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The field of statistical computing is rapidly developing and evolving. Shifting away from the formerly siloed landscape of mathematics, statistics, and computer science, recent advancements in statistical computing are largely characterized by a fusing of these worlds; namely, programming, software development, and applied statistics are merging in new and exciting ways. There are numerous drivers behind this advancement, including open movement (encompassing development, science, and access), the advent of data science as a field, and collaborative problem-solving, as well as practice-altering advances in subfields such as artificial intelligence, machine learning, and Bayesian estimation. In this paper, we trace this shift in how modern statistical computing is performed, and that which has recently emerged from it. This discussion points to a future of boundless potential for the field. [ABSTRACT FROM AUTHOR]

There is an increase use of security driven approaches to support software development activities, such as requirements, design and implementation. The objective of this paper is to identify the existing software security approaches used in the software development lifecycle (SDLC). In order to meet our goal, we conducted a systematic mapping study to identify the primary studies on the use of software security techniques in SDLC. In total, we selected and categorized 118 primary studies. After analyzing the selected studies, we identified 52 security approaches and we categorized them in to five main categories, namely, ‘secure requirements modeling’, ‘vulnerability identification, adaption and mitigation’, ‘software security focused process’, ‘extended UML-based secure modeling profiles’, ‘non UML-based secure modeling notations’. The results show that the most frequently used approaches are static analysis and dynamic analysis that provide security checks in the coding phase. In addition, our results show that many studies in this review considered security checks around the coding stage of software development. This work will assist software development organizations in better understanding the existing software security approaches used in the software development lifecycle. It can also provide researchers with a firm basis on which to develop new software security approaches. [ABSTRACT FROM AUTHOR]

In computer science, functional orbits – i.e., tracks left by the iterations of a function – in a finite domain naturally appear at a high or a low level. This paper introduces a Coq logical orbit framework, the purpose of which is to help rigorously developing software systems with some complex data structures from specification to implementation. The result is a Coq library of orbit concepts formalized as definitions, lemmas and theorems. Most of them are inspired by our previous work in geometric modelling, where combinatorial hypermaps were used to describe surface subdivisions appearing in computational geometry problems, e.g., building convex hulls or Delaunay diagrams. Now, this domain remains a reference for us, but our results are drastically extended and usable in other computer science areas. The proof of Floyd's cycle-detection algorithm, known as “the tortoise and the hare”, confirms that point. The library contains operations to observe, traverse and update orbits – addition, deletion, mutation, transposition – with proofs of their behavior. It focuses on the important case where the involved function is a partial injection. In this case, it defines a connectivity relationship and evaluates the variation of the number of connected components during updates. [ABSTRACT FROM AUTHOR]

Computer science is a predominantly male field of study. Women face barriers while trying to insert themselves in the study of computer science. Those barriers extend to when women are exposed to the professional area of computer science. Despite decades of social fights for gender equity in Science, Technology, Engineering, and Mathematics (STEM) education and in computer science in general, few women participate in computer science, and some of the reasons include gender bias and lack of support for women when choosing a computer science career. Open source software development has been increasingly used by companies seeking the competitive advantages gained by team diversity. This diversification of the characteristics of team members includes, for example, the age of the participants, the level of experience, education and knowledge in the area, and their gender. In open source software projects women are underrepresented and a series of biases are involved in their participation. This paper conducts a systematic literature review with the objective of finding factors that could assist in increasing women's interest in contributing to open source communities and software development projects. The main contributions of this paper are: (i) identification of factors that cause women's lack of interest (engagement), (ii) possible solutions to increase the engagement of this public, (iii) to outline the profile of professional women who are participating in open source software projects and software development projects. The main findings of this research reveal that women are underrepresented in software development projects and in open source software projects. They represent less than 10% of the total developers and the main causes of this underrepresentation may be associated with their workplace conditions, which reflect male gender bias. [ABSTRACT FROM AUTHOR]