Recovery and Analysis of Transaction Scope from Scattered Information in Java Enterprise Applications

Java Enterprise Applications (JEAs) are large systems that integrate multiple technologies and programming languages. Transactions in JEAs simplify the development of code that deals with failure recovery and multi-user coordination by guaranteeing atomicity of sets of operations. The heterogeneous nature of JEAs, however, can obfuscate conceptual errors in the application code, and in particular can hide incorrect declarations of transaction scope. In this paper we present a technique to expose and analyze the application transaction scope in JEAs by merging and analyzing information from multiple sources. We also present several novel visualizations that aid in the analysis of transaction scope by highlighting anomalies in the specification of transactions and violations of architectural constraints. We have validated our approach on two versions of a large commercial case study.

MooseJEE: A Moose Extension to Enable the assessment of JEAs

Java Enterprise Applications (JEAs) are large systems that integrate multiple technologies and programming languages. With the purpose to support the analysis of JEAs we have developed MooseJEE an extension of the \emphMoose environment capable to model the typical elements of JEAs.

Object-Oriented Legacy System Trace-based Logic Testing

When reengineering legacy systems, it is crucial to assess if the legacy behavior has been preserved or how it changed due to the reengineering effort. Ideally if a legacy system is covered by tests, running the tests on the new version can identify potential differences or discrepancies. However, writing tests for an unknown and large system is difficult due to the lack of internal knowledge. It is especially difficult to bring the system to an appropriate state. Our solution is based on the acknowledgment that one of the few trustable piece of information available when approaching a legacy system is the running system itself. Our approach reifies the execution traces and uses logic programming to express tests on them. Thereby it eliminates the need to programatically bring the system in a particular state, and handles the test-writer a high-level abstraction mechanism to query the trace. The resulting system, called TESTLOG, was used on several real-world case studies to validate our claims.

Distribution Map

Understanding large software systems is a challenging task, and to support it many approaches have been developed. Often, the result of these approaches categorize existing entities into new groups or associates them with mutually exclusive properties. In this paper we present the Distribution Map as a generic technique to visualize and analyze this type of result. Our technique is based on the notion of focus, which shows whether a property is well-encapsulated or cross-cutting, and the notion of spread, which shows whether the property is present in several parts of the system. We present a basic visualization and complement it with measurements that quantify focus and spread. To validate our technique we show evidence of applying it on the result sets of different analysis approaches. As a conclusion we propose that the Distribution Map technique should belong to any reverse engineering toolkit.

Package Patterns for Visual Architecture Recovery

Recovering the architecture is the first step towards reengineering a software system. Many reverse engineering tools use top-down exploration as a way of providing a visual and interactive process for architecture recovery. During the exploration process, the user navigates through various views on the system by choosing from several exploration operations. Although some sequences of these operations lead to views which, from the architectural point of view, are mode relevant than others, current tools do not provide a way of predicting which exploration paths are worth taking and which are not. In this article we propose a set of package patterns which are used for augmenting the exploration process with in formation about the worthiness of the various exploration paths. The patterns are defined based on the internal package structure and on the relationships between the package and the other packages in the system. To validate our approach, we verify the relevance of the proposed patterns for real-world systems by analyzing their frequency of occurrence in six open-source software projects.

How Lisp systems look different

Many reverse engineering approaches have been developed to analyze software systems written in different languages like C/C++ or Java. These approaches typically rely on a meta-model, that is either specific for the language at hand or language independent (e.g. UML). However, one language that was hardly addressed is Lisp. While at first sight it can be accommodated by current language independent meta-models, Lisp has some unique features (e.g. macros, CLOS entities) that are crucial for reverse engineering Lisp systems. In this paper we propose a suite of new visualizations that reveal the special traits of the Lisp language and thus help in understanding complex Lisp systems. To validate our approach we apply them on several large Lisp case studies, and summarize our experience in terms of a series of recurring visual patterns that we have detected.

Test Blueprints - Exposing Side Effects in Execution Traces to Support Writing Unit Tests

Writing unit tests for legacy systems is a key maintenance task. When writing tests for object-oriented programs, objects need to be set up and the expected effects of executing the unit under test need to be verified. If developers lack internal knowledge of a system, the task of writing tests is non-trivial. To address this problem, we propose an approach that exposes side effects detected in example runs of the system and uses these side effects to guide the developer when writing tests. We introduce a visualization called Test Blueprint, through which we identify what the required fixture is and what assertions are needed to verify the correct behavior of a unit under test. The dynamic analysis technique that underlies our approach is based on both tracing method executions and on tracking the flow of objects at runtime. To demonstrate the usefulness of our approach we present results from two case studies.

Augmenting Static Source Views in IDEs with Dynamic Metrics

Mainstream IDEs such as Eclipse support developers in managing software projects mainly by offering static views of the source code. Such a static perspective neglects any information about runtime behavior. However, object-oriented programs heavily rely on polymorphism and late-binding, which makes them difficult to understand just based on their static structure. Developers thus resort to debuggers or profilers to study the system's dynamics. However, the information provided by these tools is volatile and hence cannot be exploited to ease the navigation of the source space. In this paper we present an approach to augment the static source perspective with dynamic metrics such as precise runtime type information, or memory and object allocation statistics. Dynamic metrics can leverage the understanding for the behavior and structure of a system. We rely on dynamic data gathering based on aspects to analyze running Java systems. By solving concrete use cases we illustrate how dynamic metrics directly available in the IDE are useful. We also comprehensively report on the efficiency of our approach to gather dynamic metrics.

Senseo: Enriching Eclipse's Static Source Views with Dynamic Metrics

Maintaining object-oriented systems that use inheritance and polymorphism is difficult, since runtime information, such as which methods are actually invoked at a call site, is not visible in the static source code. We have implemented Senseo, an Eclipse plugin enhancing Eclipse's static source views with various dynamic metrics, such as runtime types, the number of objects created, or the amount of memory allocated in particular methods.

Predicting dependencies using domain-based coupling

Software dependencies play a vital role in programme comprehension, change impact analysis and other software maintenance activities. Traditionally, these activities are supported by source code analysis; however, the source code is sometimes inaccessible or difficult to analyse, as in hybrid systems composed of source code in multiple languages using various paradigms (e.g. object-oriented programming and relational databases). Moreover, not all stakeholders have adequate knowledge to perform such analyses. For example, non-technical domain experts and consultants raise most maintenance requests; however, they cannot predict the cost and impact of the requested changes without the support of the developers. We propose a novel approach to predicting software dependencies by exploiting the coupling present in domain-level information. Our approach is independent of the software implementation; hence, it can be used to approximate architectural dependencies without access to the source code or the database. As such, it can be applied to hybrid systems with heterogeneous source code or legacy systems with missing source code. In addition, this approach is based solely on information visible and understandable to domain users; therefore, it can be efficiently used by domain experts without the support of software developers. We evaluate our approach with a case study on a large-scale enterprise system, in which we demonstrate how up to 65 of the source code dependencies and 77% of the database dependencies are predicted solely based on domain information.