4,951 papers · page 14 of 248
Deep learning models are trained with certain assumptions about the data during the development stage and then used for prediction in the deployment stage. It is important to reason about the trustworthiness of the model's predictions with unseen data during deployment. Existing …
Large Language Models (LLM) are a new class of computation engines, "programmed" via prompt engineering. Researchers are still learning how to best "program" these LLMs to help developers. We start with the intuition that developers tend to consciously and unconsciously collect s…
Large language models have gained significant popularity because of their ability to generate human-like text and potential applications in various fields, such as Software Engineering. Large language models for code are commonly trained on large unsanitised corpora of source cod…
Numerous tools rely on automatic categorization of Android apps as part of their methodology. However, incorrect categorization can lead to inaccurate outcomes, such as a malware detector wrongly flagging a benign app as malicious. One such example is the SlideIT Free Keyboard ap…
Software build systems specify how source code is transformed into deliverables. Keeping build systems in sync with the software artifacts that they build while retaining their capacity to quickly produce updated deliverables requires a serious investment of development effort. E…
Black-box context-free grammar inference is a hard problem as in many practical settings it only has access to a limited number of example programs. The state-of-the-art approach Arvada heuristically generalizes grammar rules starting from flat parse trees and is non-deterministi…
Code generation tools driven by artificial intelligence have recently become more popular due to advancements in deep learning and natural language processing that have increased their capabilities. The proliferation of these tools may be a double-edged sword because while they c…
Database Management Systems (DBMSs) process a given query by creating a query plan, which is subsequently executed, to compute the query's result. Deriving an efficient query plan is challenging, and both academia and industry have invested decades into researching query optimiza…
With the rapid growth of Artificial Intelligence (AI) applications supported by deep learning (DL), the energy efficiency of these applications has an increasingly large impact on sustainability. We introduce Smaragdine, a new energy accounting system for tensor-based DL programs…
Continuous integration and continuous delivery (CI/CD) has become a prevalent practice in software development. GitHub Actions is emerging as a popular platform for implementing CI/CD pipelines, called workflows, especially because the platform offers 2,000 minutes of computation…
Developers frequently use the web to locate API examples that help them solve their programming tasks. While sites like Stack Overflow (SO) contain API examples embedded within their textual descriptions, developers cannot access this API knowledge directly. Instead they need to …
With practical code reuse, the code fragments from developers' forums often migrate to applications. Owing to the incomplete nature of such fragments, they often lack the details on exception handling. The adaptation for exception handling to the codebase is not trivial as develo…
Recently, Graph Neural Network (GNN)-based vulnerability detection systems have achieved remarkable success. However, the lack of explainability poses a critical challenge to deploy black-box models in security-related domains. For this reason, several approaches have been propos…
Graphical User Interface (GUI) testing is one of the primary approaches for testing mobile apps. Test scripts serve as the main carrier of GUI testing, yet they are prone to obsolescence when the GUIs change with the apps' evolution. Existing repair approaches based on GUI layout…
LTL solvers check the satisfiability of Linear-time Temporal Logic (LTL) formulas and are widely used for verifying and testing critical software systems. Thus, potential bugs in the solvers' implementations can have a significant impact. We present SpecBCFuzz, a fuzzing method f…
The growth of the decentralized finance (DeFi) ecosystem built on blockchain technology and smart contracts has led to an increased demand for secure and reliable smart contract development. However, attacks targeting smart contracts are increasing, causing an estimated $6.45 bil…
In software development, developers extensively utilize third-party libraries to avoid implementing existing functionalities. When a new third-party library vulnerability is disclosed, project maintainers need to determine whether their projects are affected by the vulnerability,…
Currently, smart contract vulnerabilities (SCVs) have emerged as a major factor threatening the transaction security of blockchain. Existing state-of-the-art methods rely on deep learning to mitigate this threat. They treat each input contract as an independent entity and feed it…
Modern integrated development environments (IDEs) provide various automated code suggestion techniques (e.g., code completion and code generation) to help developers improve their efficiency. Such techniques may retrieve similar code snippets from the code base or leverage deep l…
In decentralized finance (DeFi), lenders can offer flash loans to borrowers, i.e., loans that are only valid within a blockchain transaction and must be repaid with fees by the end of that transaction. Unlike normal loans, flash loans allow borrowers to borrow large assets withou…