BDTEX: A GQM-based Bayesian approach for the detection of antipatterns

Khomh, Foutse; Vaucher, Stéphane; Guéhéneuc, Yann‐Gaël; Sahraoui, Houari

doi:10.1016/j.jss.2010.11.921

Cited by 141 publications

(79 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Bad smells at design levels are called design smells or anti-patterns by different authors. A number of design smell detection techniques and tools are presented by different authors [21,22,23,24,25]. Anti-patterns and code-smells are often mixed up into one term, the design defects [26].…”

Section: Stat Of the Artmentioning

confidence: 99%

“…It is revealed through the review of literature that the research on Service Oriented Architecture still needs to be explored. Many detection techniques and tools are presented in the literature [21,23,25,26] that focus on specification and detection of OO anti-patterns. These OO based techniques did not give a viable solution for the identification of anti-patterns that are pointed out in webservices.…”

Section: Stat Of the Artmentioning

confidence: 99%

See 1 more Smart Citation

A Lightweight Approach for Specification and Detection of SOAP Anti-Patterns

Sabir¹,

Rasool²,

Yousaf³

2017

ijacsa

View full text Add to dashboard Cite

Abstract-Web-services have become a governing technology for Service Oriented Architectures due to reusability of services and their dependence on other services. The evolution in service based systems demands frequent changes to provide quality of service to customers. It is realised by different researchers that evolution in service based systems may degrade design and quality of service and may generate poor solutions known as antipatterns. The detection of anti-patterns from web services is an important research realm and it is continuously getting the attention of researchers. There are a number of techniques and tools presented for detection of anti-patterns from object oriented software applications but only few approaches are presented for detection of anti-patterns from SOA. The state of the art anti-pattern detection approaches presented for detection of anti-patterns from SOA are not flexible enough and they are limited to detection of only a few anti-patterns. We present a flexible approach supplemented with a tool support to detect 10 anti-patterns from different SOA-based applications. We compare results of our approach with two representative state of the art approaches.

show abstract

Section: Stat Of the Artmentioning

confidence: 99%

Section: Stat Of the Artmentioning

confidence: 99%

A Lightweight Approach for Specification and Detection of SOAP Anti-Patterns

Sabir¹,

Rasool²,

Yousaf³

2017

ijacsa

View full text Add to dashboard Cite

show abstract

“…The literature related to code smells generally falls into three categories: (1) the detection of code smells (e.g., [8,9]); (2) the evolution of code smells in software systems (e.g., [10][11][12]) and their impact on software quality (e.g., [3,5,6,13]); and (3) the relationship between code smells and software development activities (e.g.,, [1,2]). Our work in this paper falls into the third category -we aim to understand the effect of code smells on the effort required to perform certain kinds of activities (e.g., Editing, Navigating, Reading, or Searching).…”

Section: Related Workmentioning

confidence: 99%

Do Code Smells Impact the Effort of Different Maintenance Programming Activities?

Soh

Yamashita

Khomh

et al. 2016

2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER)

Self Cite

View full text Add to dashboard Cite

Abstract-Empirical studies have shown so far that code smells have relatively low impact over maintenance effort at file level. We surmise that previous studies have found low effects of code smells because the effort considered is a "sheer-effort" that does not distinguish between the kinds of developers' activities. In our study, we investigate the effects of code smells at the activity level. Examples of activities are: reading, editing, searching, and navigating, which are performed independently over different files during maintenance. We conjecture that structural attributes represented in the form of different code smells do indeed have an effect on the effort for performing certain kinds of activities. To verify this conjecture, we revisit a previous study about the impact of code smell on maintenance effort, using the same dataset, but considering activity effort. Six professional developers were hired to perform three maintenance tasks on four functionally equivalent Java Systems. Each developer performs two maintenance tasks. During maintenance task, we monitor developers' logs. Then, we define an annotation schema to identify developers' activities and assess whether code smells affect different maintenance activities. Results show that different code smells affect differently activity effort. Yet, the size of the changes performed to solve the task impacts the effort of all activities more than code smells and file size. While code smells impact the editing and navigating effort more than file size, the file size impacts the reading and searching activities more than code smells. One major implication of these results is that if code smells indeed affect the effort of certain kinds of activities, it means that their effects are contingent on the type of maintenance task at hand, where some kinds of activities will become more predominant than others.

show abstract

“…They range from manual approaches, based on inspection techniques [29], to metric-based heuristics [25], using rules and thresholds on various metrics [21] or Bayesian Belief Networks [16].…”

Section: Related Workmentioning

confidence: 99%

A model-driven approach to broaden the detection of software performance antipatterns at runtime

Marco

Trubiani

2014

Electron. Proc. Theor. Comput. Sci.

View full text Add to dashboard Cite

Performance antipatterns document bad design patterns that have negative influence on system performance. In our previous work we formalized such antipatterns as logical predicates that build on four different views: (i) the static view that captures the software elements (e.g. classes, components) and the static relationships among them; (ii) the dynamic view that represents the interaction (e.g. messages) that occurs between the software elements to provide system functionalities; (iii) the deployment view that describes the hardware elements (e.g. processing nodes) and the mapping of software resources onto hardware platforms; (iv) the performance view that collects a set of specific performance indices. In this paper we present a lightweight infrastructure that enables the detection of software performance antipatterns at runtime through the monitoring of specific performance indices. The proposed approach precalculates the logical predicates of antipatterns and identifies the ones whose static, dynamic and deployment sub-predicates occur in the current system configuration and brings at runtime the verification of performance sub-predicates. The proposed infrastructure leverages model-driven techniques to generate probes for monitoring the performance sub-predicates thus to support the detection of antipatterns at runtime.

show abstract

BDTEX: A GQM-based Bayesian approach for the detection of antipatterns

Cited by 141 publications

References 14 publications

A Lightweight Approach for Specification and Detection of SOAP Anti-Patterns

A Lightweight Approach for Specification and Detection of SOAP Anti-Patterns

Do Code Smells Impact the Effort of Different Maintenance Programming Activities?

A model-driven approach to broaden the detection of software performance antipatterns at runtime

Contact Info

Product

Resources

About