A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

Expanding sensor networks to automate knowledge acquisition

The availability of accurate, low-cost sensors to scientists has resulted in widespread deployment in a variety of sporting and health environments. The sensor data output is often in a raw, proprietary or unstructured format. As a result, it is often difficult to query multiple sensors for complex properties or actions. In our research, we deploy a heterogeneous sensor network to detect the various biological and physiological properties in athletes during training activities. The goal for exercise physiologists is to quickly identify key intervals in exercise such as moments of stress or fatigue. This is not currently possible because of low level sensors and a lack of query language support. Thus, our motivation is to expand the sensor network with a contextual layer that enriches raw sensor data, so that it can be exploited by a high level query language. To achieve this, the domain expert specifies events in a tradiational event-condition-action format to deliver the required contextual enrichment

A graph-based aspect interference detection approach for UML-based aspect-oriented models

Aspect Oriented Modeling (AOM) techniques facilitate separate modeling of concerns and allow for a more flexible composition of these than traditional modeling technique. While this improves the understandability of each submodel, in order to reason about the behavior of the composed system and to detect conflicts among submodels, automated tool support is required. Current techniques for conflict detection among aspects generally have at least one of the following weaknesses. They require to manually model the abstract semantics for each system; or they derive the system semantics from code assuming one specific aspect-oriented language. Defining an extra semantics model for verification bears the risk of inconsistencies between the actual and the verified design; verifying only at implementation level hinders fixng errors in earlier phases. We propose a technique for fully automatic detection of conflicts between aspects at the model level; more specifically, our approach works on UML models with an extension for modeling pointcuts and advice. As back-end we use a graph-based model checker, for which we have defined an operational semantics of UML diagrams, pointcuts and advice. In order to simulate the system, we automatically derive a graph model from the diagrams. The result is another graph, which represents all possible program executions, and which can be verified against a declarative specification of invariants.\ud To demonstrate our approach, we discuss a UML-based AOM model of the "Crisis Management System" and a possible design and evolution scenario. The complexity of the system makes con°icts among composed aspects hard to detect: already in the case of two simulated aspects, the state space contains 623 di®erent states and 9 different execution paths. Nevertheless, in case the right pruning methods are used, the state-space only grows linearly with the number of aspects; therefore, the automatic analysis scales

MOT meets AHA!

MOT (My Online Teacher) is an adaptive hypermedia system (AHS) web-authoring environment. MOT is now being further developed according to the LAOS five-layer adaptation model for adaptive hypermedia and adaptive web-material, containing a domain -, goal -, user -, adaptation – and presentation model. The adaptation itself follows the LAG three-layer granularity structure, figuring direct adaptation techniques and rules, an adaptation language and adaptation strategies. In this paper we shortly describe the theoretical basis of MOT, i.e., LAOS and LAG, and then give some information about the current state of MOT. The purpose of this paper is to show how we plan the design and development of MOT and the well-known system AHA! (Adaptive Hypermedia Architecture), developed at the Technical University of Eindhoven since 1996. We aim especially at the integration with AHA! 2.0. Although AHA! 2.0 represents a progress when compared to the previous versions, a lot of adaptive features that are described by the LAOS and the adaptation granulation model and that are being implemented into MOT are not yet (directly) available. So therefore AHA! can benefit from MOT. On the other hand, AHA! offers a running platform for the adaptation engine, which can benefit MOT in return

On Language Processors and Software Maintenance

This work investigates declarative transformation tools in the context of software maintenance. Besides maintenance of the language specification, evolution of a software language requires the adaptation of the software written in that language as well as the adaptation of the software that transforms software written in the evolving language. This co-evolution is studied to derive automatic adaptations of artefacts from adaptations of the language specification. Furthermore, AOP for Prolog is introduced to improve maintainability of language specifications and derived tools.Die Arbeit unterstützt deklarative Transformationswerkzeuge im Kontext der Softwarewartung. Neben der Wartung der Sprachbeschreibung erfordert die Evolution einer Sprache sowohl die Anpassung der Software, die in dieser Sprache geschrieben ist als auch die Anpassung der Software, die diese Software transformiert. Diese Koevolution wird untersucht, um automatische Anpassungen von Artefakten von Anpassungen der Sprachbeschreibungen abzuleiten. Weiterhin wird AOP für Prolog eingeführt, um die Wartbarkeit von Sprachbeschreibungen und den daraus abgeleiteten Werkzeugen zu erhöhen