A systematic literature review of traceability approaches between software architecture and source code

Author(s):  
Muhammad Atif Javed ◽  
Uwe Zdun
Author(s):  
Tahani Elfatih Babeker, Hany Ammar

  increase numbers and complexity of software development requires that learners of software engineering and software architecture or software architects who do not have sufficient practical experience must have the skills and abilities to perform their jobs. But there is a gap between academia and practical so the question why does not use one of the architecture description languages in teaching and learn software engineering and software architecture to fill this gap? The objective of this study to classification ADLs according to their domain, domain specific or general purpose languages, doing these systematic literature review flowing the steps from Ketchenham. As the result we find that most ADLs are Domain Specific ADLs (Aviation Systems, Distribution Systems, Mobile Systems, Product Lines …etc. ) none of these ADLs is used in the field of software architecture education, but most intended to deal with experts in the field, except general purpose ADLs, like ACME, which we make as start point to design Arabic ADL, so as to enrich Arabic content, also to be as helping language in teaching Software Architecture course, because most of ADLs need experience and high level of understanding to use, moreover, when student think and design with same language subject more understandable. So using software architecture description languages in educating purpose, help on understanding high level of abstraction of software architecture and software engineering courses, there are some studies that aimed to reduce the complexity of these courses using different methodologies and approaches, but none of them using architecture description languages as helping tool. So the use of architecture description languages is helpful in teaching software architecture and software engineering courses.  


IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 11307-11336 ◽  
Author(s):  
Zaigham Mushtaq ◽  
Ghulam Rasool ◽  
Balawal Shehzad

Author(s):  
Daniel Strmečki ◽  
Ivan Magdalenić ◽  
Danijel Radosević

One of the main goals of the Software Engineering discipline is to find higher abstraction levels and ways to reuse software in order to increase its productivity and quality. Ontologies, which are typically considered as a technique or an artifact used in one or more software lifecycle phases, may be used to help achieve that goal. This paper provides a systematic literature review of the proposed solutions for applying ontologies in automatic and generative programming. The paper aims to identify ontologies and software development tools, frameworks, prototypes, design patterns and methodologies that use them as development artifacts for source code generation or product derivation. The review provides researchers with the state of the art, while also identifying challenges and gaps that require further exploration and development.


2015 ◽  
Vol 6 (2) ◽  
pp. 361
Author(s):  
Ratih Nindyasari

ABSTRAK Refactoring perangat lunak merupakan sebuah teknik untuk mentransformasi struktur internal perangkat lunak tanpa merubah fungsionalitas perangkat lunak itu sendiri. Refactoring termasuk dalam bentuk evolusi perangkat lunak, dimana hal ini bertujuan untuk meningkatkan kualitas perangkat lunak itu sendiri setelah perangkat lunak mengalami perbaikan, modifikasi, penambahan dan aktivitas perubahan lainnya dalam masa hidupnya. Tujuan penulisan pada paper kali ini adalah untuk melakukan Systematic Literature Review (SLR) tentang persoalan deteksi refactoring pada level non-source code yang tergolong pada metode non-heuristic. Dengan dilakukan SLR ini terdapat beberapa teknik seperti clustering, searching, Information Retrieval dan analisis regresi dapat digunakan untuk mendeteksi persoalan refactoring pada level non-source code. Dari beberapa teknik-teknik ini masing-masing memiliki kelebihan dan kekurangan. Teknik yang memiliki tingkat komputasi yang tinggi seperti clustering, searching, dan analisis regresi biasanya mampu menghasilkan refactoring yang lebih optimal dan menyeluruh dibandingkan dengan teknik lainnya seperti NLP dan teknik similaritas. Kata kunci: refactoring, non-source code refactoring, non-heuristic, systematic literature review.


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