HASLab - Indexed Articles in Conferences
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ItemHow are Contracts Used in Android Mobile Applications?( 2024)Formal contracts and assertions are effective methods to enhance software quality by enforcing preconditions, postconditions, and invariants. However, the adoption and impact of contracts in the context of mobile application development, particularly of Android applications, remain unexplored. We present the first large-scale empirical study on the presence and use of contracts in Android applications, written in Java or Kotlin. We consider 2,390 applications and five categories of contract elements: conditional runtime exceptions, APIs, annotations, assertions, and other. We show that most contracts are annotation-based and are concentrated in a small number of applications. © 2024 IEEE Computer Society. All rights reserved.
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ItemState of the Practice in Software Testing Teaching in Four European Countries( 2024)Software testing is an indispensable component of software development, yet it often receives insufficient attention. The lack of a robust testing culture within computer science and informatics curricula contributes to a shortage of testing expertise in the software industry. Addressing this problem at its root -education- is paramount. In this paper, we conduct a comprehensive mapping review of software testing courses, elucidating their core attributes and shedding light on prevalent subjects and instructional methodologies. We mapped 117 courses offered by Computer Science (and related) degrees in 49 academic institutions from four Western European countries, namely Belgium, Italy, Portugal and Spain. The testing subjects were mapped against the conceptual framework provided by the ISO/IEC/IEEE 29119 standard on software testing. Among the results, the study showed that dedicated software testing courses are offered by only 39% of the analysed universities, whereas the basics of software testing are taught in at least one course at every university. The analysis of the software testing topics highlights the gaps that need to be filled in order to better align the current academic offerings with the real industry needs.
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ItemPatient-Centric Health Data Sovereignty: An Approach Using Proxy Re-Encryption( 2024)The exponential growth in the digitisation of services implies the handling and storage of large volumes of data. Businesses and services see data sharing and crossing as an opportunity to improve and produce new business opportunities. The health sector is one area where this proves to be true, enabling better and more innovative treatments. Notwithstanding, this raises concerns regarding personal data being treated and processed. In this paper, we present a patient-centric platform for the secure sharing of health records by shifting the control over the data to the patient, therefore, providing a step further towards data sovereignty. Data sharing is performed only with the consent of the patient, allowing it to revoke access at any given time. Furthermore, we also provide a break-glass approach, resorting to Proxy Re-encryption (PRE) and the concept of a centralised trusted entity that possesses instant access to patients' medical records. Lastly, an analysis is made to assess the performance of the platform's key operations, and the impact that a PRE scheme has on those operations.
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ItemAssessing the impact of hints in learning formal specification( 2024)Background: Many progranunmg environments include automated feedback in the form of hints to help novices learn autonomously. Some experimental studies investigated the impact of automated liints in the immediate, performance and learning retention in that context. Automated feedback is also becoming a popular research topic in the context of formal specification languages, but so far no experimental studies have been conducted to assess its impact while learning such languages. Objective: We aim to investigate the impact of different types of automated hints while learning a formal specification language, not only in terms of immediate performance and learning retention, but also in the emotional response of the students. Method: We conducted a simple one-factor randomised experiment in 2 sessions involving 85 BSc students majoring in CSE. In the 1st session students were divided in 1 control group and 3 experimental groups, each receiving a different type of hint while learning to specify simple, requirements with the Alloy formal specification language. To assess the impact of hints on learning retention, in the 2nd session, 1 week later, students had no hints while formalising requirements. Before and after each session the students answered a standard self-reporting emotional survey to assess their emotional response to the experiment. Results: Of the 3 types of hints considered, only those pointing to the precise location of an error had a positive impact on the immediate performance and none had significant impact in learning retention. Hint availability also causes a significant impact on the emotional response, but no significant emotional :impact exists once hints are no longer available (i.e. no deprivation effects were detected). Conclusion: Although none of the evaluated hints had an impact on learning retention, learning a formal specification language with an environment that provides hints with precise error locations seems to contribute to a better overall experience without apparent drawbacks. Further studies are needed to investigate if other kind of feedback, namely hints combined with some sort of self explanation prompts, can have a positive impact in learning retention.
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ItemA Language for Explaining Counterexamples( 2024)Model checkers can automatically verify a system’s behavior against temporal logic properties. However, analyzing the counterexamples produced in case of failure is still a manual process that requires both technical and domain knowledge. However, this step is crucial to understand the flaws of the system being verified. This paper presents a language created to support the generation of natural language explanations of counterexamples produced by a model checker. The language supports querying the properties and counterexamples to generate the explanations. The paper explains the language components and how they can be used to produce explanations. © Ezequiel José Veloso Ferreira Moreira and José Creissac Campos.