Evolution of Bad Smells in LabVIEW Graphical Models.

Abstract

Bad smells often indicate potential problems in software, which may lead to long-term challenges and expensive maintenance efforts. Although bad smells often occur in source code, bad smells also exist in representations of design descriptions and models. We have observed that many users of graphical modeling environments (e.g., LabVIEW) are systems engineers who may not be aware of core software engineering techniques, such as refactoring of bad smells. Systems engineers often focus on implementation correctness and may be unaware of how their designs affect long-term maintenance properties that may increase design smells. There exists a large body of research focused on analysing bad smells embedded in the source code of textual languages, but there has been limited research on bad smells in systems models of graphical languages.In this paper, we present a semi-automated approach for extracting design smells across versions of LabVIEW graphical models through user-defined queries. We describe example queries that highlight the emergence of design smells that we discovered from posts in the LabVIEW user's forum. We then demonstrate the use of the example queries in understanding the evolution of seven bad smells we found in 81 LabVIEW models stored in 10 GitHub repositories. We analyze the evolution of these smells in order to understand the prevalence and introduction of bad smells, as well as the relationship between bad smells and the structural changes made to the models. Our results show that all of the models contain instances of at least one type of bad smell and the number of smells fluctuates as the size of a model increases. Furthermore, the majority of the structural changes across different versions of LabVIEW models involve the addition of new elements with a corresponding increase in the presence of design smells. This paper summarizes the need for better analysis of design smells in systems models and suggests an approach that may assist in improving the structure and quality of systems models developed in LabVIEW.

Threat Actors’ Tenacity to Disrupt: Examination of Major Cybersecurity Incidents

“…Threat actors never stop searching for those unpatched vulnerabilities to exploit [41], [42]. There are other scenarios where the design of software systems may contain flaws that negatively affect quality and maintainability [43], thereby creating a vulnerability that if exploited may be disruptive to an organization [39], [40].…”

Labcode Analyzer: A Semi-Automatic Refactoring Tool From Static Code Analysis of Labview Applications

“…O principal objetivo da presente pesquisa é o projeto e implementação da ferramenta LabCODE Analyzer que visa analisar códigos em LabVIEW para indicar problemas de codificação (code smells) e sugerir, de modo semiautomático, refatoração do código que possa afetar o desempenho, o funcionamento, a manutenibilidade, a legibilidade, a escalabilidade e o reuso de uma aplicação nos médio e longo prazos. Devido à dificuldade de se implementar todos os code smells encontrados na literatura pesquisada, numa primeira etapa será adotada a mesma estratégia utilizada por Popoola et al (2021), em que foram escolhidos sete problemas mais comuns encontrados em aplicações LabVIEW. Além de analisar os códigos em LabVIEW, o LabCODE tem a capacidade de explicar a razão pela qual o problema indicado pode prejudicar a aplicação, e apresentar uma sugestão para a refatoração do trecho de código que causa o problema, características ausentes na ferramenta VI Analyzer Tool do LabVIEW.…”

“…Outro ponto importante a ser destacado é a aparente inexistência de ferramentas para a plataforma LabVIEW que, além de analisar os códigos estaticamente, também efetuem a refatoração ou, ao menos, orientem a desenvolvedor das alternativas de alteração de código. Tanto a ferramenta disponível no próprio LabVIEW, o VI Analyzer Tool, quanto os protótipos apresentados nos trabalhos de Chambers e Scaffidi (2013) e Popoola et al (2021), apenas localizam os problemas de codificação. Dessa forma, a principal contribuição da ferramenta proposta -o LabCODE Analyzer -é oferecer ao desenvolvedor a possibilidade de executar a correção do código de maneira semiautomática através das alternativas possíveis de refatoração para o problema reportado.…”