Dynamic Analysis of Software Systems using Execution Pattern Mining

Safyallah, H.; Sartipi, Kamran

doi:10.1109/icpc.2006.19

Cited by 57 publications

(31 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Then, processing this fine grain data to extract useful high-level information will be difficult. This situation is a well know issue, which can be addressed with summarizing and visualization techniques (Cornelissen et al 2007;Safyallah and Sartipi 2006).…”

Section: Dynamic Analysismentioning

confidence: 99%

A practice-driven systematic review of dependency analysis solutions

2011

View full text Add to dashboard Cite

When following architecture-driven strategies to develop large softwareintensive systems, the analysis of the dependencies is not an easy task. In this paper, we report a systematic literature review on dependency analysis solutions. Dependency analysis concerns making dependencies due to interconnections between programs or system components explicit. The review is practice-driven because its research questions, execution, and reporting were influenced by the practice of a group of software architects at Philips Healthcare MRI. The review results in an overview and assessment of the state-of-the-art and applicability of dependency analysis. The overview provides insights about definitions related to dependency analysis, the sort of development activities that need dependency analysis, and the classification and description of a number of dependency analysis solutions. The contribution of this paper is for both practitioners and researchers. They can take it as a reference to learn about dependency analysis, match their own practice to the presented results, and to build similar overviews of other techniques and methods for other domains or types of systems.

show abstract

Section: Dynamic Analysismentioning

confidence: 99%

A practice-driven systematic review of dependency analysis solutions

2011

View full text Add to dashboard Cite

show abstract

“…They were motivated by the identification of: crosscutting concerns (aspects) [14], business processes [15], patterns of interests among service users [16], [17], and features either in OO systems [18] or SBSs [19]. Further related work focused on the identification of service composition patterns [20], i.e.…”

Section: B Knowledge Extractionmentioning

confidence: 99%

Improving SOA antipatterns detection in Service Based Systems by mining execution traces

Nayrolles

Moha

Valtchev

2013

2013 20th Working Conference on Reverse Engineering (WCRE)

View full text Add to dashboard Cite

Abstract-Service Based Systems (SBSs), like other software systems, evolve due to changes in both user requirements and execution contexts. Continuous evolution could easily deteriorate the design and reduce the Quality of Service (QoS) of SBSs and may result in poor design solutions, commonly known as SOA antipatterns. SOA antipatterns lead to a reduced maintainability and reusability of SBSs. It is therefore important to first detect and then remove them. However, techniques for SOA antipattern detection are still in their infancy, and there are hardly any tools for their automatic detection. In this paper, we propose a new and innovative approach for SOA antipattern detection called SOMAD (Service Oriented Mining for Antipattern Detection) which is an evolution of the previously published SODA (Service Oriented Detection For Antpatterns) tool. SOMAD improves SOA antipattern detection by mining execution traces: It detects strong associations between sequences of service/method calls and further filters them using a suite of dedicated metrics. We first present the underlying association mining model and introduce the SBS-oriented rule metrics. We then describe a validating application of SOMAD to two independently developed SBSs. A comparison of our new tool with SODA reveals superiority of the former: Its precision is better by a margin ranging from 2.6% to 16.67% while the recall remains optimal at 100% and the speed is significantly reduces (2.5+ times on the same test subjects).

show abstract

“…[1,13,40,44]); (b) static analysis, based on static source code information, such as slicing, control or data flow graphs (e.g. [7,27,39]); and (c) textual analysis, explore natural language text found in programs like comments or documentation.…”

Section: Related Workmentioning

confidence: 99%

Conclave: Ontology-Driven Measurement of Semantic Relatedness between Source Code Elements and Problem Domain Concepts

Carvalho

Almeida

Henriques

et al. 2014

Computational Science and Its Applications – ICCSA 2014

View full text Add to dashboard Cite

Abstract. Software maintainers are often challenged with source code changes to improve software systems, or eliminate defects, in unfamiliar programs. To undertake these tasks a sufficient understanding of the system (or at least a small part of it) is required. One of the most time consuming tasks of this process is locating which parts of the code are responsible for some key functionality or feature. Feature (or concept) location techniques address this problem. This paper introduces Conclave, an environment for software analysis, and in particular the Conclave-Mapper tool that provides a feature location facility. This tool explores natural language terms used in programs (e.g. function and variable names), and using textual analysis and a collection of Natural Language Processing techniques, computes synonymous sets of terms. These sets are used to score relatedness between program elements, and search queries or problem domain concepts, producing sorted ranks of program elements that address the search criteria, or concepts. An empirical study is also discussed to evaluate the underlying feature location technique.

show abstract

Dynamic Analysis of Software Systems using Execution Pattern Mining

Cited by 57 publications

References 8 publications

A practice-driven systematic review of dependency analysis solutions

A practice-driven systematic review of dependency analysis solutions

Improving SOA antipatterns detection in Service Based Systems by mining execution traces

Conclave: Ontology-Driven Measurement of Semantic Relatedness between Source Code Elements and Problem Domain Concepts

Contact Info

Product

Resources

About