2,847 papers · page 71 of 143
Software debugging is a time-consuming and challenging process. Supporting debugging has been a focus of the software engineering field since its inception with numerous empirical studies, theories, and tools to support developers in this task. Performance bugs and performance de…
Software engineering practices have evolved to the point where a developer writing a new application today doesn’t start from scratch, but reuses a number of open source libraries and components. These third-party libraries evolve independently of the applications in which they a…
Recently, the k-induction algorithm has proven to be a successful approach for both finding bugs and proving correctness. However, since the algorithm is an incremental approach, it might waste resources trying to prove incorrect programs. In this paper, we extend the k-induction…
In large-scale distributed systems, node crashes are inevitable, and can happen at any time. As such, distributed systems are usually designed to be resilient to these node crashes via various crash recovery mechanisms, such as write-ahead logging in HBase and hinted handoffs in …
Learning-based clone detection is widely exploited for binary vulnerability search. Although they solve the problem of high time overhead of traditional dynamic and static search approaches to some extent, their accuracy is limited, and need to manually identify the true positive…
App reviews play an essential role for users to convey their feedback about using the app. The critical information contained in app reviews can assist app developers for maintaining and updating mobile apps. However, the noisy nature and large-quantity of daily generated app rev…
In 2007, the Deckard paper was published at ICSE. Since its publication, it has led to much follow-up research and applications. The paper made two core contributions: a novel vector embedding of structured code for fast similarity detection, and an application of the embedding f…
Developing Big Data Analytics often involves trial and error debugging, due to the unclean nature of datasets or wrong assumptions made about data. When errors (e.g. program crash, outlier results, etc.) arise, developers are often interested in pinpointing the root cause of erro…
Deep learning (DL) systems are increasingly applied to safety-critical domains such as autonomous driving cars. It is of significant importance to ensure the reliability and robustness of DL systems. Existing testing methodologies always fail to include rare inputs in the testing…
The timing characteristics of cache, a high-speed storage between the fast CPU and the slow memory, may reveal sensitive information of a program, thus allowing an adversary to conduct side-channel attacks. Existing methods for detecting timing leaks either ignore cache all toget…
This work models the reliability of software systems using recurrent neural networks with long short-term memory (LSTM) units and truncated backpropagation algorithm, and encoder-decoder LSTM architecture and proposes LSTM with software reliability functions as activation functio…
Delta debugging (DD) is an approach to automating the debugging activities based on systematic testing. DD algorithms find the cause of a regression of a program by minimizing the changes applied between a working version and a faulty version of the program. However, it is still …
Bidirectional model transformation (BX) plays a vital role in Model-Driven Engineering. A major challenge in conventional relational and bidirectionalization-based BX approaches is the ambiguity issue, i.e., the backward transformation may not be uniquely determined by the consis…
Logs are often used for troubleshooting in large-scale software systems. For a cloud-based online system that provides 24/7 service, a huge number of logs could be generated every day. However, these logs are highly imbalanced in general, because most logs indicate normal system …
In Model-Driven Software Development, models are automatically processed to support the creation, build, and execution of systems. A large variety of dedicated model-transformation languages exists, promising to efficiently realize the automated processing of models. To investiga…
Dynamically typed languages such as JavaScript and Python are increasingly popular, yet static typing has not been totally eclipsed: Python now supports type annotations and languages like TypeScript offer a middle-ground for JavaScript: a strict superset of JavaScript, to which …
Proofs play a key role in reasoning about programs and verification of properties of systems. Mechanized proof assistants help users in developing and checking the consistency of proofs using the proof language developed by the systems; but even then writing proofs is tedious and…
With the rise of machine learning, there is a great deal of interest in treating programs as data to be fed to learning algorithms. However, programs do not start off in a form that is immediately amenable to most off-the-shelf learning techniques. Instead, it is necessary to tra…
Mobile apps collect dierent categories of personal information to provide users with various services. Companies use privacy policies containing critical requirements to inform users about their data practices. With the growing access to personal information and the scale of mobi…
UI testing is known to be difficult, especially as today’s development cycles become faster. Manual UI testing is tedious, costly and error- prone. Automated UI tests are costly to write and maintain. This paper presents AppFlow, a system for synthesizing highly robust, highly re…