Antonio Filieri
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View article: Robust Probabilistic Model Checking with Continuous Reward Domains
Robust Probabilistic Model Checking with Continuous Reward Domains Open
Probabilistic model checking traditionally verifies properties on the expected value of a measure of interest. This restriction may fail to capture the quality of service of a significant proportion of a system's runs, especially when the …
View article: Rigorous Assessment of Model Inference Accuracy using Language Cardinality
Rigorous Assessment of Model Inference Accuracy using Language Cardinality Open
Models such as finite state automata are widely used to abstract the behavior of software systems by capturing the sequences of events observable during their execution. Nevertheless, models rarely exist in practice and, when they do, get …
View article: Compositional Taint Analysis for Enforcing Security Policies at Scale
Compositional Taint Analysis for Enforcing Security Policies at Scale Open
Automated static dataflow analysis is an effective technique for detecting security critical issues like sensitive data leak, and vulnerability to injection attacks. Ensuring high precision and recall requires an analysis that is context, …
View article: Neural-Based Test Oracle Generation: A Large-Scale Evaluation and Lessons Learned
Neural-Based Test Oracle Generation: A Large-Scale Evaluation and Lessons Learned Open
Defining test oracles is crucial and central to test development, but manual construction of oracles is expensive. While recent neural-based automated test oracle generation techniques have shown promise, their real-world effectiveness rem…
View article: Probabilistic Counterexample Guidance for Safer Reinforcement Learning (Extended Version)
Probabilistic Counterexample Guidance for Safer Reinforcement Learning (Extended Version) Open
Safe exploration aims at addressing the limitations of Reinforcement Learning (RL) in safety-critical scenarios, where failures during trial-and-error learning may incur high costs. Several methods exist to incorporate external knowledge o…
View article: Sibyl Datasets
Sibyl Datasets Open
This upload includes the three datasets used in the experimental evaluation of the algorithm selector Sibyl for the submission "Sibyl: Improving Software Engineering Tools with SMT Selection". We also include the pre-comupted graphs. The a…
View article: Sibyl Datasets
Sibyl Datasets Open
This upload includes the three datasets used in the experimental evaluation of the algorithm selector Sibyl for the submission "Sibyl: Improving Software Engineering Tools with SMT Selection". We also include the pre-comupted graphs. The a…
View article: Rigorous Assessment of Model Inference Accuracy using Language Cardinality
Rigorous Assessment of Model Inference Accuracy using Language Cardinality Open
Models such as finite state automata are widely used to abstract the behavior of software systems by capturing the sequences of events observable during their execution. Nevertheless, models rarely exist in practice and, when they do, get …
View article: Input splitting for cloud-based static application security testing platforms
Input splitting for cloud-based static application security testing platforms Open
As software development teams adopt DevSecOps practices, application security is increasingly the responsibility of development teams, who are required to set up their own Static Application Security Testing (SAST) infrastructure.
View article: Quality-Aware DevOps Research: Where Do We Stand?
Quality-Aware DevOps Research: Where Do We Stand? Open
DevOps is an emerging paradigm that reduces the barriers between developers and operations teams to offer continuous fast delivery and enable quick responses to changing requirements within the software life cycle. A significant volume of …
View article: Empirical Standards for Software Engineering Research
Empirical Standards for Software Engineering Research Open
Empirical Standards are natural-language models of a scientific community's expectations for a specific kind of study (e.g. a questionnaire survey). The ACM SIGSOFT Paper and Peer Review Quality Initiative generated empirical standards for…
View article: ACM SIGSOFT Empirical Standards.
ACM SIGSOFT Empirical Standards. Open
Empirical Standards are brief public document that communicate expectations for a specific kind of study (e.g. a questionnaire survey). The ACM SIGSOFT Paper and Peer Review Quality Initiative generated empirical standards for common resea…
View article: On the probabilistic analysis of neural networks
On the probabilistic analysis of neural networks Open
Neural networks are powerful tools for automated decision-making, seeing increased application in safety-critical domains, such as autonomous driving. Due to their black-box nature and large scale, reasoning about their behavior is challen…
View article: An evaluation of pure spectrum‐based fault localization techniques for large‐scale software systems
An evaluation of pure spectrum‐based fault localization techniques for large‐scale software systems Open
Summary Pure spectrum‐based fault localization (SBFL) is a well‐studied statistical debugging technique that only takes a set of test cases (some failing and some passing) and their code coverage as input and produces a ranked list of susp…
View article: Automated control of multiple software goals using multiple actuators
Automated control of multiple software goals using multiple actuators Open
Modern software should satisfy multiple goals simultaneously: it should provide predictable performance, be robust to failures, handle peak loads and deal seamlessly with unexpected conditions and changes in the execution environment. For …
View article: Self-Adaptive Video Encoder: Comparison of Multiple Adaptation Strategies Made Simple (Artifact)
Self-Adaptive Video Encoder: Comparison of Multiple Adaptation Strategies Made Simple (Artifact) Open
This paper presents an adaptive video encoder that can be used to compare the behavior of different adaptation strategies using multiple actuators to steer the encoder towards a global goal, composed of multiple conflicting objectives. A v…
View article: On the probabilistic symbolic analysis of programs
On the probabilistic symbolic analysis of programs Open
Recently we have proposed symbolic execution techniques for the probabilistic analysis of programs. These techniques seek to quan- tify the probability of a program to satisfy a property of interest under a relevant usage profile. We descr…
View article: Approximate and Probabilistic Computing: Design, Coding, Verification (Dagstuhl Seminar 15491)
Approximate and Probabilistic Computing: Design, Coding, Verification (Dagstuhl Seminar 15491) Open
Computing has entered the era of approximation, in which hardware and software generate and reason about estimates. Navigation applications turn maps and location estimates from hardware GPS sensors into driving directions; speech recognit…