Rivista e Edizione

Volume 47 (2022): Edizione 3 (September 2022)

Volume 47 (2022): Edizione 2 (June 2022)

Volume 47 (2022): Edizione 1 (February 2022)

Volume 46 (2021): Edizione 4 (December 2021)

Volume 46 (2021): Edizione 3 (September 2021)

Volume 46 (2021): Edizione 2 (June 2021)

Volume 46 (2021): Edizione 1 (March 2021)

Volume 45 (2020): Edizione 4 (December 2020)

Volume 45 (2020): Edizione 3 (September 2020)

Volume 45 (2020): Edizione 2 (June 2020)

Volume 45 (2020): Edizione 1 (March 2020)

Volume 44 (2019): Edizione 4 (December 2019)

Volume 44 (2019): Edizione 3 (September 2019)

Volume 44 (2019): Edizione 2 (June 2019)

Volume 44 (2019): Edizione 1 (March 2019)

Volume 43 (2018): Edizione 4 (December 2018)

Volume 43 (2018): Edizione 3 (September 2018)

Volume 43 (2018): Edizione 2 (June 2018)

Volume 43 (2018): Edizione 1 (March 2018)

Volume 42 (2017): Edizione 4 (December 2017)

Volume 42 (2017): Edizione 3 (September 2017)

Volume 42 (2017): Edizione 2 (June 2017)

Volume 42 (2017): Edizione 1 (February 2017)

Volume 41 (2016): Edizione 4 (November 2016)

Volume 41 (2016): Edizione 3 (September 2016)

Volume 41 (2016): Edizione 2 (June 2016)

Volume 41 (2016): Edizione 1 (March 2016)

Volume 40 (2015): Edizione 4 (December 2015)

Volume 40 (2015): Edizione 3 (September 2015)

Volume 40 (2015): Edizione 2 (June 2015)

Volume 40 (2015): Edizione 1 (March 2015)

Volume 39 (2014): Edizione 4 (December 2014)

Volume 39 (2014): Edizione 3 (September 2014)

Volume 39 (2014): Edizione 2 (June 2014)

Volume 39 (2014): Edizione 1 (February 2014)

Volume 38 (2013): Edizione 4 (December 2013)

Volume 38 (2013): Edizione 3 (September 2013)

Volume 38 (2013): Edizione 2 (June 2013)

Volume 38 (2013): Edizione 1 (March 2013)

Volume 37 (2012): Edizione 4 (December 2012)

Volume 37 (2012): Edizione 3 (September 2012)

Volume 37 (2012): Edizione 2 (June 2012)

Volume 37 (2012): Edizione 1 (March 2012)

Dettagli della rivista
Formato
Rivista
eISSN
2300-3405
Pubblicato per la prima volta
24 Oct 2012
Periodo di pubblicazione
4 volte all'anno
Lingue
Inglese

Cerca

Volume 46 (2021): Edizione 2 (June 2021)

Dettagli della rivista
Formato
Rivista
eISSN
2300-3405
Pubblicato per la prima volta
24 Oct 2012
Periodo di pubblicazione
4 volte all'anno
Lingue
Inglese

Cerca

4 Articoli
Accesso libero

Effect or Program Constructs on Code Readability and Predicting Code Readability Using Statistical Modeling

Pubblicato online: 17 Jun 2021
Pagine: 127 - 145

Astratto

Abstract

In software, code is the only part that remains up to date, which shows how important code is. Code readability is the capability of the code that makes it readable and understandable for professionals. The readability of code has been a great concern for programmers and other technical people in development team because it can have a great influence on software maintenance. A lot of research has been done to measure the influence of program constructs on the code readability but none has placed the highly influential constructs together to predict the readability of a code snippet. In this article, we propose a novel framework using statistical modeling that extracts important features from the code that can help in estimating its readability. Besides that using multiple correlation analysis, our proposed approach can measure dependencies among di erent program constructs. In addition, a multiple regression equation is proposed to predict the code readability. We have automated the proposals in a tool that can do the aforementioned estimations on the input code. Using those tools we have conducted various experiments. The results show that the calculated estimations match with the original values that show the effectiveness of our proposed work. Finally, the results of the experiments are analyzed through statistical analysis in SPSS tool to show their significance.

Parole chiave

  • Code Readability
  • Program Constructs
  • Code Readability Metrics
  • Statistical Modeling
  • Code Readability Prediction
Accesso libero

Applying Data Envelopment Analysis Principle in Ordinal Multi Criteria Decision Analysis

Pubblicato online: 17 Jun 2021
Pagine: 147 - 157

Astratto

Abstract

We consider a multicriteria decision analysis (MCDA) problem where importance of criteria, and evaluations of alternatives with respect to the criteria, are expressed on a qualitative ordinal scale. Using the extreme-point principle of Data Envelopment Analysis (DEA), we develop a two-parameter method for obtaining overall ratings of the alternatives when preferences and evaluations are made on an ordinal scale. We assume no parametric setup other than the two parameters that reflect minimum intensities of discriminating among rank positions: one parameter for the alternatives’ ranking and one for the criteria ranking. These parameters are bounded by the ordinal input data, and they imply a universal tie among the alternatives when both parameters are selected to be zero. We describe the model, discuss its theoretical underpinning, and demonstrate its application.

Parole chiave

  • Multiple criteria analysis
  • ordinal scale
  • DEA
  • extreme-point
  • discriminating factor
Accesso libero

A Statistical Evaluation of The Depth of Inheritance Tree Metric for Open-Source Applications Developed in Java

Pubblicato online: 17 Jun 2021
Pagine: 159 - 172

Astratto

Abstract

The Depth of Inheritance Tree (DIT) metric, along with other ones, is used for estimating some quality indicators of software systems, including open-source applications (apps). In cases involving multiple inheritances, at a class level, the DIT metric is the maximum length from the node to the root of the tree. At an application (app) level, this metric defines the corresponding average length per class. It is known, at a class level, a DIT value between 2 and 5 is good. At an app level, similar recommended values for the DIT metric are not known. To find the recommended values for the DIT mean of an app we have proposed to use the confidence and prediction intervals. A DIT mean value of an app from the confidence interval is good since this interval indicates how reliable the estimate is for the DIT mean values of all apps used for estimating the interval. A DIT mean value higher than an upper bound of prediction interval may indicate that some classes have a large number of the inheritance levels from the object hierarchy top. What constitutes greater app design complexity as more classes are involved. We have estimated the confidence and prediction intervals of the DIT mean using normalizing transformations for the data sample from 101 open-source apps developed in Java hosted on GitHub for the 0.05 significance level.

Parole chiave

  • statistical evaluation
  • software metric
  • depth of inheritance tree
  • opensource application
  • Java
Accesso libero

Acceptable-and-attractive Approximate Solution of a Continuous Non-Cooperative Game on a Product of Sinusoidal Strategy Functional Spaces

Pubblicato online: 17 Jun 2021
Pagine: 173 - 197

Astratto

Abstract

A problem of solving a continuous noncooperative game is considered, where the player’s pure strategies are sinusoidal functions of time. In order to reduce issues of practical computability, certainty, and realizability, a method of solving the game approximately is presented. The method is based on mapping the product of the functional spaces into a hyperparallelepiped of the players’ phase lags. The hyperparallelepiped is then substituted with a hypercubic grid due to a uniform sampling. Thus, the initial game is mapped into a finite one, in which the players’ payoff matrices are hypercubic. The approximation is an iterative procedure. The number of intervals along the player’s phase lag is gradually increased, and the respective finite games are solved until an acceptable solution of the finite game becomes sufficiently close to the same-type solutions at the preceding iterations. The sufficient closeness implies that the player’s strategies at the succeeding iterations should be not farther from each other than at the preceding iterations. In a more feasible form, it implies that the respective distance polylines are required to be decreasing on average once they are smoothed with respective polynomials of degree 2, where the parabolas must be having positive coefficients at the squared variable.

Parole chiave

  • game theory
  • payoff functional
  • sinusoidal strategy
  • continuous game
  • finite approximation
  • attractive situation
4 Articoli
Accesso libero

Effect or Program Constructs on Code Readability and Predicting Code Readability Using Statistical Modeling

Pubblicato online: 17 Jun 2021
Pagine: 127 - 145

Astratto

Abstract

In software, code is the only part that remains up to date, which shows how important code is. Code readability is the capability of the code that makes it readable and understandable for professionals. The readability of code has been a great concern for programmers and other technical people in development team because it can have a great influence on software maintenance. A lot of research has been done to measure the influence of program constructs on the code readability but none has placed the highly influential constructs together to predict the readability of a code snippet. In this article, we propose a novel framework using statistical modeling that extracts important features from the code that can help in estimating its readability. Besides that using multiple correlation analysis, our proposed approach can measure dependencies among di erent program constructs. In addition, a multiple regression equation is proposed to predict the code readability. We have automated the proposals in a tool that can do the aforementioned estimations on the input code. Using those tools we have conducted various experiments. The results show that the calculated estimations match with the original values that show the effectiveness of our proposed work. Finally, the results of the experiments are analyzed through statistical analysis in SPSS tool to show their significance.

Parole chiave

  • Code Readability
  • Program Constructs
  • Code Readability Metrics
  • Statistical Modeling
  • Code Readability Prediction
Accesso libero

Applying Data Envelopment Analysis Principle in Ordinal Multi Criteria Decision Analysis

Pubblicato online: 17 Jun 2021
Pagine: 147 - 157

Astratto

Abstract

We consider a multicriteria decision analysis (MCDA) problem where importance of criteria, and evaluations of alternatives with respect to the criteria, are expressed on a qualitative ordinal scale. Using the extreme-point principle of Data Envelopment Analysis (DEA), we develop a two-parameter method for obtaining overall ratings of the alternatives when preferences and evaluations are made on an ordinal scale. We assume no parametric setup other than the two parameters that reflect minimum intensities of discriminating among rank positions: one parameter for the alternatives’ ranking and one for the criteria ranking. These parameters are bounded by the ordinal input data, and they imply a universal tie among the alternatives when both parameters are selected to be zero. We describe the model, discuss its theoretical underpinning, and demonstrate its application.

Parole chiave

  • Multiple criteria analysis
  • ordinal scale
  • DEA
  • extreme-point
  • discriminating factor
Accesso libero

A Statistical Evaluation of The Depth of Inheritance Tree Metric for Open-Source Applications Developed in Java

Pubblicato online: 17 Jun 2021
Pagine: 159 - 172

Astratto

Abstract

The Depth of Inheritance Tree (DIT) metric, along with other ones, is used for estimating some quality indicators of software systems, including open-source applications (apps). In cases involving multiple inheritances, at a class level, the DIT metric is the maximum length from the node to the root of the tree. At an application (app) level, this metric defines the corresponding average length per class. It is known, at a class level, a DIT value between 2 and 5 is good. At an app level, similar recommended values for the DIT metric are not known. To find the recommended values for the DIT mean of an app we have proposed to use the confidence and prediction intervals. A DIT mean value of an app from the confidence interval is good since this interval indicates how reliable the estimate is for the DIT mean values of all apps used for estimating the interval. A DIT mean value higher than an upper bound of prediction interval may indicate that some classes have a large number of the inheritance levels from the object hierarchy top. What constitutes greater app design complexity as more classes are involved. We have estimated the confidence and prediction intervals of the DIT mean using normalizing transformations for the data sample from 101 open-source apps developed in Java hosted on GitHub for the 0.05 significance level.

Parole chiave

  • statistical evaluation
  • software metric
  • depth of inheritance tree
  • opensource application
  • Java
Accesso libero

Acceptable-and-attractive Approximate Solution of a Continuous Non-Cooperative Game on a Product of Sinusoidal Strategy Functional Spaces

Pubblicato online: 17 Jun 2021
Pagine: 173 - 197

Astratto

Abstract

A problem of solving a continuous noncooperative game is considered, where the player’s pure strategies are sinusoidal functions of time. In order to reduce issues of practical computability, certainty, and realizability, a method of solving the game approximately is presented. The method is based on mapping the product of the functional spaces into a hyperparallelepiped of the players’ phase lags. The hyperparallelepiped is then substituted with a hypercubic grid due to a uniform sampling. Thus, the initial game is mapped into a finite one, in which the players’ payoff matrices are hypercubic. The approximation is an iterative procedure. The number of intervals along the player’s phase lag is gradually increased, and the respective finite games are solved until an acceptable solution of the finite game becomes sufficiently close to the same-type solutions at the preceding iterations. The sufficient closeness implies that the player’s strategies at the succeeding iterations should be not farther from each other than at the preceding iterations. In a more feasible form, it implies that the respective distance polylines are required to be decreasing on average once they are smoothed with respective polynomials of degree 2, where the parabolas must be having positive coefficients at the squared variable.

Parole chiave

  • game theory
  • payoff functional
  • sinusoidal strategy
  • continuous game
  • finite approximation
  • attractive situation

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