDA is suitable for large organizations but yet not standardized. In this paper the pros and cons of Model Driven Architecture (MDA) and Extreme programming have been discussed. As both of them have some limitations and cannot be used in both large scale and small scale organizations a new architecture has been proposed. In this model it is tried to opt the advantages and important values to overcome the limitations of both the software development procedures. In support to the proposed architecture the implementation of it on Online Polling System has been discussed and all the phases of software development have been explained.Comment: 14 pages,1 Figure,1 Tabl