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Informacje o czasopiśmie
Format
Czasopismo
eISSN
2300-3405
Pierwsze wydanie
24 Oct 2012
Częstotliwość wydawania
4 razy w roku
Języki
Angielski

Wyszukiwanie

Tom 46 (2021): Zeszyt 2 (June 2021)

Informacje o czasopiśmie
Format
Czasopismo
eISSN
2300-3405
Pierwsze wydanie
24 Oct 2012
Częstotliwość wydawania
4 razy w roku
Języki
Angielski

Wyszukiwanie

4 Artykułów
Otwarty dostęp

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

Data publikacji: 17 Jun 2021
Zakres stron: 127 - 145

Abstrakt

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.

Słowa kluczowe

  • Code Readability
  • Program Constructs
  • Code Readability Metrics
  • Statistical Modeling
  • Code Readability Prediction
Otwarty dostęp

Applying Data Envelopment Analysis Principle in Ordinal Multi Criteria Decision Analysis

Data publikacji: 17 Jun 2021
Zakres stron: 147 - 157

Abstrakt

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.

Słowa kluczowe

  • Multiple criteria analysis
  • ordinal scale
  • DEA
  • extreme-point
  • discriminating factor
Otwarty dostęp

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

Data publikacji: 17 Jun 2021
Zakres stron: 159 - 172

Abstrakt

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.

Słowa kluczowe

  • statistical evaluation
  • software metric
  • depth of inheritance tree
  • opensource application
  • Java
Otwarty dostęp

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

Data publikacji: 17 Jun 2021
Zakres stron: 173 - 197

Abstrakt

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.

Słowa kluczowe

  • game theory
  • payoff functional
  • sinusoidal strategy
  • continuous game
  • finite approximation
  • attractive situation
4 Artykułów
Otwarty dostęp

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

Data publikacji: 17 Jun 2021
Zakres stron: 127 - 145

Abstrakt

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.

Słowa kluczowe

  • Code Readability
  • Program Constructs
  • Code Readability Metrics
  • Statistical Modeling
  • Code Readability Prediction
Otwarty dostęp

Applying Data Envelopment Analysis Principle in Ordinal Multi Criteria Decision Analysis

Data publikacji: 17 Jun 2021
Zakres stron: 147 - 157

Abstrakt

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.

Słowa kluczowe

  • Multiple criteria analysis
  • ordinal scale
  • DEA
  • extreme-point
  • discriminating factor
Otwarty dostęp

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

Data publikacji: 17 Jun 2021
Zakres stron: 159 - 172

Abstrakt

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.

Słowa kluczowe

  • statistical evaluation
  • software metric
  • depth of inheritance tree
  • opensource application
  • Java
Otwarty dostęp

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

Data publikacji: 17 Jun 2021
Zakres stron: 173 - 197

Abstrakt

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.

Słowa kluczowe

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

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