Research in Programming Languages and Software Engineering

1990 ◽  
Author(s):  
Victor R. Basili ◽  
John D. Gannon ◽  
Marvin V. Zelkowitz
Keyword(s):  
Software Engineering ◽  
Programming Languages

scholarly journals BDI Agent Architectures: A Survey

2020 ◽  
Author(s):  
Lavindra de Silva ◽  
Felipe Meneguzzi ◽  
Brian Logan
Keyword(s):  
Systematic Review ◽  
Software Engineering ◽  
Programming Languages ◽  
Agent Architectures ◽  
Agent Oriented Software Engineering ◽  
Agent Programming ◽  
Agent Programming Languages ◽  
Trade Offs ◽  
Bdi Agent ◽  
Bdi Architecture

The BDI model forms the basis of much of the research on symbolic models of agency and agent-oriented software engineering. While many variants of the basic BDI model have been proposed in the literature, there has been no systematic review of research on BDI agent architectures in over 10 years. In this paper, we survey the main approaches to each component of the BDI architecture, how these have been realised in agent programming languages, and discuss the trade-offs inherent in each approach.

scholarly journals Detecting Uninitialized Variables in C++ with the Clang Static Analyzer

2020 ◽  
Author(s):  
Kristóf Umann ◽  
Zoltán Porkoláb
Keyword(s):  
Software Engineering ◽  
Open Source ◽  
Programming Languages ◽  
Static Analysis ◽  
Common Source ◽  
Initial Value ◽  
Analysis Techniques ◽  
Specific Variable ◽  
Prototype Tool ◽  
Run Time

Uninitialized variables have been a source of errors since the beginning of software engineering. Some programming languages (e.g. Java and Python) will automatically zero-initialize such variables, but others, like C and C++, leave their state undefined. While laying aside initialization in C and C++ might be a performance advantage if an initial value can't be supplied, working with such variables is an undefined behavior, and is a common source of instabilities and crashes. To avoid such errors, whenever meaningful initialization is possible, it should be used. Tools for detecting these errors run time have existed for decades, but those require the problematic code to be executed. Since in many cases the number of possible execution paths are combinatoric, static analysis techniques emerged as an alternative. In this paper, we overview the technique for detecting uninitialized C++ variables using the Clang Static Analyzer, and describe various heuristics to guess whether a specific variable was left in an undefined state intentionally. We implemented a prototype tool based on our idea and successfully tested it on large open source projects.

scholarly journals RESEARCH TRENDS IN SOFTWARE ENGINEERING FIELD: A LITERATURE REVIEW

2020 ◽  
Vol 7 (6) ◽  
pp. 58-65
Author(s):  
Hiba Al Sghaier
Keyword(s):  
Software Engineering ◽  
Programming Languages ◽  
New Technologies ◽  
Research Trends ◽  
Mobile Technologies ◽  
Smart Devices ◽  
Software Systems ◽  
Current Time ◽  
Develop Software ◽  
Software Engineers

Software engineering is one of computer science branches, it comprises of building and developing software systems and applications. Software engineering is a discipline that has a constant growth in research in aim to identify new technologies and adopt it in different areas; there is a considerable investment on software engineering trends at the current time due to the availability of mobile technologies. With millions of billions of smart devices that are connected to the internet, all industries around the world are rapidly becoming a technology driven industries. Software engineers are aware of programming languages that are employed to develop software systems, by applying engineering principles to development process; they can design customized software systems for individual or organizational customers. The new trends in software engineering are numerous, Cloud Computing, machine learning, deep learning, big Data, mobile Computing. Nevertheless, there are many more other research trends in software engineering's field that have been intensively explored and implemented in many different industries. In this paper, authors try to summarize the most fields that are integrated with software engineering recently.

scholarly journals COMPARISON OF SOFTWARE COMPLEXITY OF SEARCH ALGORITHM USING CODE BASED COMPLEXITY METRICS

2021 ◽  
Vol 6 (5) ◽  
Author(s):  
Bello Muriana ◽  
Ogba Paul Onuh
Keyword(s):  
Software Engineering ◽  
Programming Languages ◽  
Search Algorithm ◽  
Source Code ◽  
Search Algorithms ◽  
Binary Search ◽  
Software Systems ◽  
Software Complexity ◽  
Complexity Metrics ◽  
Binary Search Algorithm

Measures of software complexity are essential part of software engineering. Complexity metrics can be used to forecast key information regarding the testability, reliability, and manageability of software systems from study of the source code. This paper presents the results of three distinct software complexity metrics that were applied to two searching algorithms (Linear and Binary search algorithm). The goal is to compare the complexity of linear and binary search algorithms implemented in (Python, Java, and C++ languages) and measure the sample algorithms using line of code, McCabe and Halstead metrics. The findings indicate that the program difficulty of Halstead metrics has minimal value for both linear and binary search when implemented in python. Analysis of Variance (ANOVA) was adopted to determine whether there is any statistically significant differences between the search algorithms when implemented in the three programming languages and it was revealed that the three (3) programming languages do not vary considerably for both linear and binary search techniques which implies that any of the (3) programming languages is suitable for coding linear and binary search algorithms.

scholarly journals RESEARCH TRENDS IN SOFTWARE ENGINEERING FIELD: A LITERATURE REVIEW

2020 ◽  
Vol 7 (6) ◽  
pp. 58-65
Author(s):  
Hiba Al Sghaier
Keyword(s):  
Software Engineering ◽  
Programming Languages ◽  
New Technologies ◽  
Research Trends ◽  
Mobile Technologies ◽  
Smart Devices ◽  
Software Systems ◽  
Current Time ◽  
Develop Software ◽  
Software Engineers

Software engineering is one of computer science branches, it comprises of building and developing software systems and applications. Software engineering is a discipline that has a constant growth in research in aim to identify new technologies and adopt it in different areas; there is a considerable investment on software engineering trends at the current time due to the availability of mobile technologies. With millions of billions of smart devices that are connected to the internet, all industries around the world are rapidly becoming a technology driven industries. Software engineers are aware of programming languages that are employed to develop software systems, by applying engineering principles to development process; they can design customized software systems for individual or organizational customers. The new trends in software engineering are numerous, Cloud Computing, machine learning, deep learning, big Data, mobile Computing. Nevertheless, there are many more other research trends in software engineering's field that have been intensively explored and implemented in many different industries. In this paper, authors try to summarize the most fields that are integrated with software engineering recently.

scholarly journals Source Code Authorship Identification Using Deep Neural Networks

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2044 ◽  
Author(s):  
Anna Kurtukova ◽  
Aleksandr Romanov ◽  
Alexander Shelupanov
Keyword(s):  
Software Engineering ◽  
Programming Languages ◽  
Language Processing ◽  
Source Code ◽  
Research Area ◽  
The Public ◽  
Common Basis ◽  
Average Accuracy ◽  
Authorship Identification ◽  
Project Lifecycle

Many open-source projects are developed by the community and have a common basis. The more source code is open, the more the project is open to contributors. The possibility of accidental or deliberate use of someone else’s source code as a closed functionality in another project (even a commercial) is not excluded. This situation could create copyright disputes. Adding a plagiarism check to the project lifecycle during software engineering solves this problem. However, not all code samples for comparing can be found in the public domain. In this case, the methods of identifying the source code author can be useful. Therefore, identifying the source code author is an important problem in software engineering, and it is also a research area in symmetry. This article discusses the problem of identifying the source code author and modern methods of solving this problem. Based on the experience of researchers in the field of natural language processing (NLP), the authors propose their technique based on a hybrid neural network and demonstrate its results both for simple cases of determining the authorship of the code and for those complicated by obfuscation and using of coding standards. The results show that the author’s technique successfully solves the essential problems of analogs and can be effective even in cases where there are no obvious signs indicating authorship. The average accuracy obtained for all programming languages was 95% in the simple case and exceeded 80% in the complicated ones.

Sign in / Sign up

Export Citation Format

Share Document