Verification of Unstructured Grid Adaptation Components

Adaptive unstructured grid techniques have made limited impact on production analysis workflows where the control of discretization error is critical to obtaining reliable simulation results. Recent progress has matured a number of independent implementations of flow solvers, error estimation methods, and anisotropic grid adaptation mechanics. Known differences and previously unknown differences in grid adaptation components and their integrated processes are identified here for study. Unstructured grid adaptation tools are verified using analytic functions and the Code Comparison Principle. Three analytic functions with different smoothness properties are adapted to show the impact of smoothness on implementation differences. A scalar advection-diffusion problem with an analytic solution that models a boundary layer is adapted to test individual grid adaptation components. Laminar flow over a delta wing and turbulent flow over an ONERA M6 wing are verified with multiple, independent grid adaptation procedures to show consistent convergence to fine-grid forces and a moment. The scalar problems illustrate known differences in a grid adaptation component implementation and a previously unknown interaction between components. The wing adaptation cases in the current study document a clear improvement to existing grid adaptation procedures. The stage is set for the infusion of verified grid adaptation into production fluid flow simulations

A Fine-Grained Approach for Automated Conversion of JUnit Assertions to English

Converting source or unit test code to English has been shown to improve the maintainability, understandability, and analysis of software and tests. Code summarizers identify important statements in the source/tests and convert them to easily understood English sentences using static analysis and NLP techniques. However, current test summarization approaches handle only a subset of the variation and customization allowed in the JUnit assert API (a critical component of test cases) which may affect the accuracy of conversions. In this paper, we present our work towards improving JUnit test summarization with a detailed process for converting a total of 45 unique JUnit assertions to English, including 37 previously-unhandled variations of the assertThat method. This process has also been implemented and released as the AssertConvert tool. Initial evaluations have shown that this tool generates English conversions that accurately represent a wide variety of assertion statements which could be used for code summarization or other NLP analyses.Comment: In Proceedings of the 4th ACM SIGSOFT International Workshop on NLP for Software Engineering (NL4SE 18), November 4, 2018, Lake Buena Vista, FL, USA. ACM, New York, NY, USA, 4 page

A Model-Based Approach to Impact Analysis Using Model Differencing

Impact analysis is concerned with the identification of consequences of changes and is therefore an important activity for software evolution. In modelbased software development, models are core artifacts, which are often used to generate essential parts of a software system. Changes to a model can thus substantially affect different artifacts of a software system. In this paper, we propose a modelbased approach to impact analysis, in which explicit impact rules can be specified in a domain specific language (DSL). These impact rules define consequences of designated UML class diagram changes on software artifacts and the need of dependent activities such as data evolution. The UML class diagram changes are identified automatically using model differencing. The advantage of using explicit impact rules is that they enable the formalization of knowledge about a product. By explicitly defining this knowledge, it is possible to create a checklist with hints about development steps that are (potentially) necessary to manage the evolution. To validate the feasibility of our approach, we provide results of a case study.Comment: 16 pages, 5 figures, In: Proceedings of the 8th International Workshop on Software Quality and Maintainability (SQM), ECEASST Journal, vol. 65 201

Software systems engineering: a journey to contemporary agile and beyond, do people matter?

It is fascinating to view the evolution of software systems engineering over the decades. At the first glance, it could be perceived that the various approaches and processes are different. Are they indeed different? This paper will briefly discuss such a journey relating to findings from an empirical study in some organisations in the UK. Some of the issues described in the literature and by practitioners are common across different software system engineering approaches over the time. It can be argued that human-element of software development plays an integral part in the success of software systems development endeavour. After all, software engineering is a human-centric craft. In order to understand such issues, we crossed the discipline to other disciplines in order to adapt theories and principles that will help to better understand and tackle such matter. Other disciplines have well established human related theories and principles that can be useful. From Japanese management philosophies, we have adapted Lean and knowledge management theories. From psychology, we have adapted Emotional Intelligence (EI). With such an interdisciplinary view, some of the issues can be addressed adequately. Which bring the question: is it really the process or the people? The second author will reflect on his experience attending the first SQM conference 25 years ago. The reflection will discuss the evolution of software systems engineering, and what was changed since then, if at all changed