Handling preprocessor-conditioned declarations

Penta, Massimiliano Di; Baxter, Ira D.

doi:10.1109/scam.2002.1134108

Cited by 25 publications

(34 citation statements)

References 6 publications

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“…Based on data from our other data sources, we believe that low-level implementation dependencies represent at least 45 % of configuration constraints, which is very promising to automated tools. On the other hand, the three other categories of configuration constraints we found show that automated analysis is not sufficient to extract a complete variability 5. Short for "fast user-space mutex", which is a Linux kernel system call that programmers can use to implement basic locking model.…”

Section: Constraint Classification Discussionmentioning

confidence: 92%

“…More details on conditional symbol tables can be found in related publications on variability-aware module systems [5], [29]. In contrast to the file-local preprocessor, parser, and type constraint analyses, linker analysis is global across all translation units.…”

Section: Constraintsmentioning

confidence: 99%

“…However, recall that the reasoning behind Rule 1 and Rule 2 is different; the former represents errors, whereas the latter is a heuristic whose violation does not break the system. Thus, we still distinguish between both and yield the following three global formulas: rule1 = preprocessor^ parser^ type^ linker (4) rule2 = feffect^ feffect_build (5) code = rule1^ rule2 (6) In addition to the individual formulas 1-3, we will also use these global formulas 4-6 when assessing recoverability of existing variability-model constraints as will be shown in Section 5.…”

Section: Full Code Formulamentioning

confidence: 99%

See 2 more Smart Citations

Where Do Configuration Constraints Stem From? An Extraction Approach and an Empirical Study

Nadi

Berger

Kästner

et al. 2015

IIEEE Trans. Software Eng.

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Abstract-Highly configurable systems allow users to tailor software to specific needs. Valid combinations of configuration options are often restricted by intricate constraints. Describing options and constraints in a variability model allows reasoning about the supported configurations. To automate creating and verifying such models, we need to identify the origin of such constraints. We propose a static analysis approach, based on two rules, to extract configuration constraints from code. We apply it on four highly configurable systems to evaluate the accuracy of our approach and to determine which constraints are recoverable from the code. We find that our approach is highly accurate (93 % and 77 % respectively) and that we can recover 28 % of existing constraints. We complement our approach with a qualitative study to identify constraint sources, triangulating results from our automatic extraction, manual inspections, and interviews with 27 developers. We find that, apart from low-level implementation dependencies, configuration constraints enforce correct runtime behavior, improve users' configuration experience, and prevent corner cases. While the majority of constraints is extractable from code, our results indicate that creating a complete model requires further substantial domain knowledge and testing. Our results aim at supporting researchers and practitioners working on variability model engineering, evolution, and verification techniques.

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Section: Constraint Classification Discussionmentioning

confidence: 92%

Section: Constraintsmentioning

confidence: 99%

Section: Full Code Formulamentioning

confidence: 99%

See 1 more Smart Citation

Where Do Configuration Constraints Stem From? An Extraction Approach and an Empirical Study

Nadi

Berger

Kästner

et al. 2015

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

show abstract

“…Feature SSL adds class SSL (Lines 7-10) to the email client's code base and refines class Trans to encrypt outgoing messages (Lines [11][12][13][14][15]. To this effect, the refinement of Trans adds a new field key (Line 12) and overrides the method send of class Trans (Lines 13-15).…”

Section: An Overview Of Ffjmentioning

confidence: 99%

Type safety for feature-oriented product lines

et al. 2010

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A feature-oriented product line is a family of programs that share a common set of features. A feature implements a stakeholder's requirement and represents a design decision or configuration option. When added to a program, a feature involves the introduction of new structures, such as classes and methods, and the refinement of existing ones, such as extending methods. A feature-oriented decomposition enables a generator to create an executable program by composing feature code solely on the basis of the feature selection of a user -no other information needed. A key challenge of product line engineering is to guarantee that only well-typed programs are generated. As the number of valid feature combinations grows combinatorially with the number of features, it is not feasible to type check all programs individually. The only feasible approach is to have a type system check the entire code base of the feature-oriented product line. We have developed such a type system on the basis of a formal model of a feature-oriented Java-like language. The type system guaranties type safety for feature-oriented product lines. That is, it ensures that every valid program of a well-typed product line is well-typed. Our formal model including type system is sound and complete.

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“…Many researchers have attempted analysis and rewrite systems for unpreprocessed C code (Aversano et al, 2002;Hu et al, 2000;Overbey & Johnson, 2009;Vidacs et al, 2004;Tartler et al, 2011;Garrido & Johnson, 2005;Baxter & Mehlich, 2001;Livadas & Small, 1994). For example, Ernst et al (2002) identify problematic patterns and quantify them in a large code base, Tartler et al (2011) search for code blocks that are dead in all feature configurations, and Hu et al (2000) use control flow graphs to analyze the inclusion structure of files.…”

Section: Related Workmentioning

confidence: 99%

Do background colors improve program comprehension in the #ifdef hell?

et al. 2012

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Software-product-line engineering aims at the development of variable and reusable software systems. In practice, software product lines are often implemented with preprocessors. Preprocessor directives are easy to use, and many mature tools are available for practitioners. However, preprocessor directives have been heavily criticized in academia and even referred to as "#ifdef hell", because they introduce threats to program comprehension and correctness. There are many voices that suggest to use other implementation techniques instead, but these voices ignore the fact that a transition from preprocessors to other languages and tools is tedious, erroneous, and expensive in practice. Instead, we and others propose to increase the readability of preprocessor directives by using background colors to highlight source code annotated with ifdef directives. In three controlled experiments with over 70 subjects in total, we evaluate whether and how background colors improve program comprehension in preprocessor-based implementations. Our results demonstrate that background colors have the potential to improve program This is the authors' version and intended for personal use only. Any other use may violate the copyright. comprehension, independently of size and programming language of the underlying product. Additionally, we found that subjects generally favor background colors. We integrate these and other findings in a tool called FeatureCommander, which facilitates program comprehension in practice and which can serve as a basis for further research.

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Handling preprocessor-conditioned declarations

Abstract: Abstract

Cited by 25 publications

References 6 publications

Where Do Configuration Constraints Stem From? An Extraction Approach and an Empirical Study

Where Do Configuration Constraints Stem From? An Extraction Approach and an Empirical Study

Type safety for feature-oriented product lines

Do background colors improve program comprehension in the #ifdef hell?

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