12,305 research outputs found
Evaluating Random Mutant Selection at Class-Level in Projects with Non-Adequate Test Suites
Mutation testing is a standard technique to evaluate the quality of a test
suite. Due to its computationally intensive nature, many approaches have been
proposed to make this technique feasible in real case scenarios. Among these
approaches, uniform random mutant selection has been demonstrated to be simple
and promising. However, works on this area analyze mutant samples at project
level mainly on projects with adequate test suites. In this paper, we fill this
lack of empirical validation by analyzing random mutant selection at class
level on projects with non-adequate test suites. First, we show that uniform
random mutant selection underachieves the expected results. Then, we propose a
new approach named weighted random mutant selection which generates more
representative mutant samples. Finally, we show that representative mutant
samples are larger for projects with high test adequacy.Comment: EASE 2016, Article 11 , 10 page
XML in Motion from Genome to Drug
Information technology (IT) has emerged as a central to the solution of contemporary genomics and drug discovery problems. Researchers involved in genomics, proteomics, transcriptional profiling, high throughput structure determination, and in other sub-disciplines of bioinformatics have direct impact on this IT revolution. As the full genome sequences of many species, data from structural genomics, micro-arrays, and proteomics became available, integration of these data to a common platform require sophisticated bioinformatics tools. Organizing these data into knowledgeable databases and developing appropriate software tools for analyzing the same are going to be major challenges. XML (eXtensible Markup Language) forms the backbone of biological data representation and exchange over the internet, enabling researchers to aggregate data from various heterogeneous data resources. The present article covers a comprehensive idea of the integration of XML on particular type of biological databases mainly dealing with sequence-structure-function relationship and its application towards drug discovery. This e-medical science approach should be applied to other scientific domains and the latest trend in semantic web applications is also highlighted
On a Catalogue of Metrics for Evaluating Commercial Cloud Services
Given the continually increasing amount of commercial Cloud services in the
market, evaluation of different services plays a significant role in
cost-benefit analysis or decision making for choosing Cloud Computing. In
particular, employing suitable metrics is essential in evaluation
implementations. However, to the best of our knowledge, there is not any
systematic discussion about metrics for evaluating Cloud services. By using the
method of Systematic Literature Review (SLR), we have collected the de facto
metrics adopted in the existing Cloud services evaluation work. The collected
metrics were arranged following different Cloud service features to be
evaluated, which essentially constructed an evaluation metrics catalogue, as
shown in this paper. This metrics catalogue can be used to facilitate the
future practice and research in the area of Cloud services evaluation.
Moreover, considering metrics selection is a prerequisite of benchmark
selection in evaluation implementations, this work also supplements the
existing research in benchmarking the commercial Cloud services.Comment: 10 pages, Proceedings of the 13th ACM/IEEE International Conference
on Grid Computing (Grid 2012), pp. 164-173, Beijing, China, September 20-23,
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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
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