Metrics for Student Source Code Analysis

Software Quality Assurance is a sub-process that ensures that developed software meets and complies with defined or standardized quality specifications. Focusing on source code, there are characteristics that can be used to evaluate the quality. Introductory courses must encourage freshmen students to improve internal quality of their source code, but only as sophomore they have contact with Software Engineering concepts, including Quality Assurance. In this paper we present a tool to source code quality evaluation aimed at supporting students to improve their source code and, consequently, their programming skills. The proposed tool uses quality reports (available to professional environment integrate with software repositories) to analyze students' source code and provide a feedback about the student coding. The proposed tool run locally, with few computational resources. In addition, we proposed the methodology to use the proposed tool: it consists of challenging students to perform a set of maintenance tasks in a controlled environment. We prepared a source code by introducing common defects, what decreases the quality of source code, and ask to students to perform maintenance tasks in order to both eliminate the introduced defects and introduce new features. After each modification, the students must evaluate their code using the proposed tool to obtain a feedback about quality of source code. To evaluate the approach and the tool, we created a survey and applied to students and the teacher. As a result, we show the benefits of using the proposed tool to both teachers and students perspectives. The results are positive to enhance the teaching-learning Software Quality Assurance to Software Engineering students.

Early prediction of quality of service using interface-level metrics, code-level metrics, and antipatterns

In Engineering and Scientific computing, a significant number of software systems that are being commonly used by the Engineering community are developed and deployed as Open Source Systems (OSS). This collaborative development model has been widely accepted in both academia and industry. As these systems are typically developed by developers who are experts in their fields (e.g., Engineering), some of those programmers may be lacking an essential skillset today's software quality and engineering concepts (e.g., source code maintainability and analyzability, source code vulnerability, parallelization, etc.). An empirical study is presented that examines some of the source code quality aspects and programming practices (e.g., jumps statements, usage of recursion) from software engineering perspective in ten open source Engineering software systems. The studied systems are written in the C/C++ programming languages and comprised of over ten million lines of code, and present numerous tasks of the engineering community, including computer-aided design, computational fluid dynamics, and finite element analysis. Static analysis methods are applied to each system to determine the number of jump statements (Goto and Break statements) and functions that are recursively invoked. Functions that contain direct or indirect recursive calls are determined and counted. The results show that number of the used jump statements and functions that have recursive calls are significant and thus pose more of a roadblock to effectively and automatically maintain, comprehend, analyze, and re-engineer systems. Lastly, this leads to inefficiencies in a software engineer's ability to accomplish these common tasks. The study showed that issues in source code stemming from the lack of coding standards have increased over time and are prevalent.

Analysis of the source code of video games is not an integrated part of the formal analysis. Rather, few scholars have investigated how an analysis of the source code can inform a hermeneutic reading of the game. In this paper I will present a reading of the source code of Passage (Rohrer, 2007), argue for why a traditional focus on authorial intention is unnecessary when investigating the symbolism and metaphors of a game, and illustrate how source code analysis can inform the formal analysis of the executed game. Finally, I shall discuss how the source code relates to the game as a ‘work’, and how it can be used for studies of symbolism and metaphors. Thus, I will conclude that it is indeed a valuable method for game studies, although further studies should expand on the textual relation between executed game and source code.

Static code analysis is a very important stage in the development and implementation of software, and it needs to be used to obtain a better code. The most complicated in static analysis is the analysis of source code, and further analysis. Analysis of the source code can be done multiple times and expand the set of necessary grammar. The main goal was and remains to provide a solution to reduce the time needed for a global reassessment of static analysis at code level after a change.The main problem when using static code analysis is to build an abstract semantic graph, because each software solution is provided with a separate data warehouse. The proposed solution proposes to use as a database repository using graphs. Thus, the storage mechanisms of the created abstract semantic graph have been simplified, which in turn, in addition to increasing the clarity of the information we store, provides convenient ways to further work with the stored information.The developed solution can transform a rather large source repository into a graphic representation and maintain it later. It is found that the approach is suitable for carrying out code compliance checks and for performing static analysis tests on a graphic representation. This approach also uses advanced file-level detailing, accelerating static analysis. Based on my measurements, the frameworks are fast enough to help their users quickly change the repository of codes.This article confirms the thesis about the possibility of storing an abstract semantic graph in a graph database, and after refinement, if it contains sufficient transformations and requests for language processing, can become a complete transport for communication between various static analysis tools that usually perform one of two the functions of verification either for quality or for vulnerability, thereby making a unified creation of an abstract semantic graph.As an improvement it is necessary to consider the possibility of incremental analysis – the analysis of changes in the code, in order to minimize resource costs for a rather resource intensive operation of the structure of the abstract semantic graph.Manuscript received 09.06.2020

Software is being produced so fast that its growth hinders its sustainability. Technical debt, which encompasses internal software quality, evolution and maintenance, reengineering, and economics, is growing such that its management is becoming the dominant driver of software engineering progress. It spans the software engineering life cycle, and its management capitalizes on recent advances in fields such as source code analysis, quality measurement, and project management. Managing technical debt will become an investment activity applying economic theories. It will effectively address the architecture level and will offer specific processes and tools employing data science and analytics to support decision making. It will also be an essential part of the software engineering curriculum. Getting ahead of the software quality and innovation curve will inevitably involve establishing technical-debt management as a core software engineering practice. This article is part of a special issue on the Future of Software Engineering.

Measuring the internal quality of source code is one of the traditional goals of making software development into an engineering discipline. Cyclomatic complexity (CC) is an often used source code quality metric, next to source lines of code (SLOC). However, the use of the CC metric is challenged by the repeated claim that CC is redundant with respect to SLOC because of strong linear correlation.We conducted an extensive literature study of the CC/SLOC correlation results. Next, we tested correlation on large Java (17.6 M methods) and C (6.3 M functions) corpora. Our results show that linear correlation between SLOC and CC is only moderate as a result of increasingly high variance. We further observe that aggregating CC and SLOC as well as performing a power transform improves the correlation.Our conclusion is that the observed linear correlation between CC and SLOC of Java methods or C functions is not strong enough to conclude that CC is redundant with SLOC. This conclusion contradicts earlier claims from literature but concurs with the widely accepted practice of measuring of CC next to SLOC. Copyright © 2015 John Wiley & Sons, Ltd.

This work presents the results of a study of web sites of 230 OA digital repositories in 16 European countries. The analysis addresses the extent to which these repositories fulfil display characteristics of quality sites, over and above the quality of their content. The objective of this study is to verify whether web sites specifically committed to free access to information satisfy the quality criteria of accessibility, web positioning and quality of the source code. The results obtained find that accessibility must be improved upon, source code quality is merely acceptable, and web positioning is good. In short, bad practices were observed that should not occur in sites whose objective is to facilitate the free access to information.

A significant slowdown in processor performance growth is associated with approaching the physical limits of reducing transistor size. This has led to the situation where traditional ways of increasing performance (increasing the clock frequency or the number of cores) no longer fully deliver performance gains. In modern processors, SIMD (Single Instruction, Multiple Da-ta) instruction-set architectures play an important role in increasing computing performance. They allow a processor to perform one operation on multiple data streams simultaneously on a single core. In such a situation, parallel processing at the data level, implemented using SIMD instructions, becomes key. Directing the compilation process with special directives, options, and proper data organization makes it possible to obtain an optimized, vectorized code without explicitly using SIMD instructions in the program source code. However, the effectiveness of such mechanisms largely depends on a number of factors: the processor architectural features, the compiler version, the source code quality, and the optimizer state. The article analyzes some existing methods and tools for vectorizing code using SIMD instructions and proposes an ap-proach to automating vectorization by inserting labels into source code, detecting section boundaries in compiled code, analyzing instructions within sections, and generating a report with a link to the source code. A comparative analysis of existing vectorization tools and the developed prototype is conducted. The proposed approach allows for automating the verifica-tion of code vectorization with line-level accuracy and works even with aggressive optimiza-tion, including function embedding.

In this chapter, we looked at some of the C#, .NET, and Visual Studio features that you can use to improve the quality of your source code and reduce the likelihood of errors or unexpected behavior in your program. No single technique is perfect, but a combination of the approaches we have looked at can provide a great deal of insight into how your code will operate and the implicit assumptions that we all make when writing code. Few programmers like testing, but the more experienced you become with C# and .NET, the more you will appreciate how much of your time and your users’ time can be saved by improving the quality of your code.

Software development practices rely extensively on reusing source code written by other programmers. One of the recurring questions about such practice is how much programmers, acting as users of somebody else’s code, really understand the source code that they inject it in their programs. The question is even more important for novices, who are trying to learn what programming is and how it should be practiced on a larger scale. In this paper we present the results of an ongoing research using a semiotic approach to investigate how novice programmers reuse source code, and how, through messages inscribed in the source code of the programs they write or reuse, they communicate, implicitly or explicitly, what such source code "means" to them and others. We carried out three studies with novice programmers, and results suggest that source code reuse may impact what programmers take their source code to mean.

K-scope is a source code analysis tool with a graphical user interface for the performance tuning of Fortran programs. With K-scope, developers are able to visually understand the structures of their Fortran programs and estimate their performance. However, the original version of K-scope has two problems. First, it lacks the ability to integrate the results of source code analysis with performance profiling data. Second, it requires developers to install XcalableMP because K-scope utilizes the front-end of the XcalableMP compiler. However it is difficult to set up the XcalableMP environment because this requires installing and configuring several libraries and applications. A binary package of XcalableMP is only available for major Linux distributions, and developers thus have a hard time installing XcalableMP on other environments, e.g., Windows. In order to address these two problems, we extend K-scope with two mechanisms. The first visualizes performance profiling data and the second offloads the parsing of Fortran programs to a remote server. More specifically, the visualization mechanism enables users to readily identify performance bottlenecks in their programs by mapping performance profiling data to each line of the source code. With the offloading mechanism, developers no longer need to install XcalableMP. Instead, they can connect K-scope to a remote server on which XcalableMP is installed, and which generates the intermediate code used for analysis. For this purpose, we develop a tool named SSHconnect. To verify the effectiveness of our extended K-scope, we analyze the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) code, an application for global climate simulation that consists of about 300,000 lines of Fortran code. We found that K-scope successfully identified performance bottlenecks in the NICAM code and translated the source code for several applications using its remote parsing mechanism.

In this paper an approach to automatically detect Design Patterns (DPs) in Object Oriented systems is presented. It allows to link system's source code components to the roles they play in each pattern. DPs are modelled by high level structural properties (e.g. inheritance, dependency, invocation, delegation, type nesting and membership relationships) that are checked against the system structure and components. The proposed metamodel also allows to define DP variants, overriding the structural properties of existing DP models, to improve detection quality. The approach was validated on an open benchmark containing several open-source systems of increasing sizes. Moreover, for other two systems, the results have been compared with the ones from a similar approach existing in literature. The results obtained on the analyzed systems, the identified variants and the efficiency and effectiveness of the approach are thoroughly presented and discussed.

We studied source code analysis techniques to predict statically how real programs work and use memory. If we can recognize problems of memory usage in the source code, we are able to prevent them and improve security in the software development phase. The problem detection techniques which are already existed can detect whether the program includes weak code such as Common Vulnerabilities and Exposures, Common Weakness Enumeration. However, these methods are not useful for finding problems in programs that do not include OpenSource. because they use hash value or pattern of weak code contained in OpenSource. Therefore, we propose a static prediction technique for dynamic memory usage with source code analysis without using techniques such as similarity detection. Also, we present how to calculate the values used for static prediction from the source code.

Detection of design patterns is an important part of reverse engineering. Availability of patterns provides for a better understanding of code and also makes analysis more efficient in terms of time and cost. In recent years, we have observed a continual improvement in the field of automatic detection of design patterns in source code. Existing approaches can detect a fairly broad range of design patterns, targeting both structural and behavioral aspects of patterns. However, it is not straightforward to assess and compare these approaches. There is no common ground on which to evaluate the accuracy of the detection approaches, given the existence of variants and specific code constructs used to implement a design pattern. We propose a systematic approach to constructing a comprehensive test suite for detectors of design patterns. This approach is applied to construct a test suite covering the Singleton pattern. The test suite contains many implementation variants of these patterns, along with such code constructs as method forwarding, access modifiers, and long inheritance paths. Furthermore, we use this test suite to compare three detection tools and to identify their strengths and weaknesses.