Background: The Java programming language version eight introduced several features that encourage the functional style of programming, including the support for lambda expressions and the Stream API. Currently, there is common wisdom that refactoring legacy code to introduce lambda expressions, besides other potential benefits, simplifies the code and improves program comprehension. Aims: The purpose of this work is to investigate this belief, conducting an in-depth study to evaluate the effect of introducing lambda expressions on program comprehension. Method: We conduct this research using a mixed-method study. For the quantitative method, we quantitatively analyze 166 pairs of code snippets extracted directly either from GitHub or from recommendations from three tools (RJTL, NetBeans, and IntelliJ). We also surveyed practitioners to collect their perceptions about the benefits on program comprehension when introducing lambda expressions. We asked practitioners to evaluate and rate sets of pairs of code snippets. Results: We found contradictory results in our research. Based on the quantitative assessment, we could not find evidence that the introduction of lambda expressions improves software readability—one of the components of program comprehension. Our results suggest that the transformations recommended by the aforementioned tools decrease program comprehension when assessed by two state-of-the-art models to estimate readability. Differently, our findings of the qualitative assessment suggest that the introduction of lambda expression improves program comprehension in three scenarios: when we convert anonymous inner classes to a lambda expression, structural loops with inner conditional to a anyMatch operator, and structural loops to filter operator combined with a collect method. Implications: We argue in this paper that one can improve program comprehension when she applies particular transformations to introduce lambda expressions (e.g., replacing anonymous inner classes with lambda expressions). Also, the opinion of the participants shines the opportunities in which a transformation for introducing lambda might be advantageous. This might support the implementation of effective tools for automatic program transformations.
No abstract
Uma das tarefas mais importantes para o desenvolvimento de software é a realização de testes que em boa parte das vezes é feita manualmente pelo testador ou desenvolvedor. O processo de teste pode ser facilitado por meio de automação sem a necessidade de intervenção humana e agilizando as tarefas de teste com a geração de dados automatizados. No entanto, a geração de dados de teste de forma automática pode dificultar esse processo em relação a criação e validação que podem necessitar de recursos externos e sobrecarregar o software. Este artigo apresenta uma solução simples utilizando algoritmo genético para a criação de dados com baixo número de gerações e com maior qualidade. A solução também mostrou eficiência em relação a não utilização de recursos externos e validação dos dados de teste gerados. A proposta supera algumas abordagens exploradas anteriormente.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.