Alexandre Bergel

Pooja Rani, Suada Abukar, Nataliia Stulova et al.

Assessing code comment quality is known to be a difficult problem. A number of coding style guidelines have been created with the aim to encourage writing of informative, readable, and consistent comments. However, it is not clear from the research to date which specific aspects of comments the guidelines cover (e.g., syntax, content, structure). Furthermore, the extent to which developers follow these guidelines while writing code comments is unknown. We analyze various style guidelines in Java and Python and uncover that the majority of them address more the content aspect of the comments rather than syntax or formatting, but when considering the different types of information developers embed in comments and the concerns they raise on various online platforms about the commenting practices, existing comment conventions are not yet specified clearly enough, nor do they adequately cover important concerns. We also analyze commenting practices of developers in diverse projects to see the extent to which they follow the guidelines. Our results highlight the mismatch between developer commenting practices and style guidelines, and provide several focal points for the design and improvement of comment quality checking tools.

Mehrdad Abdi, Henrique Rocha, Serge Demeyer et al.

Some test amplification tools extend a manually created test suite with additional test cases to increase the code coverage. The technique is effective, in the sense that it suggests strong and understandable test cases, generally adopted by software engineers. Unfortunately, the current state-of-the-art for test amplification heavily relies on program analysis techniques which benefit a lot from explicit type declarations present in statically typed languages. In dynamically typed languages, such type declarations are not available and as a consequence test amplification has yet to find its way to programming languages like Smalltalk, Python, Ruby and Javascript. We propose to exploit profiling information --readily obtainable by executing the associated test suite-- to infer the necessary type information creating special test inputs with corresponding assertions. We evaluated this approach on 52 selected test classes from 13 mature projects in the Pharo ecosystem containing approximately 400 test methods. We show the improvement in killing new mutants and mutation coverage at least in 28 out of 52 test classes (53%). Moreover, these generated tests are understandable by humans: 8 out of 11 pull-requests submitted were merged into the main code base (72%). These results are comparable to the state-of-the-art, hence we conclude that test amplification is feasible for dynamically typed languages.

Leonardo Humberto Silva, Marco Tulio Valente, Alexandre Bergel

JavaScript systems are becoming increasingly complex and large. To tackle the challenges involved in implementing these systems, the language is evolving to include several constructions for programming- in-the-large. For example, although the language is prototype-based, the latest JavaScript standard, named ECMAScript 6 (ES6), provides native support for implementing classes. Even though most modern web browsers support ES6, only a very few applications use the class syntax. In this paper, we analyze the process of migrating structures that emulate classes in legacy JavaScript code to adopt the new syntax for classes introduced by ES6. We apply a set of migration rules on eight legacy JavaScript systems. In our study, we document: (a) cases that are straightforward to migrate (the good parts); (b) cases that require manual and ad-hoc migration (the bad parts); and (c) cases that cannot be migrated due to limitations and restrictions of ES6 (the ugly parts). Six out of eight systems (75%) contain instances of bad and/or ugly cases. We also collect the perceptions of JavaScript developers about migrating their code to use the new syntax for classes.

Leonardo Humberto Silva, Daniel Hovadick, Marco Tulio Valente et al.

With the increasing usage of JavaScript in web applications, there is a great demand to write JavaScript code that is reliable and maintainable. To achieve these goals, classes can be emulated in the current JavaScript standard version. In this paper, we propose a reengineering tool to identify such class-like structures and to create an object-oriented model based on JavaScript source code. The tool has a parser that loads the AST (Abstract Syntax Tree) of a JavaScript application to model its structure. It is also integrated with the Moose platform to provide powerful visualization, e.g., UML diagram and Distribution Maps, and well-known metric values for software analysis. We also provide some examples with real JavaScript applications to evaluate the tool.

Tobias Kuhn, Alexandre Bergel

Writing documentation about software internals is rarely considered a rewarding activity. It is highly time-consuming and the resulting documentation is fragile when the software is continuously evolving in a multi-developer setting. Unfortunately, traditional programming environments poorly support the writing and maintenance of documentation. Consequences are severe as the lack of documentation on software structure negatively impacts the overall quality of the software product. We show that using a controlled natural language with a reasoner and a query engine is a viable technique for verifying the consistency and accuracy of documentation and source code. Using ACE, a state-of-the-art controlled natural language, we present positive results on the comprehensibility and the general feasibility of creating and verifying documentation. As a case study, we used automatic documentation verification to identify and fix severe flaws in the architecture of a non-trivial piece of software. Moreover, a user experiment shows that our language is faster and easier to learn and understand than other formal languages for software documentation.