Related papers: NuzzleBug: Debugging Block-Based Programs in Scrat…
Training set bugs are flaws in the data that adversely affect machine learning. The training set is usually too large for man- ual inspection, but one may have the resources to verify a few trusted items. The set of trusted items may not by…
Greybox fuzzing is a scalable and practical approach for software testing. Most greybox fuzzing tools are coverage-guided as reaching high code coverage is more likely to find bugs. However, since most covered codes may not contain bugs,…
Interactive program verification is characterized by iterations of unfinished proof attempts. To support the process of constructing a complete proof, many interactive program verification systems offer a proof scripting language as a…
Block-based programming environments such as Scratch are an essential entry point to computer science. In order to create an effective learning environment that has the potential to address the gender imbalance in computer science, it is…
By recording every state change in the run of a program, it is possible to present the programmer every bit of information that might be desired. Essentially, it becomes possible to debug the program by going ``backwards in time,'' vastly…
Surface cracks are a very common indicator of potential structural faults. Their early detection and monitoring is an important factor in structural health monitoring. Left untreated, they can grow in size over time and require expensive…
Debugging nondeterministic programs is inherently difficult, particularly in microcontroller environments where execution paths can diverge unpredictably due to external sensor inputs. Traditional debugging techniques often fail to capture…
Many logic programming languages have delay primitives which allow coroutining. This introduces a class of bug symptoms -- computations can flounder when they are intended to succeed or finitely fail. For concurrent logic programs this is…
In NLP, reusing pre-trained models instead of training from scratch has gained popularity; however, NLP models are mostly black boxes, very large, and often require significant resources. To ease, models trained with large corpora are made…
Large language models (LLMs) have become an essential tool to support developers using traditional text-based programming languages, but the graphical notation of the block-based Scratch programming environment inhibits the use of LLMs. To…
Debugging is commonly understood as finding and fixing the cause of a problem. But what does ``cause'' mean? How can we find causes? How can we prove that a cause is a cause--or even ``the'' cause? This paper defines common terms in…
As most parallel and distributed programs are internally non-deterministic -- consecutive runs with the same input might result in a different program flow -- vanilla cyclic debugging techniques as such are useless. In order to use cyclic…
Debugging physical computing projects provides a rich context to understand cross-disciplinary problem solving that integrates multiple domains of computing and engineering. Yet understanding and assessing students' learning of debugging…
A major difficulty in debugging distributed systems lies in manually determining which of the many available debugging tools to use and how to query its logs. Our own study of a production debugging workflow confirms the magnitude of this…
Context. Code smells, which are recurring anomalies in design or style, have been extensively researched in professional code. However, their significance in block-based projects created by novices is still largely unknown. Block-based…
We describe a system that simplifies the process of debugging programs produced by computer-aided parallelization tools. The system uses relative debugging techniques to compare serial and parallel executions in order to show where the…
Debugging distributed systems is hard. Most of the techniques that have been developed for debugging such systems use either extensive model checking, or postmortem analysis of logs and traces. Interactive debugging is typically a tool that…
Over 70% of security vulnerabilities in critical software systems today result from memory safety violations. To address this challenge, fuzzing and static analysis are widely used automated methods to discover such vulnerabilities. Fuzzing…
Debugging is considered as a rigorous but important feature of software engineering process. Since more than a decade, the software engineering research community is exploring different techniques for removal of faults from programs but it…
Block-based programming environments like Scratch have become widely adopted in Computer Science Education, but the mouse-based drag-and-drop interface can challenge users with disabilities. While prior work has provided solutions…