Detecting anomalies in Kotlin code

Bryksin, Timofey; Petukhov, Victor; Kirill, Smirenko; Povarov, Nikita

doi:10.1145/3236454.3236457

Cited by 4 publications

(5 citation statements)

References 7 publications

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“…The tests also indicate that Flutter should not be used in applications that heavily depend on database operations. The same caution should be taken when using both Java and Kotlin/Native, especially because of some anomalies in the language which can and do affect its creation process [ 29 ].…”

Section: Discussionmentioning

confidence: 99%

A Comparison of Java, Flutter and Kotlin/Native Technologies for Sensor Data-Driven Applications

Wasilewski

Zabierowski

2021

Sensors

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As a result of the continuous progress and fast-growing popularity of mobile technologies in recent years, the demand for mobile applications has increased rapidly. One of the most important decisions that its developers have to make is the choice of technology on which their application will be based. This article is devoted to the comparison of Java, Flutter, and Kotlin/Native technologies for applications based on processing and analyzing data from sensors. The main elements of the comparison are the efficiency and resource utilization of mobile applications for Android OS implemented in each of the aforementioned technologies.

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Section: Discussionmentioning

confidence: 99%

A Comparison of Java, Flutter and Kotlin/Native Technologies for Sensor Data-Driven Applications

Wasilewski

Zabierowski

2021

Sensors

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“…For example, Courtney and Neilsen present a tool, named j2kCLI [55], that allows users to translate Java code to Kotlin faster than the same functionality provided by Android Studio. From the JetBrains research group, Bryksin et al [56] investigated code anomalies in Kotlin and whether these anomalies could improve the Kotlin compiler.…”

Section: Related Workmentioning

confidence: 99%

An experience-based recommendation system to support migrations of Android applications from Java to Kotlin

Mateus,

Martinez,

Kolski

2021

Preprint

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In 2017, Google announced Kotlin as an official Android programming language, and more recently, as the preferred programming language to build applications. These facts motivated developers to migrate their applications, which is challenging because each migrated piece of code must be tested after the migration to ensure it preserves the expected behavior. Due to the interoperability between Java and Kotlin, most developers decided to migrate their applications gradually. Thus, developers have to decide which file(s) to migrate first on each migration step. However, there are no tools available to help developers make these choices. This paper presents an approach to support a gradual migration of Android applications that given a version of an application written in Java and eventually, in Kotlin, it suggests the most convenient files to migrate. To this end, we built a large-scale corpus of open-source projects that migrated Java files to Kotlin. Then, we trained a learning to rank model using the information extracted from these projects. To validate our model, we verify whether these recommendations made by them correspond to real migrations. The results showed our approach modestly outperforms random approaches. Since most Android applications are written in Java, we conclude that our approach may significantly impact Android applications' development. Therefore, we consider this result is the first step into long-term research towards a model capable of predicting precisely file-level migration, establishing the initial baseline on file migrations.

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“…Indentation-aware languages such as Python [71], Occam [49], Haskell [30] or Kotlin [12] are quite popular and not as shunned now as they were some years ago [74]. However, in the very beginning of the programming language evolution assigning meaning to input characters based on which position within the string they were found, was rather commonexamples include COBOL [61], HLASM [57] or pre-f90 FOR-TRAN [7].…”

Section: Position-based Syntax (And Semantics)mentioning

confidence: 99%

“…The version on the left is written to make most use of problematic features of BabyCobol, while the version on the right avoids some of them and is thus easier to parse, compile and analyse, while being functionally equivalent. Lines (1) and ( 27) contain a comment ( § 3.1), lines (2), ( 6), ( 13), ( 28), (32) and (39) start separate divisions ( § 3.7), lines (8)(9) and (34)(35)(36)(37)(38) contain picture clauses ( § 4.1), lines (11)(12) -like clauses ( § 4.1), line (8) defines an identifier with a name equal to a keyword ( § 3.4), lines ( 12) and ( 22) declare an identifier and a paragraph with a dash in their names, line (14) does not use quotes and hence uses default values of three undefined fields ( § 4.4), line (16) relies on case insensitivity ( § 3.3), lines (15) and (51) execute picture-driven inputs, lines (17), (23), (43) and (49) -picture-driven output, line (16) uses a figurative constant on targets of different types ( § 4.3), lines (20) and (46) contain an out-of-line PERFORM statement ( § 5.2) calling the paragraph on lines (22)(23)(24)(25)(26) or (48)(49)(50)(51)(52), lines (25)(26) exploit whitespace insignificance ( § 3.5), lines (17), (19), (23)…”

Section: Position-based Syntax (And Semantics)mentioning

confidence: 99%

“…ASSIGN 12 TO N GO TO N, (7,12,19) On one hand, the ASSIGN command is more than a simple value assignment (which could have taken the form of "N = 12"), since it signals to the compiler that the variable N will be used as a label name and from that point on cannot be used in arithmetic expressions. On the other hand, the GO TO command, which can be very far removed from the actual target assignment in real code, contains a list of allowed assignable line numbers, and thus helps the programmer to read and understand this code, as well as allows the compiler to statically check all related ASSIGNs against this list.…”

Section: Inspirational Languages Summarymentioning

confidence: 99%

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Software language engineers’ worst nightmare

Zaytsev

2020

Proceedings of the 13th ACM SIGPLAN International Conference on Software Language Engineering

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Many techniques in software language engineering get their first validation by being prototyped to work on one particular language such as Java, Scala, Scheme, or ML, or a subset of such a language. Claims of their generalisability, as well as discussion on potential threats to their external validity, are often based on authors' ad hoc understanding of the world outside their usual comfort zone. To facilitate and simplify such discussions by providing a solid measurable ground, we propose a language called BabyCobol, which was specifically designed to contain features that turn processing legacy programming languages such as COBOL, FORTRAN, PL/I, REXX, CLIST, and 4GLs (fourth generation languages), into such a challenge. The language is minimal by design so that it can help to quickly find weaknesses in frameworks making them inapplicable to dealing with legacy software. However, applying new techniques of software language engineering and reverse engineering to such a small language will not be too tedious and overwhelming. BabyCobol was designed in collaboration with industrial compiler developers by systematically traversing features of several second, third and fourth generation languages to identify the core culprits in making development of compiler for legacy languages difficult.

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Detecting anomalies in Kotlin code

Cited by 4 publications

References 7 publications

A Comparison of Java, Flutter and Kotlin/Native Technologies for Sensor Data-Driven Applications

A Comparison of Java, Flutter and Kotlin/Native Technologies for Sensor Data-Driven Applications

An experience-based recommendation system to support migrations of Android applications from Java to Kotlin

Software language engineers’ worst nightmare

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