26,098 papers · page 185 of 1,305
Context-free language (CFL) reachability is a fundamental framework for formulating program analyses. CFL-reachability analysis works on top of an edge-labeled graph by deriving reachability relations and adding them as labeled edges to the graph. Existing CFL-reachability algori…
As the world takes cognizance of AI's growing role in greenhouse gas(GHG) and carbon emissions, the focus of AI research & development is shifting towards inclusion of energy efficiency as another core metric. Sustainability, a core agenda for most organizations, is also being vi…
Bugs and their fixes in the code evolution histories are important assets for many software engineering tasks such as deriving new state-of-the-art automatic bug fixing techniques. Existing bug datasets are either manually built which is difficult to grow efficiently to a scale l…
This experience paper describes thirteen considerations for implementing machine learning software defect prediction (ML SDP) in vivo. Specifically, we provide the following report on the ground of the most important observations and lessons learned gathered during a large-scale …
Decentralized Finance (DeFi) apps have rapidly proliferated with the development of blockchain and smart contracts, whose maximum total value locked (TVL) has exceeded 100 billion dollars in the past few years. These apps allow users to interact and perform complicated financial …
Finite model finders give users the ability to specify properties of a system in mathematical logic and then automatically find concrete examples, called solutions, that satisfy the properties. These solutions are often viewed as a key benefit of model finders, as they create an …
Unit testing validates the correctness of the unit under test and has become an essential activity in software development process. A unit test consists of a test prefix that drives the unit under test into a particular state, and a test oracle (e.g., assertion), which specifies …
Proper incentives are important for motivating developers in open-source communities, which is crucial for maintaining the development of open-source software healthy. To provide such incentives, an accurate and objective developer contribution measurement method is needed. Howev…
SMT solvers are utilized to check the satisfiability of logic formulas and have been applied in various crucial domains, including software verification, test case generation, and program synthesis. However, bugs hidden in SMT solvers can lead to severe consequences, causing erro…
Autonomous agents equipped with Large Language Models (LLMs) are rapidly gaining prominence as a revolutionary technology within the realm of Software Engineering. These intelligent and autonomous systems demonstrate the capacity to perform tasks and make independent decisions, l…
The SZZ algorithm has been widely used for identifying bug-inducing commits. However, it suffers from low precision, as not all deletion lines in the bug-fixing commit are related to the bug fix. Previous studies have attempted to address this issue by using static methods to fil…
Large Language Models (LLMs) have demonstrated remarkable performance in code completion. However, due to the lack of domain-specific knowledge, they may not be optimal in completing code that requires intensive domain knowledge for example completing the library names. Although …
A FinTech system is a cluster of FinTech applications that intensively interact with databases containing a large quantity of user data. To ensure data consistency, it is a common practice to specify data constraints to validate data at runtime. However, data constraints often ev…
Adversarial examples are important to test and enhance the robustness of deep code models. As source code is discrete and has to strictly stick to complex grammar and semantics constraints, the adversarial example generation techniques in other domains are hardly applicable. More…
Deep learning has been widely adopted to tackle various code-based tasks by building deep code models based on a large amount of code snippets. While these deep code models have achieved great success, even state-of-the-art models suffer from noise present in inputs leading to er…
Designing and optimizing deep models require managing large datasets and conducting carefully designed controlled experiments that depend on large sets of hyper-parameters and problem dependent software/data configurations. These experiments are executed by training the model und…
The advent of edge devices dedicated to machine learning tasks enabled the execution of AI-based applications that efficiently process and classify the data acquired by the resource-constrained devices populating the Internet of Things. The proliferation of such applications (e.g…
Front-end developers want their applications to contain no more code than is needed in order to minimize the amount of time that elapses between visiting a web page and the page becoming responsive. However, front-end code is typically written in JavaScript, the ubiquitous “langu…
Reading source code occupies most of developer's daily activities. Any maintenance and evolution task requires developers to read and understand the code they are going to modify. For this reason, previous research focused on the definition of techniques to automatically assess t…
With the increased developments in quantum computing, the availability of systematic and automatic testing approaches for quantum programs is becoming increasingly essential. To this end, we present the quantum software testing tool QuCAT for combinatorial testing of quantum prog…