Ganesha Upadhyaya

• PhD
• Senior Researcher at Iowa State University

Many data-driven software engineering tasks such as discovering programming patterns, mining API specifications, etc., perform source code analysis over control flow graphs (CFGs) at scale. Analyzing millions of CFGs can be expensive and performance of the analysis heavily depends on the underlying CFG traversal strategy. State-of-the-art analysis...

Programmers often consult an online Q&A forum such as Stack Overflow to learn new APIs. This paper presents an empirical study on the prevalence and severity of API misuse on Stack Overflow. To reduce manual assessment effort, we design ExampleCheck, an API usage mining framework that extracts patterns from over 380K Java repositories on GitHub and...

Source code analysis at a large scale is useful for solving many software engineering problems, however, could be very expensive, thus, making its use difficult. This work proposes hybrid traversal, a technique for performing source code analysis over control flow graphs more efficiently. Analysis over a control flow graph requires traversing the g...

Popularity of data-driven software engineering has led to an increasing demand on the infrastructures to support efficient execution of tasks that require deeper source code analysis. While task optimization and parallelization are the adopted solutions, other research directions are less explored. We present collective program analysis (CPA), a te...

Encouraged by the success of data-driven software engineering (SE) techniques that have found numerous applications e.g. in defect prediction, specification inference, the demand for mining and analyzing source code repositories at scale has significantly increased. However, analyzing source code at scale remains expensive to the extent that data-d...

We introduce Candoia, a platform and ecosystem for building Mining Software Repositories (MSR) tools. The platform is designed to support building of MSR tools by providing necessary tools and abstractions that hide the complex details of version control, bug databases, source code programming languages and forges. The ecosystem allows easy sharing...

The need for concurrency in modern software is increasingly fulfilled by utilizing the message passing paradigm because of its modularity and scalability. In the message passing paradigm, concurrently running processes communicate by sending and receiving messages. Asynchronous messaging introduces the possibility of message ordering problems: two...

Efficient mapping of message passing concurrency (MPC) abstractions to Java Virtual Machine (JVM) threads is critical for performance, scalability, and CPU utilization; but tedious and time consuming to perform manually. In general, this mapping cannot be found in polynomial time, but we show that by exploiting the local characteristics of MPC abst...

Actor frameworks running on Java Virtual Machine (JVM) platform face two main challenges in utilizing multi-core architectures, i) efficiently mapping actors to JVM threads, and ii) scheduling JVM threads on multi-core. JVM-based actor frameworks allow fine tuning of actors to threads mapping, however scheduling of threads on multi-core is left to...