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Researchers have developed various techniques for static analysis of JavaScript to improve analysis precision. To develop such techniques, they first identify causes of the precision losses for unproven properties. While most of the…
Dependency analysis is a technique to identify and determine data dependencies between service protocols. Protocols evolving concurrently in the service composition need to impose an order in their execution if there exist data…
When developing mobile apps, programmers rely heavily on standard API frameworks and libraries. However, learning and using those APIs is often challenging due to the fast-changing nature of API frameworks for mobile systems, the complexity…
This paper introduces a method for detecting vulnerabilities in smart contracts using static analysis and a multi-objective optimization algorithm. We focus on four types of vulnerabilities: reentrancy, call stack overflow, integer…
Blockchain smart contracts have emerged as a transformative force in the digital realm, spawning a diverse range of compelling applications. Since solidity smart contracts across various domains manage trillions of dollars in virtual coins,…
Automatically generated static code warnings suffer from a large number of false alarms. Hence, developers only take action on a small percent of those warnings. To better predict which static code warnings should not be ignored, we suggest…
This review paper synthesizes the latest research on performance optimization strategies for serverless applications deployed on AWS Lambda. By examining recent studies, we highlight the challenges, solutions, and best practices for…
Software organizations want to be able to base their decisions on the latest set of available data and the real-time analytics derived from them. In order to support "real-time enterprise" for software organizations and provide information…
We introduce SWE-PRBench, a benchmark of 350 pull requests with human-annotated ground truth for evaluating AI code review quality. Evaluated against an LLM-as-judge framework validated at kappa=0.75, 8 frontier models detect only 15-31% of…
Static analysis tools are commonly used to detect defects before the code is released. Previous research has focused on their overall effectiveness and their ability to detect defects. However, little is known about the usage patterns of…
Static analysis is one of the most widely adopted techniques to find software bugs before code is put in production. Designing and implementing effective and efficient static analyses is difficult and requires high expertise, which results…
Just like other software, spreadsheets can contain significant faults. Static analysis is an accepted and well-established technique in software engineering known for its capability to discover faults. In recent years, a growing number of…
In the evolving IT landscape, stability and reliability of systems are essential, yet their growing complexity challenges DevOps teams in implementation and maintenance. Log analysis, a core element of AIOps, provides critical insights into…
When analyzing programs, large libraries pose significant challenges to static points-to analysis. A popular solution is to have a human analyst provide points-to specifications that summarize relevant behaviors of library code, which can…
The distributed data analytic system -- Spark is a common choice for processing massive volumes of heterogeneous data, while it is challenging to tune its parameters to achieve high performance. Recent studies try to employ auto-tuning…
The rapid adoption of blockchain technology highlighted the importance of ensuring the security of smart contracts due to their critical role in automated business logic execution on blockchain platforms. This paper provides an empirical…
Data science pipelines to train and evaluate models with machine learning may contain bugs just like any other code. Leakage between training and test data can lead to overestimating the model's accuracy during offline evaluations, possibly…
In the era of big data, ensuring the quality of datasets has become increasingly crucial across various domains. We propose a comprehensive framework designed to automatically assess and rectify data quality issues in any given dataset,…
Monitoring the network performance experienced by the end-user is crucial for managers of wireless networks as it can enable them to remotely modify the network parameters to improve the end-user experience. Unfortunately, for performance…
The source code of Function as a Service (FaaS) applications is constantly being refined. To detect if a source code change introduces a significant performance regression, the traditional benchmarking approach evaluates both the old and…