In order to program parallel and distributed systems efficiently, a systematic way of defining and understanding the complex behavior of process interactions in concurrent programs is needed. A proven method for understanding existing programs is event-driven monitoring which abstracts the program behavior to a sequence of events. These event traces are analyzed for debugging and tuning of the ...

Program debugging is an extremely time-consuming process, and it takes up a large portion of software development time. In practice, debugging is still very much of an art, with the developer painstakingly going through volumes of execution traces to locate the actual cause of an observable error. In this work, we discuss recent advances in debugging which makes it systematic scientific activit...

The notion of event constitutes the basis of the target program behavior model. This model, called H-space (History-space), is formally defined through a set of axioms (event grammar) for two basic relations, which may hold between two arbitrary events: the events may be sequentially ordered or one of them might be included in another composite event. Target program execution history is represe...

Nondeterministic nature of parallel programs is the major difficulty in debugging. Order-replay, a technique to solve this problem, is widely used because of its small overhead. It has, however, several serious drawbacks: all processes of the parallel program have to participate in replay even when some of them are clearly not involved with the bug; and the programmer cannot stop the process be...

Based on the technique for finding errors in new object intents a method of debugging source code is presented. This method is capable of finding strict implicative dependencies between lines of source code covered in successful and failed runs. The output is a logical expression. Using the new method it is possible to come closer to debugging programs on a logical level not checking executions...

It is difficult to debug a program when the data set that causes it to fail is large (or voluminous). The cues that may help in locating the fault are obscured by the large amount of information that is generated from processing the data set. Clearly, a smaller data set which exhibits the same failure should lead to the diagnosis of the fault more quickly than the initial, large data set. We te...

Program debugging is an important part of the domain expertise required for intelligent tutoring systems that teach programming languages. This article explores the process by which student programs can be automatically debugged in order to increase the instructional capabilities of these systems. The research presented provides a methodology and implementation for the diagnosis and correction ...

This paper introduces the bisection debugging model. The key idea is to use a debugger to identify the semantic differences between two versions of the same program. The debugger leads the user (programmer) to the region of the source code that is different between the versions and effects erroneous behavior. To implement bisection debugging, a debugger must insert checkpoints around regions of...

We present a novel approach to program debugging and dynamic program analysis based on a temporal data model and query language. The data model exposes a point-based view of executions, while the underlying data is represented using intervals, for efficiency reasons. The point-based query language supports selection, projection, joins, grouping/aggregation, and recursion on both data and tempor...

We present automated techniques for the explanation of counter-examples, where a counter-example should be understood as a sequence of program statements. Our approach is based on variable dependency analysis and is applicable to programs written in Cimple, an expressive subset of the C programming language. Central to our approach is the derivation of a focus-statement sequence (FSS) from a gi...