Seminari
Da febbraio 2019, l’Istituto del Software ha iniziato una serie di seminari. Ogni giovedì pomeriggio, un ricercatore dell’Istituto terrà un breve discorso su un argomento di ingegneria del software a sua scelta, come ad esempio articoli interessanti pubblicati di recente, articoli seminali nel proprio campo di ricerca, discussioni su idee preliminari, tutorial e piccoli esperimenti.
Sulla nostra playlist YouTube potete riguardare alcuni dei seminari precedenti. Di seguito trovate ulteriori dettagli sul prossimo seminario, su quelli a venire e un archivio dei relatori precedenti.
Tutti sono invitati a partecipare ai seminari organizzati dall’Istituto del Software.
Prossimo Relatore: Rosalia Tufano
The automation of code review has been tackled by several researchers with the goal of reducing its cost. The adoption of deep learning in software engineering pushed the automation to new boundaries, with techniques imitating developers in generative tasks, such as commenting on a code change as a reviewer would do or addressing a reviewer’s comment by modifying code. The performance of these techniques is usually assessed through quantitative metrics, e.g., the percentage of instances in the test set for which correct predictions are generated, leaving many open questions on the techniques’ capabilities. For example, knowing that an approach is able to correctly address a reviewer’s comment in 10% of cases is of little value without knowing what was asked by the reviewer: What if in all successful cases the code change required to address the comment was just the removal of an empty line? In this study we aim at characterizing the cases in which three code review automation techniques tend to succeed or fail in the two above-described tasks. It has a strong qualitative focus, with ∼105 man-hours of manual inspection invested in manually analyzing correct and wrong predictions generated by the three techniques, for a total of 2,296 inspected predictions. The output of this analysis are two taxonomies reporting, for each of the two tasks, the types of code changes on which the experimented techniques tend to succeed or to fail, pointing to areas for future work.
Rosalia Tufano is a Ph.D student in the Faculty of Informatics at the Università della Svizzera Italiana (USI), Switzerland, and part of the Software Analytics Research Team (SEART). She received her MSc. in Applied Mathematics from Università degli Studi di Napoli Federico II, Italy, in March 2019. Her research interests mainly include the study and the application of machine learning techniques to support code-related tasks. More information available at: https://www.inf.usi.ch/phd/tufanr/
Programma
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5 ottobre 2023
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12 ottobre 2023
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26 ottobre 2023
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2 novembre 2023
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9 novembre 2023
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16 novembre 2023
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30 novembre 2023
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7 dicembre 2023
Archivio
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Roberto Pietrantuono (University of Naples 'Federico II') - Causal reasoning for software quality engineering (15 giugno 2023)
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Vincenzo Orrei - Contribution-based Firing of Developers? (25 maggio 2023)
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Patric Genfer, University of Vienna - On the Understandability of Security Tactics for Microservice APIs (16 maggio 2023)
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Marco Paganoni - ByteBack: Deductive Functional Verification of Bytecode programs (11 maggio 2023)
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Paolo Tonella - Mind, consciousness and ChatGPT: can ChatGPT impute unobservable mental states to others? (6 aprile 2023)
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Alberto Bacchelli (University of Zurich) - Exploring the Dual Nature of Code Review: Implications for Investigative Methods and Tool Development (30 marzo 2023)
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Csaba Nagy - Perils and Pitfalls of the Application-Database Gap (17 novembre 2022)
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Nargiz Humbatova - DeepCrime: Mutation Testing of Deep Learning Systems Based on Real Faults (6 ottobre 2022)
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Crista Lopes - Exercises in Programming Style (9 settembre 2022)
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Michele Tufano - Unit Test Case Generation with Transformers and Focal Context (20 giugno 2022)
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Diego Venâncio Marcílio - Towards Untangling Java Exceptions (12 maggio 2022)
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Bin Lin - Academic Job Search: An Experience Report (28 aprile 2022)
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Michael Weiss - Uncertainty-Wizard: Fast and User-Friendly Neural Network Uncertainty Quantification (7 aprile 2022)
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Aron Fiechter - Creating a Domain Specific Language in Kotlin Using Type-Safe Builders (24 marzo 2022)
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Luca Pascarella - Fine-Grained Code Summarization (3 marzo 2022)
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Jesper Findahl - What’s Up With the CodeLoungers?
AKA what are CodeLoungers doing all day (25 novembre 2021) -
Andrea Gallidabino - Do you understand the code you write? 'I hope the TAs won't look at this!' (4 novembre 2021)
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Igor Moreno Santos - Towards sound notional machines: a Lambda Calculus crash course (28 ottobre 2021)
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Marco Raglianti - Visualizing Discord Servers - definitely not a virtual conference video replay (14 ottobre 2021)
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Michele Lanza - History is not a burden on the (computer) memory but an illumination of the (software engineering researcher's) soul (15 aprile 2021)
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Roberto Minelli - DFlow is dead. Long live Tako! (18 marzo 2021)
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Gabriele Bavota - On Lessons Learned while Replicating my Own Research (10 dicembre 2020)
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Matthias Hauswirth - Rainfall and LuCE: The Difficulty of Learning to Program (3 dicembre 2020)
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Nargiz Humbatova - Mutation Testing of Deep Learning Systems (26 novembre 2020)
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Alejandro Mazuera Rozo - Investigating types and survivability of performance bugs in mobile apps (19 novembre 2020)
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Matteo Biagiola - Testing the plasticity of reinforcement learning based systems (12 novembre 2020)
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Csaba Nagy - Analyzing SQL Queries Embedded in the Source Code (5 novembre 2020)
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Mohammad Rezaalipour - Deep Neural Network Bugs and the Challenges of Repairing Them (29 ottobre 2020)
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Luca Pascarella - Augmented Fine-Grained Defect Prediction for Code-Review (22 ottobre 2020)
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Diego Venâncio Marcílio - SpongeBugs: Automatically Fixing Static Analysis Tools Violations (15 ottobre 2020)
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Michael Weiss - Detecting Uncertainty in Deep Learning (27 febbraio 2020)
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Christoph Treude - Uncovering the best parts of software documentation (28 gennaio 2020)
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Bhargav Bhatt - DroidPLUMB: Repairing Resource-Leak bugs with Static Analysis (5 dicembre 2019)
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Francesco Magagnino - Envisioning the future of the customer interaction (21 novembre 2019)
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Armin Heinzl - How Pair Programming Influences Team Performance: The Role of backup-behavior, shared mental models, and task novelty (7 novembre 2019)
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Davide Paolo Tua - Time Evolving Voronoi Treemaps for Metrics Visualization (31 ottobre 2019)
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Bin Lin - Program Comprehension at ICSME 2019 (24 ottobre 2019)
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Ana Ivanchikj - Discovering Imgur API – Controlled Experiment (17 ottobre 2019)
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Marco D'Ambros - Dashboarding your inbox for fun and profit (3 ottobre 2019)
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Emad Aghajani - Software Documentation: How far we've come, and challenges ahead (26 settembre 2019)
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Andrea Stocco - Black-box Confidence Estimation for Misbehavior Prediction in Autonomous Driving Systems (19 settembre 2019)
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Jacopo Tagliabue - Less (Data) Is More: Why Small Data Holds the Key to the Future of Artificial Intelligence (24 giugno 2019)
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David Clark - The Theory of Testing Programs - An Information Theoretic View (19 giugno 2019)
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Jan Vitek - Getting everything wrong without doing anything right! (13 giugno 2019)
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Hridesh Rajan - Software as Data (12 giugno 2019)
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Alejandro Mazuera Rozo - SOFIA: An Automated Security Oracle for Black-Box Testing of SQL-Injection Vulnerabilities (23 maggio 2019)
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Jevgenija Pantiuchina - On the Naturalness of Buggy Code (16 maggio 2019)
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Richard Torkar - Why do we encourage even more missingness when having missing data? (9 maggio 2019)
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Fengcai Wen - Neural-Machine-Translation-Based Commit Message Generation: How Far Are We? (2 maggio 2019)
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Vincenzo Riccio - A Day in the (Activity) Lifecycle (18 aprile 2019)
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Luis Mastrangelo - Casting about in the Dark (11 aprile 2019)
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Gunel Jahangirova - Mutation Testing of Deep Learning Systems (4 aprile 2019)
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Andrea Mocci - The Tale of 'Quattro Tabelle' (28 marzo 2019)
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Carlo Alberto Furia - Why You Should Use Bayesian Statistics for Empirical Software Engineering (7 marzo 2019)
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Csaba Nagy - Beauty and the Beast: True Stories of Evolving Software Systems (28 febbraio 2019)
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Andrea Gallidabino - Liquid Software: Multi-Device Adaptation with Liquid Media Queries (21 febbraio 2019)