Abstract
Software testing is an integral part of modern software development. Testing frameworks are part of the toolset of any software language allowing programmers to test their programs in order to detect bugs. Unfortunately, there is no work on testing in attribute grammars. In this paper we combine the powerful property-based testing technique with the attribute grammar formalism. In such property-based attribute grammars, properties are defined on attribute instances. Properties are tested on large sets of randomly generated (abstract syntax) trees by evaluating their attributes. We present an implementation that relies on strategies to express property-based attribute grammars. Strategies are tree-based recursion patterns that are used to encode logic quantifiers defining the properties.

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Abstract
JavaScript is a widely used programming language initially designed to make the Web more dynamic in the 1990s. In the last decade, though, its scope has extended far beyond the Web, finding utility in backend development, desktop applications, and even IoT devices. To circumvent the needs of modern programming, JavaScript has undergone a remarkable evolution since its inception, with the groundbreaking release of its sixth version in 2015 (ECMAScript 6 standard). While adopting modern JavaScript features promises several benefits (such as improved code comprehension and maintenance), little is known about which modern features of the language have been used in practice (or even ignored by the community). To fill this gap, in this paper, we report the results of an empirical study that aims to understand the adoption trends of modern JavaScript features, and whether or not developers conduct rejuvenation efforts to replace legacy JavaScript constructs and idioms with modern ones in legacy systems. To this end, we mined the source code history of 158 JavaScript open-source projects, identified contributions to rejuvenate legacy code, and used time series to characterize the adoption trends of modern JavaScript features. The results of our study reveal extensive use of JavaScript modern features which are present in more than 80% of the analyzed projects. Our findings also reveal that (a) the widespread adoption of modern features happened between one and two years after the release of ES6 and, (b) a consistent trend toward increasing the adoption of modern JavaScript language features in open-source projects and (c) large efforts to rejuvenate the source code of their programs.

Abstract
Historically, programming language performance focused on fast execution times. With the advent of cloud and edge computing, and the significant energy consumption of large data centers, energy efficiency has become a critical concern both for computer manufacturers and software developers. Despite the considerable efforts of the green software community in developing techniques and tools for analysing and optimising software energy consumption, there has been limited research on how imposing hardware-level energy constraints affects software energy efficiency. Moreover, prior research has demonstrated that the choice of programming language can significantly impact a program’s energy efficiency. This paper investigates the impact of CPU power capping on the energy consumption and execution time of programs written in Haskell, Java, and Python. Our preliminary results analysing well-established benchmarks indicate that while power capping does reduce energy consumption across all benchmarks, it also substantially increases execution time. These findings highlight the trade-offs between energy efficiency and runtime performance, offering insights for optimising software under energy constraints. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).