4,951 papers · page 33 of 248
Data constraints are widely used in FinTech systems for monitoring data consistency and diagnosing anomalous data manipulations. However, many equivalent data constraints are created redundantly during the development cycle, slowing down the FinTech systems and causing unnecessar…
The exponential growth of social media platforms such as Twitter and Facebook has revolutionized textual communication and textual content publication in human society. However, they have been increasingly exploited to propagate toxic content, such as hate speech, malicious adver…
Software systems introduce an increasing number of configuration options to provide flexibility, and support updating the options on the fly to provide persistent services. This mechanism, however, may affect the system reliability, leading to unexpected results like software cra…
Mini-programs, which are programs running inside mobile super apps such as WeChat, often have access to privacy-sensitive information, such as location data and phone numbers, through APUs provided by the super apps. This access poses a risk of privacy sensitive data leaks, eithe…
Today's software failures have two dominating root causes: code bugs and misconfigurations. To combat failure-inducing software changes, unified regression testing (URT) is needed to synergistically test the changed code and all changed production configurations for deployment re…
The advances of machine learning (ML) including deep learning (DL) have enabled several approaches to implicitly learn vulnerable code patterns to automatically detect software vulnerabilities. A recent study showed that despite successes, the existing ML/DL-based vulnerability d…
As one of bad smells in code, code clones may increase the cost of software maintenance and the risk of vulnerability propagation. In the past two decades, numerous clone detection technologies have been proposed. They can be divided into text-based, token-based, tree-based, and …
Using API should follow its specifications. Otherwise, it can bring security impacts while the functionality is damaged. To detect API misuse, we need to know what its specifications are. In addition to being provided manually, current tools usually mine the majority usage in the…
The IFDS framework supports interprocedural dataflow analysis with distributive flow functions over finite domains. A large class of interprocedural dataflow analysis problems can be formulated as IFDS problems and thus can be solved with the IFDS framework precisely. Unfortunate…
Reducing energy consumption of software is an increasingly important objective, and there has been extensive research for data centers, smartphones, and embedded systems. However, when it comes to software, we lack working tools and methods to directly reduce energy consumption. …
Symbolic execution is a powerful program analysis and testing technique. Symbolic execution engines are usually implemented as interpreters, and the induced interpretation over-head can dramatically inhibit performance. Alternatively, implementation choices based on instrumentati…
Prior studies have demonstrated the effectiveness of Deep Learning (DL) in automated software vulnerability detection. Graph Neural Networks (GNNs) have proven effective in learning the graph representations of source code and are commonly adopted by existing DL-based vulnerabili…
As a widely-used platform to support various Java-bytecode-based applications, Java Virtual Machine (JVM) incurs severe performance loss caused by its real-time program interpretation mechanism. To tackle this issue, the Just-in- Time compiler (JIT) has been widely adopted to str…
Third-party libraries (TPLs) are frequently used in software to boost efficiency by avoiding repeated developments. However, the massive using TPLs also brings security threats since TPLs may introduce bugs and vulnerabilities. Therefore, software composition analysis (SCA) tools…
Modern software systems are increasingly relying on dependencies from the ecosystem. A recent estimation shows that around 35% of an open-source project's code come from its depended libraries. Unfortunately, open-source libraries are often threatened by various vulnerability iss…
Despite their stunning performance, developing deep learning models from scratch is a formidable task. Therefore, it popularizes Machine-Learning-as-a-Service (MLaaS), where general users can access the trained models of MLaaS providers via Application Programming Interfaces (API…
The rapid growth of software supply chain attacks has attracted considerable attention to software bill of materials (SBOM). SBOMs are a crucial building block to ensure the transparency of software supply chains that helps improve software supply chain security. Although there a…
Testing Machine Learning (ML) projects is challenging due to inherent non-determinism of various ML algorithms and the lack of reliable ways to compute reference results. Developers typically rely on their intuition when writing tests to check whether ML algorithms produce accura…
Automated Program Repair (APR) aims to help developers automatically patch software bugs. However, current state-of-the-art traditional and learning-based APR techniques face the problem of limited patch variety, failing to fix complicated bugs. This is mainly due to the reliance…
Computer graphics are powered by graphics APIs (e.g., OpenGL, Direct3D) and their associated shader compilers, which render high-quality images by compiling and optimizing user-written high-level shader programs into GPU machine code. Graphics rendering is extensively used in pro…