2,847 papers · page 44 of 143
Many machine learning (ML) algorithms are inherently random – multiple executions using the same inputs may produce slightly different results each time. Randomness impacts how developers write tests that check for end-to-end quality of their implementations of these ML algorithm…
We present LLSC, a prototype compiler for nondeterministic parallel symbolic execution of the LLVM intermediate representation (IR). Given an LLVM IR program, LLSC generates code preserving the symbolic execution semantics and orchestrating solver invocations. The generated code …
For ensuring the reliability of Android apps, there has been tremendous, continuous progress on improving automated GUI testing in the past decade. Specifically, dozens of testing techniques and tools have been developed and demonstrated to be effective in detecting crash bugs an…
Concurrency bugs are extremely difficult to detect. Recently, several dynamic techniques achieve sound analysis. M2 is even complete for two threads. It is designed to decide whether two events can occur consecutively. However, real-world concurrency bugs can involve more events …
Combinatorial problems (CPs) arise in many areas, and people use constraint solvers to automatically solve these problems. However, the state-of-the-art constraint solvers (e.g., Gecode and Chuffed) have overly complicated software architectures; they compute solutions inefficien…
Dynamic program slicing is used in a variety of tasks, including program debugging and security analysis. Despite being extensively studied in the literature, the only dynamic slicing solution for Java programs that is publicly available today is a tool named JavaSlicer. Unfortun…
Modern software applications are increasingly configurable, which puts a burden on users to tune these configurations for their target hardware and workloads. To help users, machine learning techniques can model the complex relationships between software configuration parameters …
Resource-driven systems have tasks that are bound by limited resources. These systems must adapt their tasks that cannot gain access to sufficient resources. This dissertation proposes a new resource-driven adaptation approach, which aims to support (1) task prioritisation using …
Community smells represent symptoms of sub-optimal organizational and social issues within software development communities that often lead to additional project costs and reduced software quality. Previous research identified a variety of community smells that are connected to s…
Testing web APIs automatically requires generating input data values such as addressess, coordinates or country codes. Generating meaningful values for these types of parameters randomly is rarely feasible, which means a major obstacle for current test case generation approaches.…
Knowing how exactly a bug has been introduced into the code can help developers debug the bug efficiently. However, techniques currently used to retrieve Bug Inducing Commits (BICs) from the repository timeline are limited in their accuracy. Automated bisection of the version his…
Developers need to perform adequate testing to ensure the quality of Automatic Speech Recognition (ASR) systems. However, manually collecting required test cases is tedious and time-consuming. Our recent work proposes CrossASR, a differential testing method for ASR systems. This …
One of the major challenges in the verification of complex industrial Cyber-Physical Systems is the difficulty of determining whether a particular system output or behaviour is correct or not, the so-called test oracle problem. Metamorphic testing alleviates the oracle problem by…
The Software Engineering (SE) community is prolific, making it challenging for experts to keep up with the flood of new papers and for neophytes to enter the field. Therefore, we posit that the community may benefit from a tool extracting terms and their interrelations from the S…
In recent years, many incidents have been reported where machine learning models exhibited discrimination among people based on race, sex, age, etc. Research has been conducted to measure and mitigate unfairness in machine learning models. For a machine learning task, it is a com…
Tracing requirements to their implementation is crucial to all stakeholders of a software development process. When managing software variability, requirements are typically expressed in terms of features, a feature being a user-visible characteristic of the software. While featu…
Authorship attribution (i.e., determining who is the author of a piece of source code) is an established research topic. State-of-the-art results for the authorship attribution problem look promising for the software engineering field, where they could be applied to detect plagia…
For any errorless fuzzing campaign, no matter how long, there is always some residual risk that a software error would be discovered if only the campaign was run for just a bit longer. Recently, greybox fuzzing tools have found widespread adoption. Yet, practitioners can only gue…
In this digital era, the textual content has become a seemingly ubiquitous part of our life. Natural Language Processing (NLP) empowers machines to comprehend the intricacies of textual data and eases human-computer interaction. Advancement in language modeling, continual learnin…
Increasingly, software is making autonomous decisions in case of criminal sentencing, approving credit cards, hiring employees, and so on. Some of these decisions show bias and adversely affect certain social groups (e.g. those defined by sex, race, age, marital status). Many pri…