2,847 papers · page 54 of 143
Machine learning models are increasingly being used in important decision-making software such as approving bank loans, recommending criminal sentencing, hiring employees, and so on. It is important to ensure the fairness of these models so that no discrimination is made based on…
We present counterintuitive results for the scalability of fuzzing. Given the same non-deterministic fuzzer, finding the same bugs linearly faster requires linearly more machines. For instance, with twice the machines, we can find all known bugs in half the time. Yet, finding lin…
In this paper, we take the fundamental perspective of fuzzing as a learning process. Suppose before fuzzing, we know nothing about the behaviors of a program P: What does it do? Executing the first test input, we learn how P behaves for this input. Executing the next input, we ei…
Data stored in cloud services is highly sensitive and so access to it is controlled via policies written in domain-specific languages (DSLs). The expressiveness of these DSLs provides users flexibility to cover a wide variety of uses cases, however, unintended misconfigurations c…
Recommendations between colleagues are effective for encouraging developers to adopt better practices. Research shows these peer interactions are useful for improving developer behaviors, or the adoption of activities to help software engineers complete programming tasks. However…
Modern software is bloated. Demand for new functionality has led developers to include more and more features, many of which become unneeded or unused as software evolves. This phenomenon, known as software bloat, results in software consuming more resources than it otherwise nee…
We present a web-based Program Analysis Collaboratory (PAClab) tool that helps researchers to obtain realistic program benchmarks using user-defined selection criteria. Based on selection criteria, PAClab identifies relevant projects and its programs from open-source repositories…
We envision visual semantics learning (VSL), a novel methodology that derives high-level functional description of given software from its visual (graphical) outputs. By visual semantics, we mean the semantic description about the software’s behaviors that are exhibited in its vi…
We consider a usage model for automated machine learning (AutoML) in which users can influence the generated pipeline by providing a weak pipeline specification: an unordered set of API components from which the AutoML system draws the components it places into the generated pipe…
Unit testing focused on Modified Condition/Decision Coverage (MC/DC) criterion is essential in development safety-critical systems. However, design of test data that meets the MC/DC criterion currently needs detailed manual analysis of branching conditions in units under test by …
We present HOMI, a new technique to enhance symbolic execution by maintaining only a small number of promising states. In practice, symbolic execution typically maintains as many states as possible in a fear of losing important states. In this paper, however, we show that only a …
The landscape of web APIs is evolving to meet new client requirements and to facilitate how providers fulfill them. A recent web API model is GraphQL, which is both a query language and a runtime. Using GraphQL, client queries express the data they want to retrieve or mutate, and…
Machine learning software is increasingly being used to make decisions that affect people's lives. But sometimes, the core part of this software (the learned model), behaves in a biased manner that gives undue advantages to a specific group of people (where those groups are deter…
Deep neural networks (DNNs) have been widely applied in the software development process to automatically learn patterns from massive data. However, many applications still make decisions based on rules that are manually crafted and verified by domain experts due to safety or sec…
Deep learning (DL) becomes increasingly pervasive, being used in a wide range of software applications. These software applications, named as DL based software (in short as DL software), integrate DL models trained using a large data corpus with DL programs written based on DL fr…
The management of cloud service incidents (unplanned interruptions or outages of a service/product) greatly affects customer satisfaction and business revenue. After years of efforts, cloud enterprises are able to solve most incidents automatically and timely. However, in practic…
A large percentage of real-world software configuration issues, such as misconfigurations, involve multiple interdependent configuration parameters. However, existing techniques and tools either do not consider dependencies among configuration parameters— termed configuration dep…
Detecting Graphical User Interface (GUI) elements in GUI images is a domain-specific object detection task. It supports many software engineering tasks, such as GUI animation and testing, GUI search and code generation. Existing studies for GUI element detection directly borrow t…
In large-scale online service systems, incidents occur frequently due to a variety of causes, from updates of software and hardware to changes in operation environment. These incidents could significantly degrade system’s availability and customers’ satisfaction. Some incidents a…
There is a significant rise in the availability, development and size of software projects in the present day. Many open source projects are reused or updated for various purposes that include fixing bugs in existing projects, development and maintenance of project extensions. De…