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

WapMetrics: a tool for computing UML design metrics for Web applications

Many companies are still asking how to assess and predict the maintenance cost of their software. Measures of software maintenance cost can be taken either late or early in the development process. Early measures of software maintenance cost are beneficial because they can help in allocating project resources efficiently, predicting the effort of maintenance tasks and controlling the maintenance process. This paper describes a tool for computing early metrics from UML class diagrams based on the Web Application Extension (WAE) for UML. A case study is used to show the usefulness and effectiveness of the tool

Design metrics for web application maintainability measurement

Many web applications have evolved from simple HTML pages to complex applications that have a high maintenance cost. This high maintenance cost is due to the heterogeneity of web applications, to fast Internet evolution and the fast- moving market which imposes short development cycles and frequent modifications. In order to control the maintenance cost, quantitative metrics for predicting web applications maintainability must be used. This paper provides an exploratory study for new design metrics used for measuring the maintainability of web applications from class diagrams. The metrics are based on Web Application Extension (WAE)for UML and will measure the following design attributes: size, complexity, coupling and reusability. In this study the metrics are applied to two web applications from the telecommunications domain

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

Unlike for Human Monocytes after LPS Activation, Release of TNF-α by THP-1 Cells Is Produced by a TACE Catalytically Different from Constitutive TACE

Tumor necrosis factor-alpha (TNF-α) is a pro-inflammatory cytokine today identified as a key mediator of several chronic inflammatory diseases. TNF-α, initially synthesized as a membrane-anchored precursor (pro-TNF-α), is processed by proteolytic cleavage to generate the secreted mature form. TNF-α converting enzyme (TACE) is currently the first and single protease described as responsible for the inducible release of soluble TNF-α.Here, we demonstrated the presence on THP-1 cells as on human monocytes of a constitutive proteolytical activity able to cleave pro-TNF-α. Revelation of the cell surface TACE protein expression confirmed that the observed catalytic activity is due to TACE. However, further studies using effective and innovative TNF-α inhibitors, as well as a highly selective TACE inhibitor, support the presence of a catalytically different sheddase activity on LPS activated THP-1 cells. It appears that this catalytically different TACE protease activity might have a significant contribution to TNF-α release in LPS activated THP-1 cells, by contrast to human monocytes where the TACE activity remains catalytically unchanged even after LPS activation.On the surface of LPS activated THP-1 cells we identified a releasing TNF-α activity, catalytically different from the sheddase activity observed on human monocytes from healthy donors. This catalytically-modified TACE activity is different from the constitutive shedding activity and appears only upon stimulation by LPS

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism

Empirical validation of UML class diagram metrics through an industrial case study

Many web applications have evolved from simple HTML pages to complex service-oriented applications that have high maintenance cost. This high maintenance cost is due to the heterogeneity of web applications, to the fast Internet evolution and to the fast-moving market which imposes short development cycles and frequent modifications. In order to control the maintenance cost, quantitative metrics for predicting web applications' maintainability must be used. This study introduces class diagram design metrics based on Conallen Web Application Extension for UML. The study will use data from an industrial web application to show the correlation between the class diagram metrics and maintenance effort measured by the number of lines of code changed

An industrial study using UML design metrics for Web applications

Many web applications have evolved from simple HTML pages to complex applications that are difficult to maintain. In order to control the maintenance of web applications quantitative metrics and models for predicting web applications maintainability must be used. This paper introduces new design metrics for measuring the maintainability of web applications from class diagrams. The metrics are based on Web Application Extension (WAE) for UML and measure the design attributes of size, complexity, and coupling. The paper describes an experiment carried out using a CVS repository from a US telecoms web application. A relationship is established between the metrics and maintenance effort measured by the number of lines of code changed

Exploring the relationship between UML design metrics for Web applications and maintainability

Measures of software maintainability can be taken either late or early in the development process. Late measurements of software maintainability can be used for assessing the software system, and planning for future enhancements. On the other hand, early measures of software maintainability can help in allocating project resources efficiently, predicting the effort of maintenance tasks and controlling the maintenance process