Many workload characterization studies depend on accurate measurements of the cost of executing a piece of code. Often these measurements are conducted using infrastructures to access hardware performance counters. Most modern processors provide such counters to count micro-architectural events such as retired instructions or clock cycles. These counters can be difficult to configure, may not be programmable or readable from user-level code, and can not discriminate between events caused by different software threads. Various software infrastructures address this problem, providing access to per-thread counters from application code. This paper constitutes the first comparative study of the accuracy of three commonly used measurement infrastructures (perfctr, perfmon2, and PAPI) on three common processors (Pentium D, Core 2 Duo, and AMD ATHLON 64 X2). We find significant differences in accuracy of various usage patterns for the different infrastructures and processors. Based on these results we provide guidelines for finding the best measurement approach.

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Traditional profilers identify where a program spends most of its resources. They do not provide information about why the program spends those resources or about how resource consumption would change for different program inputs. In this paper we introduce the idea of algorithmic profiling . While a traditional profiler determines a set of measured cost values , an algorithmic profiler determines a cost function . It does that by automatically determining the "inputs" of a program, by measuring the program's "cost" for any given input, and by inferring an empirical cost function.

A significant body of prior work has devised approaches for automating the functional testing of interactive applications. However, little work exists for automatically testing their performance. Performance testing imposes additional requirements upon GUI test automation tools: the tools have to be able to replay complex interactive sessions, and they have to avoid perturbing the application's performance. We study the feasibility of using five Java GUI capture and replay tools for GUI performance test automation. Besides confirming the severity of the previously known GUI element identification problem, we also describe a related problem, the temporal synchronization problem, which is of increasing importance for GUI applications that use timer-driven activity. We find that most of the tools we study have severe limitations when used for recording and replaying realistic sessions of real-world Java applications and that all of them suffer from the temporal synchronization problem. However, we find that the most reliable tool, Pounder, causes only limited perturbation and thus can be used to automate performance testing. Based on an investigation of Pounder's approach, we further improve its robustness and reduce its perturbation. Finally, we demonstrate in a set of case studies that the conclusions about perceptible performance drawn from manual tests still hold when using automated tests driven by Pounder. Besides the significance of our findings to GUI performance testing, the results are also relevant to capture and replay-based functional GUI test automation approaches. This article is an extended version of our AST 2010 paper Jovic et al. (2010). A. Adamoli (&) Á D. Zaparanuks Á M. Jovic Á M. Hauswirth

Interactive applications with graphical user interfaces are prevalent in today's environment: Everybody with access to any kind of computer constantly uses them. A significant body of prior work has devised approaches for automating the functional testing of such applications. However, no such work exists for automatically testing their performance. Performance testing imposes additional requirements upon GUI test automation tools: the tools have to be able to replay complex interactive sessions, and they have to avoid perturbing the application's performance. We study the feasibility of using five Java GUI capture & replay tools for GUI performance test automation. Besides confirming the severity of the previously known GUI element identification problem, we also identify a related problem, the temporal synchronization problem, which is of increasing importance for GUI applications that use timer-driven activity. We find that most of the tools we study have severe limitations when used for recording and replaying realistic sessions of real-world Java applications, and that all of them suffer from the temporal synchronization problem. However, we find that the most reliable tool, Pounder, causes only limited perturbation, and thus can be used to automate performance testing. Besides the significance of our findings to GUI performance testing, the results are also relevant to capture & replay-based functional GUI test automation approaches.