Ajax-enabled web applications are a new breed of highly interac-tive, highly dynamic web applications. Although Ajax allows develop-ers to create rich web applications, Ajax applications can be difficult to comprehend and thus to maintain. For this reason, we have created FireDetective, a tool that uses dynamic analysis at both the client (browser) and server-side to facilitate the understanding of Ajax ap-plications. We evaluate FireDetective using (1) a pretest-posttest user study and (2) a field user study. Preliminary evidence shows that the FireDetective tool is an effective aid for web developers striving to understand Ajax applications. 1

The analysis of execution traces is a common practice in the context of software understanding. A major issue during this task is scalability, as the massive amounts of data often make the comprehension process difficult. A significant portion of this data overload can be attributed to repetitions

data produced by realistic program runs, most work has focused on separately collecting and compressing different types of profiles. In this paper we present a unified representation of profiles called Whole Execution Trace (WET) which includes the complete information contained in each of the above

data produced by realistic program runs, most work has focused on separately collecting and compressing different types of profiles. In this paper, we present a unified representation of profiles called Whole Execution Trace (WET), which includes the complete information contained in each of the above

Runtime Verification (RV) [8,10] is an approach to modeling and verification of software systems, which focuses on analyzing program executions. An execution can abstractly be considered as represented by an execution trace, a sequence of events. RV is, amongst other things, concerned with checking

Submitted in partial fulfilment of the requirements for Master of Computer Science.

We need to understand the impact of side effects whenever changing complex object-oriented software systems. This can be difficult as side effects are at best implicit in static views of the software, and typically execution traces do not capture data flow between parts of the system. To solve

Abstract. Dynamic analysis is the analysis of the properties of a running program. In order to perform dynamic analysis, information about the running program is often collected through execution traces. Exploring and analyzing these traces can be an issue due to their size and that knowledge of a

dependencies, and schedule the task in parallel across a node or cluster. While these schedulers simplify the pro-cess of parallel software development, they can obfuscate the performance characteristics of the execution of an algorithm. The execution trace has been used for many years to give developers a

platform independent executable trace. Our technique traces and virtualizes a regular program execution that is platform dependent, and generates a stand-alone program called the trace program. Run-ning the trace program re-generates the original execution. More importantly, trace program execution