Software Quality Indicators Research Articles

УЗЛУКСИЗ ҲАРАКАТДАГИ АХБОРОТТИЗИМЛАРИ УЧУН АНАЛИТИК МОДЕЛ

Requirements for information security and reliable operation of systems do not become obsolete. On the contrary, the demand for them has increased and has become a problem that does not lose its relevance. It's no secret that the fault tolerance of large software systems is of great importance, especially when they are online. The presented article is devoted to these issues and a model is proposed for evaluating software quality indicators under failure conditions.

Lagrange-NG: The next generation of Lagrange.

Computing ancestral ranges via the Dispersion Extinction and Cladogensis (DEC) model of biogeography is characterized by an exponential number of states relative to the number of regions considered. This is because the DEC model requires computing a large matrix exponential, which typically accounts for up to 80% of overall runtime. Therefore, the kinds of biogeographical analyses that can be conducted under the DEC model are limited by the number of regions under consideration. In this work, we present a completely redesigned efficient version of the popular tool Lagrange which is up to 49 times faster with multithreading enabled, and is also 26 times faster when using only one thread. We call this new version Lagrange-NG (Lagrange-Next Generation). The increased computational efficiency allows Lagrange-NG to analyze datasets with a large number of regions in a reasonable amount of time, up to 12 regions in approximately 18 min. We achieve these speedups using a relatively new method of computing the matrix exponential based on Krylov subspaces. In order to validate the correctness of Lagrange-NG, we also introduce a novel metric on range distributions for trees so that researchers can assess the difference between any two range inferences. Finally, Lagrange-NG exhibits substantially higher adherence to coding quality standards. It improves a respective software quality indicator as implemented in the SoftWipe tool from average (5.5; Lagrange) to high (7.8; Lagrange-NG). Lagrange-NG is freely available under GPL2. [Biogeography; Phylogenetics; DEC Model.].

СИСТЕМА УПРАВЛІННЯ ЯКІСТЮ ПРОГРАМНОГО ЗАБЕЗПЕЧЕННЯ

The Software quality management system has been developed. The system allows you to determine the state of software quality at each hierarchical level of the management system, taking into account the cost of ensuring the required quality. The system also allows the IT company manager to set the potential costs for the transition of software quality indicators from one state to another. It was found out that software quality is a multifaceted concept that can be adequately expressed by some hierarchical structure of characteristics and attributes, which is called the model of software product quality. To assess the quality of the software, a set of criteria and aggregate indicators were used, which maximally characterise it in terms of functionality and usage options. It is established that the software quality model is the main attribute of the complex system of its assessment. The quality model determines which characteristics of the software product must be taken into account when transiting the control system from one state to another. The level of software quality that meets the stated and indirect needs of various stakeholders and is relevant to them is directly reflected in the quality model of the software product in the form of its properties. The software quality model classifies product properties into characteristics and sub-characteristics. A method for selecting stressful variants of software quality state according to input criteria or aggregate indicators of its current quality has been developed. The method allows to determine the current state of software quality at each hierarchical level according to the corresponding aggregate indicator, taking into account its development cost. A method for selecting the optimal version of the software quality management system from the set of permissible has been developed. The method takes into account the structure of criteria and aggregated indicators of current software quality at each hierarchical level of the management system. It is established that the task of choosing the optimal version of the software quality management system belongs to the tasks of multicriteria optimization. The task takes into account the following criteria: portability of the product and its ease of maintenance, product safety and compatibility, ease of use of the product and reliability of its work, as well as the functional suitability of the product and its efficiency of use. An example of implementation of the software quality management system in both quantitative and cost ratio is given. The example allows us to understand the essence of the method of choosing the optimal variant for the management system, as well as the features of the method of selection of stressful variants of the system state according to two criteria or aggregate indicators.

On the Concept of Transparency: A Systematic Literature Review

Over a decade since transparency was introduced as a first-class concept in computing, transparency is still an emerging concept that is quite poorly understood. Also, despite existing research contributions, transparency is yet to be incorporated into the software engineering practice, and the promise it holds remains unfulfilled. Although there is evidence of increasing stakeholders’ demand for software and process transparency, the realization of such demand is yet to be fully witnessed within the software engineering practice. There is a need to uncover transparency and how it has so far been conceptualized, operationalized, and challenges faced. We applied a systematic literature review method in search of articles published between January 2006 and March 2022. This study reports a systematic review of the explicit conceptualization and application of transparency in 18 articles out of a total of 162 selected for review. Our study found that transparency remains an under-researched non-functional quality requirement concept, especially as it impacts information and software systems development. Of the 18 articles reviewed, only three studies representing 16.67% conceptualized transparency in software development and focused on the transparency of software artifacts. The remaining 83.33% of studies conceptualized transparency in information systems, focusing on general information and fully functional information systems. Transparency is yet to be fully explored from a theoretical gathering point of view and as a non-functional indicator of software quality hence its slow adoption and incorporation into mainstream software practice. Apart from providing a catalog of transparency factors that stakeholders can use to evaluate transparency achievement, the paper proposed a roadmap to enhance transparency implementation and also provides future research directions.

Формирование оптимального комплекта программного обеспечения в образовательных организациях

The problem of determining the nomenclature of the optimal set of application software (software) necessary for the implementation of educational programs in higher educational institutions (HEI) by quantifying its quality is considered. Aim. Development of a mechanism for a comprehensive assessment of the quality of software within the selected class, to simplify the task of making an informed decision when choosing a standard set of universities. Materials and methods. The proposed mechanism is based on the use of optimization methods and expert assessments. At the first stage of the mechanism, the basic requirements are clarified, taking into account the specifics of the work of the educational organization. A set of programs (alternatives) for the selected software class is formed, with the subsequent determination of the key functions characteristic of it on the basis of expert information. Further, according to the software quality indicators proposed in the work, they are evaluated for each alternative. Software quality indicators are a hierarchical three-level system (criterion, metric, evaluation element), in which the indicators of the higher levels are determined through the indicators of the lower levels. The integral assessment of the quality of an alternative is defined as the sum of the estimates of its quality criteria. At the final stage, the problem of integer linear programming is solved to determine the optimal range of alternatives within the corresponding software class, based on their conditions: maximizing the quality of an alternative contai¬ning the required set of functions, and minimizing their number. Results. The mechanism of determining the optimal alternatives for the formation of a standard set of software, in order to implement the necessary educational programs of the university, is considered. The main indicators of software quality and the mathematical apparatus for their assessment are formalized. Conclusion. The proposed mechanism allows for a quantitative assessment of the quality of software within its class, with the subsequent selection of the most rational software tools for the university. Such an asses¬sment will simplify the task of making an informed decision when forming a standard set of software necessary for implementing the requirements of federal educational standards, and in general will increase the effectiveness of the system for coordinating informatization in this direction.

RESEARCH OF THE SOFTWARE SECURITY MODEL AND REQUIREMENTS

The subject of research in the article is a software security model. The aim of the work is to research the quality characteristics of the software and requirements for the software security in order to improve their safety. The article solves the following tasks: researching the shortcomings of the existing security model in order to identify its main shortcomings; study of the quality characteristics of software that affect its security in order to identify the possibility of improving the quality of software. The following results were obtained: on the basis of the analysis of the existing model of software security, the main features of the attributes of this model were identified, their advantages and disadvantages were given. On the basis of the conducted analytical study, the necessity of improving the existing model of ensuring the security of software has been proved. Existing requirements for software and characteristics that affect its quality are considered. The characteristics of software security are highlighted, the indicators of which should be improved. Conclusions: a software security model has been studied. The need to develop this model is shown by introducing the possibility of adapting the existing requirements for the security of software tools throughout the entire life cycle of software development; the study of the quality characteristics of software showed that to ensure its security, it is necessary to improve the following characteristics: integrity, authentication, confidentiality, access control. However, it was shown that an increase in these characteristics can lead to a deterioration in other indicators of software quality: portability, maintainability, performance.

Characterizing Buffer Overflow Vulnerabilities in Large C/C++ Projects

Security vulnerabilities are present in most software systems, especially in projects with a large codebase, with several versions over the years, developed by many developers. Issues with memory management, in particular buffer overflow, are among the most frequently exploited vulnerabilities in software systems developed in C/C++. Nevertheless, most buffer overflow vulnerabilities are not detectable by vulnerability detection tools and static analysis tools (SATs). To improve vulnerability detection, we need to better understand the characteristics of such vulnerabilities and their root causes. In this study, we analyze 159 vulnerable code units from three representative projects (i.e., Linux Kernel, Mozilla, and Xen). First, the vulnerable code is characterized using the Orthogonal Defect Classification (ODC), showing that most buffer overflow vulnerabilities are related to missing or incorrect checking (e.g., missing if construct around statement or incorrect logical expression used as branch condition). Then, we run two widely used C/C++ Static Analysis Tools (SATs) (i.e., CppCheck and Flawfinder) on the vulnerable and neutral (after the vulnerability fix) versions of each code unit, showing the low effectiveness of this type of tool in detecting buffer overflow vulnerabilities. Finally, we characterize the vulnerable and neutral versions of each code unit using software metrics, demonstrating that, although such metrics are frequently used as indicators of software quality, there is no clear correlation between them and the existence of buffer overflow in the code. As a result, we highlight a set of observations that should be considered to improve the detection of buffer overflow vulnerabilities.

Reliability prediction analysis of aspect-oriented application using soft computing techniques

Abstract Accurate estimation is the foremost goal of any forecasting model. Software reliability is one of the leading research issues of the software organization. Recently, various applications of soft computing technology have attempted. Software reliability is one of the quantitative indicators of software quality. The Software Reliability Growth Model (SRGM) is used to evaluate the reliability obtained in different stages of testing. The reliability of the software depends on several factors (extensibility, sustainability, design stability, and configurability). Moreover, these factors are related to each other and directly or indirectly affect the software development process. Among various soft computing technologies, models based on artificial neural networks are well known, which extremely needs more research work and endeavors to discover the most reasonable model for software quality. The purpose of this paper is to examine the reliability of the software using soft computing techniques, which is the most efficiently used tool to evaluate its predictive power. It provides a new comparative analysis to find the most suitable and accurate artificial neural network based on the software reliability model. To answer this question, we need to evaluate the model. We use MMRE, SD, RSD, and PRED (N) to analyze the performance of the competitive model. The applicability of a particular soft computing technique is an open question because it depends mostly on the nature and characteristics of the problem. Every software project has its development behavior and complexity model. Therefore, more research is needed to predict and analysis of the results.

Оценка меры различия алгоритмов в многовариантной системе составления производственных планов

In the process of designing a production plan, one of the important steps is scheduling the execution of technological operations. The schedule can be created either manually or by using software. If the schedule is compiled by software, then several schedule generation algorithms are used to eliminate possible errors. A set of such algorithms is called a "batch". It is advisable that only different algorithms should be included in the batch. This is necessary to eliminate errors of the same type. Therefore, the search for clones of algorithms in the batch is an urgent production task. To solve it a diversity metric of algorithms was developed in the course of this work. Such a metric numerically (as a percentage) determines how much the algorithms differ. This metric is based on the properties of the algorithm execution. Algorithm traces are constructed in the N-dimensional space using the obtained points. The coordinates of the trace points are the values with which the algorithm works at each step of its execution or each of the control points of the algorithm execution. An experiment was performed to confirm the correctness of this metric. Within this experiment, the trace properties of three sorting algorithms were calculated. Based on the properties obtained, indicators were determined for comparing algorithms in the metric space. The experiment confirmed the effectiveness of using the diversity metric to find clones in the algorithms batch. The scope of this metric is not limited to clone searches. It can be used as an independent indicator of software quality.

PRACTICAL QUALITY ANALYSIS OF OPEN SOURCE SOFTWARE

The success of any project is determined by its ability to meet the needs of the consumer, and therefore ensuring a high level of quality is a necessary task of any production, including software engineering. Insufficient quality of the created software requires many IT-organizations, up to 70% of the budget of the information system to reserve for the maintenance stage, with up to 60% of all software modifications performed to eliminate errors, and only the remaining 40% - to correct software within the business process, improvement certain indicators of software quality, or to prevent potential problems. Software quality is a complex concept. Standards highlight the quality of development processes, internal and external quality of the software product, the quality of the software product at the stage of use. For each of the components of quality can be called a set of metrics that determine the quality of the software product. The resulting structure is called the software quality model. Software metrics are a measure that allows you to get the numerical value of a property of software or its specifications, as well as the method of its calculation. Metrics allow you to get numeric values for each property of the software or its specifications. Of particular interest are software complexity metrics. Complexity is an important factor on which other parameters of software quality depend, such as accuracy, correctness, reliability, convenience of support. The existence of methods and algorithms for automatic calculation of software complexity metrics using software allows you to get a comprehensive formal report on the quality of software in a short time. This allows for objective monitoring of the quality of software throughout the project life cycle, make adjustments to the project plan, as well as make timely decisions about the need for refactoring.

Vulnerable Code Detection Using Software Metrics and Machine Learning

Software metrics are widely-used indicators of software quality and several studies have shown that such metrics can be used to estimate the presence of vulnerabilities in the code. In this paper, we present a comprehensive experiment to study how effective software metrics can be to distinguish the vulnerable code units from the non-vulnerable ones. To this end, we use several machine learning algorithms (Random Forest, Extreme Boosting, Decision Tree, SVM Linear, and SVM Radial) to extract vulnerability-related knowledge from software metrics collected from the source code of several representative software projects developed in C/C++ (Mozilla Firefox, Linux Kernel, Apache HTTPd, Xen, and Glibc). We consider different combinations of software metrics and diverse application scenarios with different security concerns (e.g., highly critical or non-critical systems). This experiment contributes to understanding whether software metrics can effectively be used to distinguish vulnerable code units in different application scenarios, and how can machine learning algorithms help in this regard. The main observation is that using machine learning algorithms on top of software metrics helps to indicate vulnerable code units with a relatively high level of confidence for security-critical software systems (where the focus is on detecting the maximum number of vulnerabilities, even if false positives are reported), but they are not helpful for low-critical or non-critical systems due to the high number of false positives (that bring an additional development cost frequently not affordable).

Reflection of expert-based evaluation of software quality

The method of reflections data, which is obtained as a result of processing expert-based evaluation of software quality by different criteria of evaluation using petal charts. Reflection of expert-based evaluation of software quality is found to be the process of reflections data in graphical form for maximum ease of understanding and rapid perception, and also providing a clear overview and shape of any object, process or phenomenon. The software quality evaluation criteria and their weighting factors for each expert are offered, which provide a reliable presentation of the current state of the software development process, a proper understanding of the problems that may arise at any stage of the program project implementation, and the exact characteristics of their components. This mechanism of data reflection enables business analysts to submit qualitatively and quantitatively multiple values of complex software quality indicators that can be obtained from the results of any survey of different experts at a particular stage of the program project implementation. The proposed methodology is suitable for presenting a variety of expert survey results, with a subdivision into unlimited number of the roles of the software quality evaluation participants concerning the importance of each of them. An algorithm for calculating the area of sectorial petals in a polar coordinate system has been developed, using which it is possible to calculate and evaluate the relative software quality according to the proper criteria. The final complex software quality indicators for each expert are determined, and a comprehensive indicator of its quality is summarized as well. An algorithm for calculating the area of a petal diagram in a polar coordinate system has been developed, which allows determining the part of software quality according to all the criteria, which is currently evaluated by one of the experts, as well as the part of software quality, which has yet to be achieved for its 100% completeness. The relevant conclusions are drawn and recommendations are made concerning the use of the developed data reflection methodology.

Evaluation of quality characteristics of software for the reference verification installations for gasmeters

The choosing a particular software product among the same type of analogues is one of the important problem of modern market relations. Even choosing the best one (with the highest numerical value of the generalized quality index), the question arises whether there is a sufficient level of quality of this software for one or for a number of tasks and functions they are solving. That is why, it is necessary to develop a scale of quality levels (qualimertic scale) for those software. The solution of this problem is the development of a qualitative scale for determining the quality indicators of such software and proving them based on experimental data of evaluation elements of quality metrics of software for measuring instruments. The authors developed three qualimetric scale models for software in this article: a uniform interval (or quantitative) scale, a scale based on the generalized Harrington utility desirability and a one based on the numbers of the Fibonacci series (“Golden section”). The number of evaluations determined by these functions was analyzed to prove the adequacy of devel­oped qualimetric scale models. According to the results of the analysis, using the Fibonacci function (“Golden section”) is more preferable then the Harrington function and the linear function for the developing the qualimetric scales of software products. Using the developed scale allows to quantify the software quality indicators determination.

VISUALIZATION OF THE RESULTS OF EXPERT EVALUATION OF SOFTWARE QUALITY USING POLAR DIAGRAMS

Розроблено методику візуалізації інформації, яку можна отримати внаслідок оброблення експертних оцінок якості програмного забезпечення (ПЗ) за різними критеріями його оцінювання з використанням полярних діаграм. Встановлено, що під візуалізацією результатів експертного оцінювання якості ПЗ розуміють подання інформації у графічному вигляді для максимальної зручності її розуміння та швидкого сприйняття, а також надання осяжної та зрозумілої форми будь-якому об'єкту, суб'єкту, процесу тощо. Запропоновано критерії оцінювання якості ПЗ та їхні вагові коефіцієнти для кожного з експертів, які забезпечують достовірне подання наявного стану процесу розроблення ПЗ, правильне розуміння суті проблем, що можуть виникнути на будь-якому етапі реалізації програмного проекту, і точні характеристики їх складових. Розроблено алгоритм розрахунку площ секторних багатокутників у полярній системі координат, за допомогою якого можна обчислити і оцінити відносну якість ПЗ за відповідними критеріями. Визначено комплексні підсумкові показники якості ПЗ для кожного з експертів і комплексний узагальнений показник його якості для усіх експертів. Розроблено алгоритм розрахунку площі неправильного багатокутника у полярній системі координат, який дає змогу визначити ту частину якості ПЗ за всіма критеріями, яку маємо на даний момент за оцінками одного з експертів, а також ту частку якості ПЗ, яку ще потрібно досягти для 100 % її повноти. Зроблено відповідні висновки та надано рекомендації щодо використання розробленої методики візуалізації інформації.

Static Analysis and Code Complexity Metrics as Early Indicators of Software Defects

Software is an important part of automotive product development, and it is commonly known that software quality assurance consumes considerable effort in safety-critical embedded software development. Increasing the effectiveness and efficiency of this effort thus becomes more and more important. Identifying problematic code areas which are most likely to fail and therefore require most of the quality assurance attention is required. This article presents an exploratory study investigating whether the faults detected by static analysis tools combined with code complexity metrics can be used as software quality indicators and to build pre-release fault prediction models. The combination of code complexity metrics with static analysis fault density was used to predict the pre-release fault density with an accuracy of 78.3%. This combination was also used to separate high and low quality components with a classification accuracy of 79%.

Method of Evaluating the Weights of Software Quality Measures and Indicators

Nowadays the actual task is evaluating the mutual influences of the software quality characteristics and subcharacteristics by the measures and software quality metrics – by the indicators. The aim of this study is the development of the method of evaluating the weights of software quality measures and indicators. The first time developed method of evaluating the weights of the software quality measures and indicators differs from known methods that: considers the correlation of software quality subchcaracteristics by the measures and metrics by the indicators, calculates the weights of exactly measures and indicators, provides the conclusion about the presence of which measures and indicators in the software requirements specification (SRS) is necessary for the appropriate level of veracity of the software quality assessment. The weights of the software quality measures and indicators provide the sorting of all missing in the SRS measures and indicators in descending of their significance (in descending of their weights), i.e. the priority of their further addition in the SRS.

Metric-based software reliability prediction approach and its application

This paper proposes a software reliability prediction approach based on software metrics. Metrics measurement results are connected to quantitative reliability predictions through defect information and consideration of the operational environments. An application of the proposed approach to a safety critical software deployed in a nuclear power plant is discussed. Results show that the proposed prediction approach could be applied using a variety of software metrics at different stages of the software development life cycle and could be used as an indicator of software quality. Therefore the approach could also guide the development process and help make design decisions. Experiences and lessons learned from the application are also discussed.

Using Personality Traits to Understand the Influence of Personality on Computer Programming

Computer programming is complex and all personality factors might influence it. Personality factors are comprehensive but broad and, therefore, lower level traits may help understanding the influence of personality on computer programming. The objective of this paper is to extend the empirical knowledge in software psychology by using narrow personality traits as well as broad personality traits to explain the influence of personality. The authors surveyed 68 programming students developing software projects to investigate the influence of personality on performance in computer programming. They measured five broad personality factors, 17 personality facets, prior experience, attitude and self-assessed survey performance. They also used the grade students achieved in the software projects as an indicator of software quality. It was found that prior programming experience, attitude towards programming, academic performance, Openness to Experience, Conscientiousness, Extraversion and Agreeableness have a positive effect on performance in computer programming. However, one facet of Openness to Experience and facets of Neuroticism revealed negative effect. The authors found an indication that different aspects of personality factors have different influences on computer programming. Personality facets show larger effect than personality and help explaining the influence of personality. More studies are needed to strengthen the findings and clarify the situation.

An automated software reliability prediction system for safety critical software

Software reliability is one of the most important software quality indicators. It is concerned with the probability that the software can execute without any unintended behavior in a given environment. In previous research we developed the Reliability Prediction System (RePS) methodology to predict the reliability of safety critical software such as those used in the nuclear industry. A RePS methodology relates the software engineering measures to software reliability using various models, and it was found that RePS's using Extended Finite State Machine (EFSM) models and fault data collected through various software engineering measures possess the most satisfying prediction capability. In this research the EFSM-based RePS methodology is improved and implemented into a tool called Automated Reliability Prediction System (ARPS). The features of the ARPS tool are introduced with a simple case study. An experiment using human subjects was also conducted to evaluate the usability of the tool, and the results demonstrate that the ARPS tool can indeed help the analyst apply the EFSM-based RePS methodology with less number of errors and lower error criticality.

Analyzing and predicting software integration bugs using network analysis on requirements dependency network

Complexity, cohesion and coupling have been recognized as prominent indicators of software quality. One characterization of software complexity is the existence of dependency relationships. Moreover, the degree of dependency reflects the cohesion and coupling between software elements. Dependencies in the design and implementation phase have been proven to be important predictors of software bugs. We empirically investigated how requirements dependencies correlate with and predict software integration bugs, which can provide early estimates regarding software quality and thus facilitate decision making early in the software lifecycle. We conducted network analysis on the requirements dependency networks of three commercial software projects. Significant correlation is observed between most of our network measures and the number of bugs. Furthermore, many network measures demonstrate significantly greater values for higher severity (or a higher fixing workload). Afterward, we built bug prediction models using these network measures and found that bugs can be predicted with high accuracy and sensitivity, even in cross-project and cross-company contexts. We further identified the dependency type that contributes most to bug correlation, as well as the network measures that contribute more to bug prediction. These observations show that the requirements dependency network can be used as an early indicator and predictor of software integration bugs.