A comparative analysis of maintainability approaches for web applications

Web applications incorporate important business assets and offer a convenient way for businesses to promote their services through the internet. Many of these web applications have evolved from simple HTML pages to complex applications that have high maintenance cost. The high maintenance cost of web applications is due to the inherent characteristics of web applications, to the fast internet evolution and to the pressing market which imposes short development cycles and frequent modifications. In order to control the maintenance cost, quantitative metrics and models for predicting web applications' maintainability must be used. Since, web applications are different from traditional software systems, models and metrics for traditional systems can not be applied to web applications. The reason for that is that web applications have special features such as hypertext structure, dynamic code generation and heterogenousity that can not be captured by traditional and object-oriented metrics. In this paper, we will provide a comparative analysis of the different approaches for predicting web applications

Modelado y Simulación como herramienta para la mejora de la Usabilidad

Las técnicas de modelado y simulación se han aplicado desde la década de los 90 para dar respuesta a distintas cuestiones relacionadas con el proceso de desarrollo de software. Una de las principales ventajas del modelado y simulación es la posibilidad de predecir las consecuencias que podrían tener determinadas decisiones en el desarrollo de un proyecto software sin necesidad de asumir riesgos elevados. Este artículo pretende justificar que las técnicas de modelado y simulación, aplicadas ya con éxito al proceso software, pueden ser también herramientas valiosas para el proceso de desarrollo de interfaces de usuario, teniendo como objetivo final la mejora de la usabilidad. Para ilustrar la aplicación de estas técnicas se presenta el proceso de construcción de un modelo de simulación dinámico del proceso de Diseño Centrado en el Usuario.Ministerio de Ciencia y Tecnología TIC 2003-369Ministerio de Ciencia y Tecnología TIC 2001-1143-C03-0

Eco-friendly synthesis, physicochemical studies, biological assay and molecular docking of steroidal oxime-ethers

The aim of this study was to report the synthesis of biologically active compounds; 7-(2′-aminoethoxyimino)-cholest-5-ene (4), a steroidal oxime-ether and its derivatives (5, 6) via a facile microwave assisted solvent free reaction methodology. This new synthetic, eco-friendly, sustainable protocol resulted in a remarkable improvement in the synthetic efficiency (85–93 % yield) and high purity using basic alumina. The synthesized compounds were screened for their antibacterial against six bacterial strains by disc diffusion method and antioxidant potential by DPPH assay. The binding capabilities of a compound 6 exhibiting good antibacterial potential were assessed on the basis of molecular docking studies and four types of three-dimensional molecular field descriptors. Moreover the structure–antimicrobial activity relationships were studied using some physicochemical and quantum-chemical parameters with GAMESS interface as well as WebMO Job Manager by using the basic level of theory. Hence, this synthetic approach is believed to provide a better scope for the synthesis of steroidal oxime-ether analogues and will be a more practical alternative to the presently existing procedures. Moreover, detailed in silico docking studies suggested the plausible mechanism of steroidal oxime-ethers as effective antimicrobial agents

An Experimental Comparison of Three Machine Learning Techniques for Web Cost Estimation

Many comparative studies on the performance of machine learning (ML) techniques for web cost estimation (WCE) have been reported in the literature. However, not much attention have been given to understanding the conceptual differences and similarities that exist in the application of these ML techniques for WCE, which could provide credible guide for upcoming practitioners and researchers in predicting the cost of new web projects. This paper presents a comparative analysis of three prominent machine learning techniques – Case-Based Reasoning (CBR), Support Vector Regression (SVR) and Artificial Neural Network (ANN) – in terms of performance, applicability, and their conceptual differences and similarities for WCE by using data obtained from a public dataset (www.tukutuku.com). Results from experiments show that SVR and ANN provides more accurate predictions of effort, although SVR require fewer parameters to generate good predictions than ANN. CBR was not as accurate, but its good explanation attribute gives it a higher descriptive value. The study also outlined specific characteristics of the 3 ML techniques that could foster or inhibit their adoption for WCE

Small Molecule Inhibitor Design for Anaplastic Lymphoma Kinase Inhibition

The Anaplastic Lymphoma Kinase (ALK) gene has been linked to tumorigenesis in a number of human cancers, including anaplastic large cell lymphoma (ALCL) and neuroblastoma. While ALK mutations in ALCL and many other cancers occur as a result of gene fusions with wild type kinase domains, those in neuroblastoma stem from single nucleotide polymorphisms (SNPs) in the kinase domain. These lead to autophosphorylation and constitutive signaling by ALK for cell growth and division, ultimately causing cancer. Crizotinib, an ATP-competitive ALK inhibitor, has proven to be an effective inhibitor of both ALKWT and ALKMutant kinase domains, and is in the middle of clinical trials for neuroblastoma treatment. This review used the PyMOL and AutoDock Vina computational biology programs to predict the binding affinities of Crizotinib, Ceritinib (LDK378), and PF-922 to three different ALK kinase mutations in order to determine the most effective inhibitor. The EGFR inhibitors gefitinib and erlotinib were also analyzed in complex with ALK as negative controls to verify the specificity of the ALK inhibitors. The crystalline complexes were then qualitatively analyzed to uncover the mechanics behind the docking results. Based on the results generated by Vina, PF-922, representative of the second generation of ALK inhibitors, is predicted to be the most effective out of the tested compounds. These results may be used to predict the inhibitor that will require the lowest dosage to achieve the greatest inhibitory effect, hopefully leading to fewer side effects from treatment

A novel model for improving the maintainability of web-based systems

Web applications incorporate important business assets and offer a convenient way for businesses to promote their services through the internet. Many of these web applica- tions have evolved from simple HTML pages to complex applications that have a high maintenance cost. This is due to the inherent characteristics of web applications, to the fast internet evolution and to the pressing market which imposes short development cycles and frequent modifications. In order to control the maintenance cost, quantita- tive metrics and models for predicting web applications’ maintainability must be used. Maintainability metrics and models can be useful for predicting maintenance cost, risky components and can help in assessing and choosing between different software artifacts. Since, web applications are different from traditional software systems, models and met- rics for traditional systems can not be applied with confidence to web applications. Web applications have special features such as hypertext structure, dynamic code generation and heterogenousity that can not be captured by traditional and object-oriented metrics. This research explores empirically the relationships between new UML design met- rics based on Conallen’s extension for web applications and maintainability. UML web design metrics are used to gauge whether the maintainability of a system can be im- proved by comparing and correlating the results with different measures of maintain- ability. We studied the relationship between our UML metrics and the following main- tainability measures: Understandability Time (the time spent on understanding the soft- ware artifact in order to complete the questionnaire), Modifiability Time(the time spent on identifying places for modification and making those modifications on the software artifact), LOC (absolute net value of the total number of lines added and deleted for com- ponents in a class diagram), and nRev (total number of revisions for components in a class diagram). Our results gave an indication that there is a possibility for a relationship to exist between our metrics and modifiability time. However, the results did not show statistical significance on the effect of the metrics on understandability time. Our results showed that there is a relationship between our metrics and LOC(Lines of Code). We found that the following metrics NAssoc, NClientScriptsComp, NServerScriptsComp, and CoupEntropy explained the effort measured by LOC(Lines of Code). We found that NC, and CoupEntropy metrics explained the effort measured by nRev(Number of Revi- sions). Our results give a first indication of the usefulness of the UML design metrics, they show that there is a reasonable chance that useful prediction models can be built from early UML design metrics