A Propriedade Intelectual Aplicada à Gestão de Fábricas de Software Acadêmicas

The creation of Academic Software Factories is an important means to improve  the learning skills of students of Computing degrees. As the main aim of such software factories is to develop software, it is fundamental to concern with the software intellectual property management. Thus this article, based on a literature review and an analysis of  the pertinent law, aims to provide a model for the software intellectual property management. After adopting the proposed model, it is expected a positive impact on the software factories’ learning curve, as well as a more precise attribuition of copyrightA criação de Fábricas de Software Acadêmicas (FSA) é uma importante ferramenta para melhorar o aprendizado de alunos em cursos de graduação na área de Computação. Como o desenvolvimento de softwares é o principal objetivo dessas FSA, uma tarefa central é a gestão da propriedade intelectual desses bens imateriais com potencial valor econômico. Dessa forma, esse artigo, por meio de revisão bibiográfica e análise da legislação pertinente, propõe um modelo de gestão da propriedade intelectual para Fábricas de software. Espera-se que as ações propostas possam ter impacto positivo na curva de aprendizagem das FSA, bem como melhorar a acurácia da titularidade e autoria dos artefatos de software desenvolvidos na FSA, contribuindo assim para o aprimoramento de seus processos gerenciais

A Decade of Code Comment Quality Assessment: A Systematic Literature Review

Code comments are important artifacts in software systems and play a paramount role in many software engineering (SE) tasks related to maintenance and program comprehension. However, while it is widely accepted that high quality matters in code comments just as it matters in source code, assessing comment quality in practice is still an open problem. First and foremost, there is no unique definition of quality when it comes to evaluating code comments. The few existing studies on this topic rather focus on specific attributes of quality that can be easily quantified and measured. Existing techniques and corresponding tools may also focus on comments bound to a specific programming language, and may only deal with comments with specific scopes and clear goals (e.g., Javadoc comments at the method level, or in-body comments describing TODOs to be addressed). In this paper, we present a Systematic Literature Review (SLR) of the last decade of research in SE to answer the following research questions: (i) What types of comments do researchers focus on when assessing comment quality? (ii) What quality attributes (QAs) do they consider? (iii) Which tools and techniques do they use to assess comment quality?, and (iv) How do they evaluate their studies on comment quality assessment in general? Our evaluation, based on the analysis of 2353 papers and the actual review of 47 relevant ones, shows that (i) most studies and techniques focus on comments in Java code, thus may not be generalizable to other languages, and (ii) the analyzed studies focus on four main QAs of a total of 21 QAs identified in the literature, with a clear predominance of checking consistency between comments and the code. We observe that researchers rely on manual assessment and specific heuristics rather than the automated assessment of the comment quality attributes

Software Provenance Tracking at the Scale of Public Source Code

International audienceWe study the possibilities to track provenance of software source code artifacts within the largest publicly accessible corpus of publicly available source code, the Software Heritage archive, with over 4 billions unique source code files and 1 billion commits capturing their development histories across 50 million software projects. We perform a systematic and generic estimate of the replication factor across the different layers of this corpus, analysing how much the same artifacts (e.g., SLOC, files or commits) appear in different contexts (e.g., files, commits or source code repositories). We observe a combinatorial explosion in the number of identical source code files across different commits. To discuss the implication of these findings, we benchmark different data models for capturing software provenance information at this scale, and we identify a viable solution, based on the properties of isochrone subgraphs, that is deployable on commodity hardware, is incremental and appears to be maintainable for the foreseeable future. Using these properties, we quantify, at a scale never achieved previously, the growth rate of original, i.e. never-seen-before, source code files and commits, and find it to be exponential over a period of more than 40 years

Tekijänoikeus osana kokeiluja hyödyntävän ohjelmistoyrityksen IPR-strategiaa

Tutkielman tavoitteena on hahmottaa ohjelmistokehitykseen tähtääviin kokeiluihin liittyviä tekijänoikeudellisia kysymyksiä sekä antaa kokeiluja käyttävän ohjelmistoyrityksen IPRstrategiaan liittyviä toimintasuosituksia. Esityksessä käytetään oikeusdogmaattista metodia sen selvittämiseksi, millaisin keinoin kokeiluja suorittava ohjelmistoyritys voi voimassa olevan lainsäädännön asettamissa kehyksissä hallita aineetonta omaisuuttaan kannattavasti. Tutkielmassa tarkastellaan ensinnäkin sitä, miten yritys voi laillisesti hyödyntää kokeilussa ulkopuolisten tuottamaa tekijänoikeudellista materiaalia, jotta kokeilu voitaisiin viedä läpi mahdollisimman joutuisasti ja edullisesti. Valmiiden ratkaisujen lisensiointi osaksi kehitettävää prototyyppiä voi olla kannattavaa, jos haluttuja ominaisuuksia ei tällöin tarvitse kehittää alusta asti itse. Nopeutta vaativissa ohjelmistokehitysprojekteissa kierrätetäänkin usein avointa lähdekoodia, jota voidaan lisensioida ilman merkittäviä transaktiokustannuksia. Tuotekehityksen alkuvaiheen kokeiluja voidaan suorittaa myös käyttämällä koodittomia prototyyppejä, joiden hyödyntäminen ei vaadi teknistä erityisosaamista, lisenssimaksujen suorittamista tai lisensiointiin liittyvää riskienhallintaa. Toiseksi tutkitaan sitä, kenelle tekijänoikeudet voivat kokeilussa syntyä ja millaisin toimintatavoin yritys voi siirtää oikeudet itselleen. Ohjelmistokehityksen tapauksessa kokeiluihin osallistuvat ulkopuoliset koehenkilöt tuskin yleensä antanevat prosessiin sellaista luovaa panosta, että heitä voitaisiin pitää kehitettävän prototyypin tekijöinä. Jos koehenkilöllä on kuitenkin mahdollisuus aktiivisesti osallistua prototyypin muokkaamiseen, voi hänellekin syntyä tekijänoikeus työnsä tulokseen. Jotta yritys voisi varmistaa tekijänoikeuksien siirtymisen itselleen, kannattaa sen joko sopia oikeuksien siirtämisestä yksinkertaisin vakiosopimuksin tai määritellä koehenkilöiden rooli kokeilussa sellaiseksi, ettei heidän toimintansa ole tekijänoikeudellisesti merkityksellistä. Lopulta luodaan katsaus siihen, millainen rooli tekijänoikeudella on osana kokeiluja käyttävän yrityksen IPR-strategiaa suhteessa muihin ohjelmistoalalla yleisesti käytettyihin suojauskeinoihin. Tekijänoikeus ja ei-muodolliset suojauskeinot näyttäytyvät patentointia joustavampina ja edullisempina vaihtoehtoina, ja ei-muodolliset menetelmät soveltuvat erityisesti tuotekehityksen alkuvaiheeseen, jolloin tekijänoikeus- tai patenttilain asettamat suojan saamisen edellytykset eivät vielä täyty. Kokeiluja suorittavan yrityksen IPR-strategiaan voisivat soveltua hyvin myös avoimen innovaation periaatteet

Assessing Comment Quality in Object-Oriented Languages

Previous studies have shown that high-quality code comments support developers in software maintenance and program comprehension tasks. However, the semi-structured nature of comments, several conventions to write comments, and the lack of quality assessment tools for all aspects of comments make comment evaluation and maintenance a non-trivial problem. To understand the specification of high-quality comments to build effective assessment tools, our thesis emphasizes acquiring a multi-perspective view of the comments, which can be approached by analyzing (1) the academic support for comment quality assessment, (2) developer commenting practices across languages, and (3) developer concerns about comments. Our findings regarding the academic support for assessing comment quality showed that researchers primarily focus on Java in the last decade even though the trend of using polyglot environments in software projects is increasing. Similarly, the trend of analyzing specific types of code comments (method comments, or inline comments) is increasing, but the studies rarely analyze class comments. We found 21 quality attributes that researchers consider to assess comment quality, and manual assessment is still the most commonly used technique to assess various quality attributes. Our analysis of developer commenting practices showed that developers embed a mixed level of details in class comments, ranging from high-level class overviews to low-level implementation details across programming languages. They follow style guidelines regarding what information to write in class comments but violate the structure and syntax guidelines. They primarily face problems locating relevant guidelines to write consistent and informative comments, verifying the adherence of their comments to the guidelines, and evaluating the overall state of comment quality. To help researchers and developers in building comment quality assessment tools, we contribute: (i) a systematic literature review (SLR) of ten years (2010–2020) of research on assessing comment quality, (ii) a taxonomy of quality attributes used to assess comment quality, (iii) an empirically validated taxonomy of class comment information types from three programming languages, (iv) a multi-programming-language approach to automatically identify the comment information types, (v) an empirically validated taxonomy of comment convention-related questions and recommendation from various Q&A forums, and (vi) a tool to gather discussions from multiple developer sources, such as Stack Overflow, and mailing lists. Our contributions provide various kinds of empirical evidence of the developer’s interest in reducing efforts in the software documentation process, of the limited support developers get in automatically assessing comment quality, and of the challenges they face in writing high-quality comments. This work lays the foundation for future effective comment quality assessment tools and techniques

Assessing Comment Quality in Object-Oriented Languages

Previous studies have shown that high-quality code comments support developers in software maintenance and program comprehension tasks. However, the semi-structured nature of comments, several conventions to write comments, and the lack of quality assessment tools for all aspects of comments make comment evaluation and maintenance a non-trivial problem. To understand the specification of high-quality comments to build effective assessment tools, our thesis emphasizes acquiring a multi-perspective view of the comments, which can be approached by analyzing (1) the academic support for comment quality assessment, (2) developer commenting practices across languages, and (3) developer concerns about comments. Our findings regarding the academic support for assessing comment quality showed that researchers primarily focus on Java in the last decade even though the trend of using polyglot environments in software projects is increasing. Similarly, the trend of analyzing specific types of code comments (method comments, or inline comments) is increasing, but the studies rarely analyze class comments. We found 21 quality attributes that researchers consider to assess comment quality, and manual assessment is still the most commonly used technique to assess various quality attributes. Our analysis of developer commenting practices showed that developers embed a mixed level of details in class comments, ranging from high-level class overviews to low-level implementation details across programming languages. They follow style guidelines regarding what information to write in class comments but violate the structure and syntax guidelines. They primarily face problems locating relevant guidelines to write consistent and informative comments, verifying the adherence of their comments to the guidelines, and evaluating the overall state of comment quality. To help researchers and developers in building comment quality assessment tools, we contribute: (i) a systematic literature review (SLR) of ten years (2010–2020) of research on assessing comment quality, (ii) a taxonomy of quality attributes used to assess comment quality, (iii) an empirically validated taxonomy of class comment information types from three programming languages, (iv) a multi-programming-language approach to automatically identify the comment information types, (v) an empirically validated taxonomy of comment convention-related questions and recommendation from various Q&A forums, and (vi) a tool to gather discussions from multiple developer sources, such as Stack Overflow, and mailing lists. Our contributions provide various kinds of empirical evidence of the developer’s interest in reducing efforts in the software documentation process, of the limited support developers get in automatically assessing comment quality, and of the challenges they face in writing high-quality comments. This work lays the foundation for future effective comment quality assessment tools and techniques