Roberto Verdecchia, Postdoctoral Research Fellow, bio photo

Roberto Verdecchia

Computer Scientist, Research Fellow at VU.

  G. Scholar   ResearchGate LinkedIn Twitter Github   Skype e-Mail

Awards

❖ Facebook Testing and Verification Research Award
Facebook Testing and Verification Symposium 2019 (Facebook TAV 2019)

Awarded for the project: "Static Prediction of Test Flakiness"
Research grant: 50K$
Abstract: The goal of this project is to develop an approach that can detect test flakiness early, preventing as far as possible that flaky tests are committed to test repositories. We propose FLAST, a fully automated approach that checks each new test method and provides a flakiness assessment: test labeled as flaky can be immediately returned to their creator for analysis and revision, whereas test cases that do not look suspicious are safely released to test suite repositories. FLAST is based exclusively on the application of well-known and fast static analysis techniques to test code. In fact, FLAST is a lightweight pre-screening technique that can complement other dynamic approaches: these will still be used, but on a much smaller set (i.e., those few test cases that fail intermittently after having passed FLAST filtering). Indeed, the advent of FLAST will transform the current ATAFistic world into a more lively AFTAFistic world (Assume Few Tests Are Flaky). Given the high impact of flaky tests both on software development costs and on developers’ motivation, predicting them timely and with high precision will bring great gains with exceptionally low additional costs.


❖ ACM SIGSOFT Distinguished Paper Award
41st IEEE/ACM International Conference on Software Engineering (ICSE 2019)

Roberto Verdecchia ICSE 2019 Award


Awarded for the paper: "Scalable Approaches for Test Suite Reduction"
Abstract: Test suite reduction approaches aim at decreasing software regression testing costs by selecting a representative subset from large-size test suites. Most existing techniques are too expensive for handling modern massive systems and moreover depend on artifacts, such as code coverage metrics or specification models, that are not commonly available at large scale. We present a family of novel very efficient approaches for similaritybased test suite reduction that apply algorithms borrowed from the big data domain together with smart heuristics for finding an evenly spread subset of test cases. The approaches are very general since they only use as input the test cases themselves (test source code or command line input). We evaluate four approaches in a version that selects a fixed budget B of test cases, and also in an adequate version that does the reduction guaranteeing some fixed coverage. The results show that the approaches yield a fault detection loss comparable to state-of-the-art techniques, while providing huge gains in terms of efficiency. When applied to a suite of more than 500K real world test cases, the most efficient of the four approaches could select B test cases (for varying B values) in less than 10 seconds.


❖ Best Early Career Researcher Award
15th IEEE International Conference on Software Architecture (ICSA 2018)

Roberto Verdecchia ICSA 2018 Award


Research statement: In software-intensive systems, technical debt is a metaphor encompassing design and implementation constructs that are used as expedients in the short term, but that hinder future maintainability and evolvability. Architectural technical debt, in turn, adopts such concept by considering sub-optimal architectural design and implementation choices that bring short-term benefits to the cost of the long-term gradual deterioration of the quality of the software architecture. Architectural technical debt is an active field of research. Nevertheless, how to accurately identify and manage architectural technical debt is still an open question. Our research aims to fill this gap. In particular, our goal is to: (i) consolidate the existing knowledge of architectural technical debt identification and its management in practice, (ii) conceive novel identification and management approaches built upon the existing state of the art techniques and industrial needs, and (iii) provide empirical evidence of architectural technical debt phenomena and assess the viability of the conceived approaches. As a result, we envision a sound methodology aimed to support software architects in the identification and management of architectural technical debt throughout the software development process


❖ Best Paper Award
52th Hawaii International Conference on System Sciences (HICSS 2019)

Roberto Verdecchia HICSS 2019 2018 Award


Awarded for the paper: "DecidArch: Playing Cards as Software Architects"
Abstract: Teaching software architecture is a challenge because of the difficulty to expose students to actual meaningful design situations. Games can provide a useful illustration of the design decision making process, and teach students the power of team interaction for making sound decisions.We introduce a game –DecidArch– developed to achieve three learning objectives: (i) create awareness about the rationale involved in design decision making, (ii) enable appreciation of the reasoning behind candidate design decisions proposed by others, and (iii) create awareness about interdependencies between design decisions. The game has been played by 22 groups with a total of 83 players, all of them students of the VU software architecture course. We present some of the lessons learned, both from our observation and through participant survey. We conclude that the game well supports our three learning objectives, and we identify several improvement points for future game editions.


❖ Runner-up Best Paper Award
5th International Conference on ICT for Sustainability (ICT4S 2018)

Awarded for the paper: "Empirical Evaluation of the Energy Impact of Refactoring Code Smells"
Abstract: Software energy efficiency has gained the increasing attention of the research community. How to improve it, however, still lacks evidence. Specifically, the impact of code smell refactoring on energy efficiency has been scarcely investigated. In the exploratory study here reported, we investigate the impact on performance and energy consumption of refactoring well-known code smells on Java software applications. In order to understand if software metrics can be used as indicators of the energy impact of refactoring, we also measured the variation caused by refactoring on a set of well-established software metrics. We conducted a controlled experiment using state-of-the-art power measurement equipment. Statistical hypothesis testing and effect size estimation were performed on the experimental results, which show that in one out of three applications, refactoring each smell significantly impacted power- and energy consumption. E.g., refactoring Feature Envy and Long Method smells led to a 49% energy efficiency improvement. No software metric, however, significantly correlated with execution time, power or energy consumption. In conclusion, refactoring code smells resulted to be a viable process to significantly improve software energy efficiency. The magnitude of the impact may depend on application properties, e.g. size or age. Further research is needed to understand the relationship between software metrics and energy efficiency.


❖ ISSIP-IBM-CBA Student Paper Award for Best Industry Studies Paper
52th Hawaii International Conference on System Sciences (HICSS 2019)

Roberto Verdecchia HICSS 2019 2018 Award


Awarded for the paper: "DecidArch: Playing Cards as Software Architects"
Abstract: Teaching software architecture is a challenge because of the difficulty to expose students to actual meaningful design situations. Games can provide a useful illustration of the design decision making process, and teach students the power of team interaction for making sound decisions.We introduce a game –DecidArch– developed to achieve three learning objectives: (i) create awareness about the rationale involved in design decision making, (ii) enable appreciation of the reasoning behind candidate design decisions proposed by others, and (iii) create awareness about interdependencies between design decisions. The game has been played by 22 groups with a total of 83 players, all of them students of the VU software architecture course. We present some of the lessons learned, both from our observation and through participant survey. We conclude that the game well supports our three learning objectives, and we identify several improvement points for future game editions.


❖ Bronze medal - ACM Student Research Competition
5th International Conference on Mobile Software Engineering and System (MobileSoft 2018)

Roberto Verdecchia MobileSoft 2018 Award


Awarded for the paper: "Identifying Architectural Technical Debt in Android Applications through Compliance Checking"
Abstract: By considering the fast pace at which mobile applications need to evolve, Architectural Technical Debt results to be a crucial yet implicit factor of success. In this research we present an approach to automatically identify Architectural Technical Debt in Android applications. The approach takes advantage of architectural guide- lines extraction and modeling, architecture reverse engineering, and compliance checking. As future work, we plan to automate the process and empirically evaluate it via large-scale experiments.