4 research outputs found

    A model of software component interactions using the call graph technique

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    Interaction information that is related to operations between components is important, especially when the program needs to be modified and maintained. Therefore, the affected components must be identified and matched based on the requirement of the system. This information can be obtained through performing the code review technique, which requires an analyst to search for specific information from the source code, which is a very time consuming process. This research proposed a model for representing software component interactions where this information was automatically extracted from the source code in order to provide an effective display for the software components interaction representation. The objective was achieved through applying a research design methodology, which consists of five phases: awareness of the problem, suggestion, development, evaluation, and conclusion. The development phase was conducted by automatically extracting the components‘ interaction information using appropriate reverse engineering tools and supporting programs that were developed in this research. These tools were used to extract software information, extract the information of component interactions in software programs, and transform this information into the proposed model, which was in the form of a call graph. The produced model was evaluated using a visualization tool and by expert review. The visualization tool was used to display the call graph from a text format into a graphical view. The processed model evaluation was conducted through an expert review technique. The findings from the model evaluation show that the produced model can be used and manipulated to visualize the component interactions. It provides a process that allows a visualization display for analysts to view the interaction of software components in order to comprehend the components integrations that are involved. This information can be manipulated and improved the program comprehension, especially for other software maintenance purposes

    Incremental Call Graph Reanalysis for AspectJ Software

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    Abstract Program call graph representation can be used to support many tasks in compiler optimization, program comprehension, and software maintenance. During software evolution, the call graph needs to remain fairly precise and be updated quickly in response to software changes. In this paper, we present an approach to incremental update, instead of exhaustive analysis of the initially constructed call graph in AspectJ software. Our approach first decomposes the source code edits between the updated and initial software versions into a set of atomic change representations, which capture the semantic differences. Then, we explore the relationship between atomic changes and call graph to incrementally update the initially constructed graph, instead of rebuilding it from the ground up. We implement the reanalysis approach on top of the ajc AspectJ compiler and perform an empirical study on 24 versions of eight AspectJ benchmarks. The experiment result shows that our approach can reduce a large portion of unnecessary reanalysis cost as program changes occur, and significant savings are observed for the incremental reconstruction of AspectJ call graph in comparison with an exhaustive analysis, with no loss in precision

    Automated refactoring for Java concurrency

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    In multicore era, programmers exploit concurrent programming to gain performance and responsiveness benefits. However, concurrent programs are difficult to write: the programmer has to balance two conflicting forces, thread safety and performance. To make concurrent programming easier, modern programming languages provide many kinds of concurrent constructs, such as threads, asynchronous tasks, concurrent collections, etc. However, despite the existence of these concurrent constructs, we know little about how developers use them. On the other hand, although existing API documentation teach developers how to use concurrent constructs, developers can still misuse and underuse them. In this dissertation, we study the use, misuse, and underuse of two types of commonly used Java concurrent constructs: Java concurrent collections and Android async constructs. Our studies show that even though concurrent constructs are widely used in practice, developers still misuse and underuse them, causing semantic and performance bugs. We propose and develop a refactoring toolset to help developers correctly use concurrent constructs. The toolset is composed of three automated refactorings: (i) detecting and fixing the misuses of Java concurrent collections, (ii) retro fitting concurrency for existing sequential Android code via a basic Android async construct, and (iii) converting inappropriately used basic Android async constructs to appropriately enhanced constructs for Android apps. Refactorings (i) and (iii) aim to fix misused constructs while refactoring (ii) aims to eliminate underuses. First, we cataloged nine commonly misused check-then-act idioms of Java concurrent collections, and show the correct usage of each idiom. We implemented the detection strategies in a tool, CTADetector, that finds and fi xes misused check-then-act idioms. We applied CTADetector to 28 widely used open source Java projects (comprising 6.4 million lines of code) that use Java concurrent collections. CTADetector discovered and fixed 60 bugs. These bugs were con firmed by developers and the fixes were accepted. Second, we conducted a formative study on how a basic Android async construct, AsyncTask, is used, misused, and underused in Android apps. Based on the study, we designed, developed, and evaluated Asynchronizer, an automated refactoring tool that enables developers to retrofit concurrency into Android apps. The refactoring uses a points-to static analysis to determine the safety of the refactoring. We applied Asynchronizer to perform 123 refactorings in 19 widely used Android apps; their developers accepted 40 refactorings in 7 projects. Third, we conducted a formative study on a corpus of 611 widely-used Android apps to map the asynchronous landscape of Android apps, understand how developers retrofi t concurrency in Android apps, and learn about barriers encountered by developers. Based on this study, we designed, implemented, and evaluated AsyncDroid, a refactoring tool which enables Android developers to transform existing improperly-used async constructs into correct constructs. We submitted 45 refactoring patches generated by AsyncDroid in 7 widely used Android projects, and developers accepted 15 of them. Finally, we released all tools as open-source plugins for the widely used Eclipse IDE which has millions of Java users. Moreover, we also integrated CTADetector and AsyncDroid with a static analysis platform, ShipShape, that is developed by Google. Google envisions ShipShape to become a widely-used platform. Any app developer that wants to check code quality, for example before submitting an app to the app store, would run ShipShape on her code base. We expect that by contributing new async analyzers to ShipShape, millions of app developers would bene t by being able to execute our analysis and transformations on their code
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