A Graph Coloring Approach to Dynamic Slicing of Object-Oriented Programs

Program slicing is a decomposition technique, which produces a subprogram from the parent program relevant to a particular computation. Hence slicing is also regarded as a program transformation technique. A dynamic program slice is an executable part of a program whose behavior is identical, for the same program input, to that of the original program with respect to a variable of interest at some execution position. Dynamic slices are smaller than static slice, which can be used eciently in dierent software engineering activities like program testing, debugging, software maintenance, program comprehension etc. In this dissertation, we present our work concerned with the dynamic slicing of object-oriented programs. We have developed a novel algorithm, which incorporates graph coloring technique to compute dynamic slice of object-oriented programs. But in order to achieve the goal efficiently, we have contradicted the constraints of the traditional graph coloring theory. Moreover, the state restriction of the slicing criterion is taken into consideration, in addition to the dependence analysis. The advantage of our algorithm is that, it is more time ecient than the existing algorithms. We have named this algorithm, as Contradictory Graph Coloring Algorithm (CGCA)

Dynamic Volume Rendering of Functional Medical Data on Dissimilar Hardware Platforms

In the last 30 years, medical imaging has become one of the most used diagnostic tools in the medical profession. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) technologies have become widely adopted because of their ability to capture the human body in a non-invasive manner. A volumetric dataset is a series of orthogonal 2D slices captured at a regular interval, typically along the axis of the body from the head to the feet. Volume rendering is a computer graphics technique that allows volumetric data to be visualized and manipulated as a single 3D object. Iso-surface rendering, image splatting, shear warp, texture slicing, and raycasting are volume rendering methods, each with associated advantages and disadvantages. Raycasting is widely regarded as the highest quality renderer of these methods. Originally, CT and MRI hardware was limited to providing a single 3D scan of the human body. The technology has improved to allow a set of scans capable of capturing anatomical movements like a beating heart. The capturing of anatomical data over time is referred to as functional imaging. Functional MRI (fMRI) is used to capture changes in the human body over time. While fMRI’s can be used to capture any anatomical data over time, one of the more common uses of fMRI is to capture brain activity. The fMRI scanning process is typically broken up into a time consuming high resolution anatomical scan and a series of quick low resolution scans capturing activity. The low resolution activity data is mapped onto the high resolution anatomical data to show changes over time. Academic research has advanced volume rendering and specifically fMRI volume rendering. Unfortunately, academic research is typically a one-off solution to a singular medical case or set of data, causing any advances to be problem specific as opposed to a general capability. Additionally, academic volume renderers are often designed to work on a specific device and operating system under controlled conditions. This prevents volume rendering from being used across the ever expanding number of different computing devices, such as desktops, laptops, immersive virtual reality systems, and mobile computers like phones or tablets. This research will investigate the feasibility of creating a generic software capability to perform real-time 4D volume rendering, via raycasting, on desktop, mobile, and immersive virtual reality platforms. Implementing a GPU-based 4D volume raycasting method for mobile devices will harness the power of the increasing number of mobile computational devices being used by medical professionals. Developing support for immersive virtual reality can enhance medical professionals’ interpretation of 3D physiology with the additional depth information provided by stereoscopic 3D. The results of this research will help expand the use of 4D volume rendering beyond the traditional desktop computer in the medical field. Developing the same 4D volume rendering capabilities across dissimilar platforms has many challenges. Each platform relies on their own coding languages, libraries, and hardware support. There are tradeoffs between using languages and libraries native to each platform and using a generic cross-platform system, such as a game engine. Native libraries will generally be more efficient during application run-time, but they require different coding implementations for each platform. The decision was made to use platform native languages and libraries in this research, whenever practical, in an attempt to achieve the best possible frame rates. 4D volume raycasting provides unique challenges independent of the platform. Specifically, fMRI data loading, volume animation, and multiple volume rendering. Additionally, real-time raycasting has never been successfully performed on a mobile device. Previous research relied on less computationally expensive methods, such as orthogonal texture slicing, to achieve real-time frame rates. These challenges will be addressed as the contributions of this research. The first contribution was exploring the feasibility of generic functional data input across desktop, mobile, and immersive virtual reality. To visualize 4D fMRI data it was necessary to build in the capability to read Neuroimaging Informatics Technology Initiative (NIfTI) files. The NIfTI format was designed to overcome limitations of 3D file formats like DICOM and store functional imagery with a single high-resolution anatomical scan and a set of low-resolution anatomical scans. Allowing input of the NIfTI binary data required creating custom C++ routines, as no object oriented APIs freely available for use existed. The NIfTI input code was built using C++ and the C++ Standard Library to be both light weight and cross-platform. Multi-volume rendering is another challenge of fMRI data visualization and a contribution of this work. fMRI data is typically broken into a single high-resolution anatomical volume and a series of low-resolution volumes that capture anatomical changes. Visualizing two volumes at the same time is known as multi-volume visualization. Therefore, the ability to correctly align and scale the volumes relative to each other was necessary. It was also necessary to develop a compositing method to combine data from both volumes into a single cohesive representation. Three prototype applications were built for the different platforms to test the feasibility of 4D volume raycasting. One each for desktop, mobile, and virtual reality. Although the backend implementations were required to be different between the three platforms, the raycasting functionality and features were identical. Therefore, the same fMRI dataset resulted in the same 3D visualization independent of the platform itself. Each platform uses the same NIfTI data loader and provides support for dataset coloring and windowing (tissue density manipulation). The fMRI data can be viewed changing over time by either animation through the time steps, like a movie, or using an interface slider to “scrub” through the different time steps of the data. The prototype applications data load times and frame rates were tested to determine if they achieved the real-time interaction goal. Real-time interaction was defined by achieving 10 frames per second (fps) or better, based on the work of Miller [1]. The desktop version was evaluated on a 2013 MacBook Pro running OS X 10.12 with a 2.6 GHz Intel Core i7 processor, 16 GB of RAM, and a NVIDIA GeForce GT 750M graphics card. The immersive application was tested in the C6 CAVE™, a 96 graphics node computer cluster comprised of NVIDIA Quadro 6000 graphics cards running Red Hat Enterprise Linux. The mobile application was evaluated on a 2016 9.7” iPad Pro running iOS 9.3.4. The iPad had a 64-bit Apple A9X dual core processor with 2 GB of built in memory. Two different fMRI brain activity datasets with different voxel resolutions were used as test datasets. Datasets were tested using both the 3D structural data, the 4D functional data, and a combination of the two. Frame rates for the desktop implementation were consistently above 10 fps, indicating that real-time 4D volume raycasting is possible on desktop hardware. The mobile and virtual reality platforms were able to perform real-time 3D volume raycasting consistently. This is a marked improvement for 3D mobile volume raycasting that was previously only able to achieve under one frame per second [2]. Both VR and mobile platforms were able to raycast the 4D only data at real-time frame rates, but did not consistently meet 10 fps when rendering both the 3D structural and 4D functional data simultaneously. However, 7 frames per second was the lowest frame rate recorded, indicating that hardware advances will allow consistent real-time raycasting of 4D fMRI data in the near future

Slicing of Aspect-Oriented Software and Its Application to Software Refactoring

This thesis first presents some program slicing techniques for Aspect-Oriented Programs (AOPs) and then presents a technique for refactoring of software using the proposed slicing technique. Main aim of all the proposed slicing algorithms in this thesis is to compute accurate and precise dynamic slices of AOPs. In order to compute the slices of aspect-oriented programs, first we extend the System Dependence Graph (SDG) for Object-Oriented Programs (OOPs) to handle AOPs. We have named the extended SDG Extended Aspect-Oriented System Dependence Graph (EAOSDG). The EAOSDG successfully represents different aspect- oriented features such as class representation, method invocation, inheritance, aspect declaration, point-cuts, advices etc. The EAOSDG of an aspect-oriented program consists of System Dependence Graph (SDG) for the non-aspect code, a group of Aspect-Oriented Dependence Graphs (ADGs) for aspect code and some additional dependence edges that are used to connect the SDG of the non-aspect code (base code) to ADG of the aspect code. Then, we propose an extended two-phase algorithm to compute the static slices of AOPs, using the proposed EAOSDG. Subsequently, we present a context-sensitive slicing algorithm to compute the dynamic slices of AOPs, using the proposed EAOSDG. The context-sensitivity makes the computed slice more precise and accurate. We have developed a slicer to implement our proposed algorithms. We have compared the performance of extended two-phase algorithm and context-sensitive algorithm, in terms of the average slice extraction time. We have considered five open source projects for comparison of slicing algorithms. We have observed that the context-sensitive algorithm computes the slices faster than the extended-two phase algorithm. Next, we extends our intermediate representation (EAOSDG) to be able to represent concurrent aspect-oriented programs. We have named this intermediate representation Multithreaded Aspect-Oriented Dependence Graph (MAODG). Our MAODG correcly represents the concurrency dependencies in concurrent AOPs. Then, we extend our context-sensitive dynamic slicing technique to handle concurrent AOPs having multiple threads. We have named our algorithm Context-Sensitive Concurrent Aspect (CSCA) slicing algorithm. Due to the presence of inter-thread synchronization and communication dependencies, some control and data flows in the threads become interdependent. This interdependency causes difficulty in finding accurate slices of concurrent AOPs. Our algorithm takes the MAODG of the concurrent AOP and a slicing criterion as input and vii computes the dynamic slice for the given concurrent AOP. We have developed a slicer Concurrent AspectJ slicer to implement our proposed CSCA algorithm. We have compared CSCA algorithm with two other existing algorithms using five case studies. The experiment shows that, our proposed CSCA algorithm computes precise slices in less time as compared to the other two existing algorithms. Further, we propose an approach for dynamic slicing of distributed AOPs. We first represent distributed aspect-oriented program using dependence based intermediate representation which we have named Distributed Aspect Dependence Graph (DADG). Based on the DADG, we present a slicing algorithm Parallel Context-sensitive Dynamic Slicing (PCDS) algorithm for distributed AOPs. We introduce parallelism in our algorithm to make slice computation faster. We have developed a tool called D-AspectJ slicer to implement the PCDS algorithm. The proposed slicing algorithm is compared with two other existing algorithms using seven case studies. The experimentation shows that our proposed PCDS algorithm generates smaller slices in less time as compared to the other two existing algorithms. Finally, we present a technique for software refactoring using program slicing. We use slice-based cohesion metrics to identify the target methods of a software that require refactoring. After identifying the target methods, we use program slicing to divide the target method into two parts. Then, we use the concept of aspects to alter the code structure in a manner that does not change the external behavior of the original module. We have implemented our proposed refactoring technique and evaluated its effectiveness through eleven case studies. We have also evaluated the effect of our proposed refactoring technique based on an open source code coverage tool EclEmm

Dagstuhl Reports : Volume 1, Issue 2, February 2011

Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn

Dependence Cluster Visualization

Large clusters of mutual dependence have long been regarded as a problem impeding comprehension, testing, maintenance, and reverse engineering. An effective visualization can aid an engineer in addressing the presence of large clusters. Such a visualization is presented. It allows a program’s dependence clusters to be considered from an abstract high level down thru a concrete source-level. At the highest level of abstraction, the visualization uses a heat-map (a color scheme) to efficiently overview the clusters found in an entire system. Other levels include three source code views that allow a user to “zoom” in on the clusters starting from the high-level system view, down through a file view, and then onto the actual source code where each cluster can be studied in detail. Also presented are two case studies, the first is the open-source calculator bc and the second is the industrial program copia, which performs signal processing. The studies consider qualitative evaluations of the visualization. From the results, it is seen that the visualization reveals high-level structure of programs and interactions between its components. The results also show that the visualization highlights potential candidates (functions/files) for re-factoring in bc and finds dependence pollution in copia

Semi-automatic fault localization

One of the most expensive and time-consuming components of the debugging process is locating the errors or faults. To locate faults, developers must identify statements involved in failures and select suspicious statements that might contain faults. In practice, this localization is done by developers in a tedious and manual way, using only a single execution, targeting only one fault, and having a limited perspective into a large search space. The thesis of this research is that fault localization can be partially automated with the use of commonly available dynamic information gathered from test-case executions in a way that is effective, efficient, tolerant of test cases that pass but also execute the fault, and scalable to large programs that potentially contain multiple faults. The overall goal of this research is to develop effective and efficient fault localization techniques that scale to programs of large size and with multiple faults. There are three principle steps performed to reach this goal: (1) Develop practical techniques for locating suspicious regions in a program; (2) Develop techniques to partition test suites into smaller, specialized test suites to target specific faults; and (3) Evaluate the usefulness and cost of these techniques. In this dissertation, the difficulties and limitations of previous work in the area of fault-localization are explored. A technique, called Tarantula, is presented that addresses these difficulties. Empirical evaluation of the Tarantula technique shows that it is efficient and effective for many faults. The evaluation also demonstrates that the Tarantula technique can loose effectiveness as the number of faults increases. To address the loss of effectiveness for programs with multiple faults, supporting techniques have been developed and are presented. The empirical evaluation of these supporting techniques demonstrates that they can enable effective fault localization in the presence of multiple faults. A new mode of debugging, called parallel debugging, is developed and empirical evidence demonstrates that it can provide a savings in terms of both total expense and time to delivery. A prototype visualization is provided to display the fault-localization results as well as to provide a method to interact and explore those results. Finally, a study on the effects of the composition of test suites on fault-localization is presented.Ph.D.Committee Chair: Harrold, Mary Jean; Committee Member: Orso, Alessandro; Committee Member: Pande, Santosh; Committee Member: Reiss, Steven; Committee Member: Rugaber, Spence

Analyzing feature implementation by visual exploration of architecturally-embedded call-graphs

ABSTRACT Maintenance, reengineering, and refactoring of large and complex software systems are commonly based on modifications and enhancements related to features. Before developers can modify feature functionality they have to locate the relevant code components and understand the components' interaction. In this paper, we present a prototype tool for analyzing feature implementation of large C/C++ software systems by visual exploration of dynamically extracted call relations between code components. The component interaction can be analyzed on various abstraction levels ranging from function interaction up to interaction of the system with shared libraries of the operating system. The user visually explores the component interaction within a multiview visualization system consisting of various textual and a graphical 3D landscape view. During exploration the 3D landscape view supports the user firstly in deciding early whether a call relation is essential for understanding the feature and, secondly, in finding starting points for fine-grained feature analysis using a top-down approach