Automated Developer Testing: Achievements and Challenges Tao Xie North Carolina State University In collaboration with Nikolai Tillmann, Peli de Halleux, Wolfram Schulte @Microsoft Research and students @NCSU ASE

Why Automate Testing? Software testing is important Software errors cost the U.S. economy about $59.5 billion each year (0.6% of the GDP) [NIST 02] Improving testing infrastructure could save 1/3 cost [NIST 02] Software testing is costly Account for even half the total cost of software development [Beizer 90] Automated testing reduces manual testing effort Test execution: JUnit, NUnit, xUnit, etc. Test generation: Pex, AgitarOne, Parasoft Jtest, etc. Test-behavior checking: Pex, AgitarOne, Parasoft Jtest, etc.

Automation in Developer Testing http://www.developertesting.com/ Kent Beck’s 2004 talk on “Future of Developer Testing” http://www.itconversations.com/shows/detail301.html This talk focuses on tool automation in developer testing (e.g., unit testing) Not system testing etc. conducted by testers

Software Testing Setup = ? + Expected Outputs Test inputs Program Outputs Test Oracles

Software Testing Problems = ? + Expected Outputs Test inputs Program Outputs Test Oracles Test Generation Generating high-quality test inputs (e.g., achieving high code coverage)

Software Testing Problems = ? + Expected Outputs Test inputs Program Outputs Test Oracles Test Generation Generating high-quality test inputs (e.g., achieving high code coverage) Test Oracles Specifying high-quality test oracles (e.g., guarding against various faults)

The Recipe of Unit Testing Three essential ingredients: Data Method Sequence Assertions void TestAdd() { int item = 3; var list = new List(); list.Add(item); Assert.AreEqual(1, list.Count); }

Parameterized Unit Testing [Tillmann&Schulte ESEC/FSE 05] Parameterized Unit Test = Unit Test with Parameters Separation of concerns Data is generated by a tool Developer can focus on functional specification void TestAdd(List list, int item) { Assume.IsTrue(list != null); var count = list.Count; list.Add(item); Assert.AreEqual(count + 1, list.Count); }

Parameterized Unit Tests are Algebraic Specifications A Parameterized Unit Test can be read as a universally quantified, conditional axiom. void TestReadWrite(Res r, string name, string data) { Assume.IsTrue(r!=null & name!=null && data!=null); r.WriteResource(name, data); Assert.AreEqual(r.ReadResource(name), data); }  string name, string data, Res r: r ≠ null ⋀ name ≠ null ⋀ data ≠ null ⇒ equals( ReadResource(WriteResource(r, name, data).state, name), data)

Parameterized Unit Testing Getting Popular Parameterized Unit Tests (PUTs) commonly supported by various test frameworks .NET: Supported by .NET test frameworks http://www.mbunit.com/ http://www.nunit.org/ … Java: Supported by JUnit 4.X http://www.junit.org/ Generating test inputs for PUTs supported by tools .NET: Supported by Microsoft Research Pex http://research.microsoft.com/Pex/ Java: Supported by Agitar AgitarOne http://www.agitar.com/

Test Generation Human Brute Force Random: Expensive, incomplete, … Brute Force Pairwise, predefined data, etc… Random: Cheap, Fast “It passed a thousand tests” feeling Dynamic Symbolic Execution: Pex, CUTE,EXE Automated white-box Not random – Constraint Solving

Dynamic Symbolic Execution Choose next path Code to generate inputs for: Solve Execute&Monitor void CoverMe(int[] a) { if (a == null) return; if (a.Length > 0) if (a[0] == 1234567890) throw new Exception("bug"); } Constraints to solve a!=null a!=null && a.Length>0 a.Length>0 && a[0]==1234567890 Data null {} {0} {123…} Observed constraints a==null a!=null && !(a.Length>0) a.Length>0 && a[0]!=1234567890 a[0]==1234567890 Negated condition a==null F T a.Length>0 F T Done: There is no path left. a[0]==123… F T

Challenges of DSE Loops Fitnex [Xie et al. DSN 09] Generic API functions e.g., RegEx matching IsMatch(s1,regex1) Reggae [Li et al. ASE 09-sp] Method sequences MSeqGen [Thummalapenta et al. ESEC/FSE 09] Environments e.g., file systems, network, db, … Parameterized Mock Objects [Marri et al. AST 09] Opportunities Regression testing [Taneja et al. ICSE 09-nier] Developer guidance (cooperative developer testing)

NCSU Industry Tech Transfer Loops Fitnex [Xie et al. DSN 09] Generic API functions e.g., RegEx matching IsMatch(s1,regex1) Reggae [Li et al. ASE 09-sp] Method sequences MSeqGen [Thummalapenta et al. ESEC/FSE 09] Environments e.g., file systems, network, db, … Parameterized Mock Objects [Marri et al. AST 09] Applications Test network app at Army division@Fort Hood, Texas Test DB app of hand-held medical assistant device at FDA

Pex on MSDN DevLabs Incubation Project for Visual Studio 11/11/2018 5:55 AM Pex on MSDN DevLabs Incubation Project for Visual Studio Download counts (20 months) (Feb. 2008 - Oct. 2009 ) Academic: 17,366 Devlabs: 13,022 Total: 30,388 © 2008 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

NCSU Industry Tech Transfer Loops Fitnex [Xie et al. DSN 09] Generic API functions e.g., RegEx matching IsMatch(s1,regex1) Reggae [Li et al. ASE 09-sp] Method sequences MSeqGen [Thummalapenta et al. ESEC/FSE 09] Environments e.g., file systems, network, db, … Parameterized Mock Objects [Marri AST 09] Applications Test network app at Army division@Fort Hood, Texas Test DB app of hand-held medical assistant device at FDA

Explosion of Search Space There are decision procedures for individual path conditions, but… Number of potential paths grows exponentially with number of branches Without guidance, same loop might be unfolded forever Fitnex search strategy [Xie et al. DSN 09]

DSE Example public bool TestLoop(int x, int[] y) { if (x == 90) { for (int i = 0; i < y.Length; i++) if (y[i] == 15) x++; if (x == 110) return true; } return false; Test input: TestLoop(0, {0}) Path condition: !(x == 90) ↓ New path condition: (x == 90) New test input: TestLoop(90, {0})

DSE Example public bool TestLoop(int x, int[] y) { if (x == 90) { for (int i = 0; i < y.Length; i++) if (y[i] == 15) x++; if (x == 110) return true; } return false; Test input: TestLoop(90, {0}) Path condition: (x == 90) && !(y[0] == 15) ↓ New path condition: (x == 90) && (y[0] == 15) New test input: TestLoop(90, {15})

Challenge in DSE public bool TestLoop(int x, int[] y) { if (x == 90) { for (int i = 0; i < y.Length; i++) if (y[i] == 15) x++; if (x == 110) return true; } return false; Test input: TestLoop(90, {15}) Path condition: (x == 90) && (y[0] == 15) && !(x+1 == 110) ↓ New path condition: (x == 90) && (y[0] == 15) && (x+1 == 110) New test input: No solution!?

A Closer Look public bool TestLoop(int x, int[] y) { if (x == 90) { for (int i = 0; i < y.Length; i++) if (y[i] == 15) x++; if (x == 110) return true; } return false; Test input: TestLoop(90, {15}) Path condition: (x == 90) && (y[0] == 15) && (0 < y.Length) && !(1 < y.Length) && !(x+1 == 110) ↓ New path condition: && (1 < y.Length)  Expand array size

A Closer Look We can have infinite paths! (both length and number) public bool TestLoop(int x, int[] y) { if (x == 90) { for (int i = 0; i < y.Length; i++) if (y[i] == 15) x++; if (x == 110) return true; } return false; Test input: TestLoop(90, {15}) We can have infinite paths! (both length and number) Manual analysis  need at least 20 loop iterations to cover the target branch Exploring all paths up to 20 loop iterations is practically infeasible: 220 paths

Fitnex: Fitness-Guided Exploration public bool TestLoop(int x, int[] y) { if (x == 90) { for (int i = 0; i < y.Length; i++) if (y[i] == 15) x++; if (x == 110) return true; } return false; Test input: TestLoop(90, {15, 15}) Key observations: with respect to the coverage target, not all paths are equally promising for flipping nodes not all nodes are equally promising to flip Our solution: Prefer to flip nodes on the most promising path Prefer to flip the most promising nodes on path Use fitness function as a proxy for promising

Fitness Function FF computes fitness value (distance between the current state and the goal state) Search tries to minimize fitness value [Tracey et al. 98, Liu at al. 05, …]

Fitness Function for (x == 110) public bool TestLoop(int x, int[] y) { if (x == 90) { for (int i = 0; i < y.Length; i++) if (y[i] == 15) x++; if (x == 110) return true; } return false; Fitness function: |110 – x |

Compute Fitness Values for Paths public bool TestLoop(int x, int[] y) { if (x == 90) { for (int i = 0; i < y.Length; i++) if (y[i] == 15) x++; if (x == 110) return true; } return false; (x, y) (90, {0}) 20 (90, {15}) 19 (90, {15, 0}) 19 (90, {15, 15}) 18 (90, {15, 15, 0}) 18 (90, {15, 15, 15}) 17 (90, {15, 15, 15, 0}) 17 (90, {15, 15, 15, 15}) 16 (90, {15, 15, 15, 15, 0}) 16 (90, {15, 15, 15, 15, 15}) 15 … Fitness function: |110 – x | Give preference to flip a node in paths with better fitness values. We still need to address which node to flip on paths …

Compute Fitness Gains for Branches Fitness Value public bool TestLoop(int x, int[] y) { if (x == 90) { for (int i = 0; i < y.Length; i++) if (y[i] == 15) x++; if (x == 110) return true; } return false; (x, y) (90, {0}) 20 (90, {15})  flip b4 19 (90, {15, 0})  flip b2 19 (90, {15, 15})  flip b4 18 (90, {15, 15, 0})  flip b2 18 (90, {15, 15, 15})  flip b4 17 (90, {15, 15, 15, 0})  flip b2 17 (90, {15, 15, 15, 15})  flip b4 16 (90, {15, 15, 15, 15, 0})  flip b2 16 (90, {15, 15, 15, 15, 15})  flip b4 15 … Fitness function: |110 – x | Branch b1: i < y.Length Branch b2: i >= y.Length Branch b3: y[i] == 15 Branch b4: y[i] != 15 Flipping branch node of b4 (b3) gives us average 1 (-1) fitness gain (loss) Flipping branch node of b2 (b1) gives us average 0 (0) fitness gain (loss)

Compute Fitness Gains for Branches FGain(b) := F(p) – F(p’) FGain(b’) := F(p’) – F(p) Compute the average fitness gain for each program branch over time p p’ n n b b’ …. …. F(p) is the fitness value of p F(p’) is the fitness value of p’

Implementation in Pex Pex maintains global search frontier All discovered branch nodes are added to frontier Frontier may choose next branch node to flip Fully explored branch nodes are removed from frontier Pex has a default search frontier It tries to create diversity across different coverage criteria Frontiers can be combined in a fair round-robin scheme

Implementation in Pex We implemented a new search frontier “Fitnex”: Nodes to flip are prioritized by their composite fitness value: F(pn) – FGain(bn), where pn is path of node n bn is explored outgoing branch of n Fitnex always picks node with lowest composite fitness value to flip. To avoid local optimal or biases, the fitness-guided strategy is combined with Pex’s search strategies

Evaluation Subjects A collection of micro-benchmark programs routinely used by the Pex developers to evaluate Pex’s performance, extracted from real, complex C# programs Ranging from string matching like if (value.StartsWith("Hello") && value.EndsWith("World!") && value.Contains(" ")) { … } to a small parser for a Pascal-like language where the target is to create a legal program.

Search Strategies Under Comparison Pex with the Fitnex strategy Pex without the Fitnex strategy Pex’s previous default strategy Random a strategy where branch nodes to flip are chosen randomly in the already explored execution tree Iterative Deepening a strategy where breadth-first search is performed over the execution tree

Evaluation Results #runs/iterations required to cover the target Pex w/o Fitnex: avg. improvement of factor 1.9 over Random Pex w/ Fitnex: avg. improvement of factor 5.2 over Random

Object Creation Pex normally uses public methods to configure non-public object fields Heuristics built-in to deal with common types User can help if needed void (Foo foo) { if (foo.Value == 123) throw … [PexFactoryMethod] Foo Create(Bar bar) { return new Foo(bar); }

QuickGraph Example A graph example from QuickGraph library interface IGraph { /* Adds given vertex to the graph */ void AddVertex(IVertex v); /* Creates a new vertex and adds it to the graph */ IVertex AddVertex(); /* Adds an edge to the graph. Both vertices should already exist in the graph */ IEdge AddEdge(IVertex v1, Ivertex v2); } 35 35

Method Under Test Desired object state for reaching targets 1 and 2: graph object should contain vertices and edges Class SortAlgorithm { IGraph graph; public SortAlgorithm(IGraph graph) { this.graph = graph; } public void Compute (IVertex s) { foreach(IVertex u in graph.Vertices) //Target 1 foreach(IEdge e in graph.Edges) //Target 2 method sequence

Example sequence generated by Randoop Method Under Test Applying Randoop, a random testing approach that constructs test inputs by randomly selecting method calls Example sequence generated by Randoop VertexAndEdgeProvider v0 = new VertexAndEdgeProvider(); Boolean v1 = false; BidirectionalGraph v2 = new BidirectionalGraph((IVertexAndEdgeProvider)v0, v1); IVertex v3 = v2.AddVertex(); IVertex v4 = v0.ProvideVertex(); IEdge v15 = v2.AddEdge(v3, v4); v4 not in the graph, so edge cannot be added to graph. Achieved 31.82% (7 of 22) branch coverage Reason for low coverage: Not able to generate graph with vertices and edges

A Mined sequence from an existing codebase New MSeqGen Approach Mine sequences from existing code bases Reuse mined sequences for achieving desired object states A Mined sequence from an existing codebase VertexAndEdgeProvider v0; bool bVal; IGraph ag = new AdjacencyGraph(v0, bVal); IVertex source = ag.AddVertex(); IVertex target = ag.AddVertex(); IVertex vertex3 = ag.AdVertex(); IEdge edg1 = ag.AddEdge(source, target); IEdge edg2 = ag.AddEdge(target, vertex3); IEdge edg3 = ag.AddEdge(source, vertex3); Graph object includes both vertices and edges Use mined sequences to assist Randoop and Pex Both Randoop and Pex achieved 86.40% (19 of 22) branch coverage with assistance from MSeqGen

Challenges Addressed by MSeqGen Existing codebases are often large and complete analysis is expensive  Search and analyze only relevant portions Concrete values in mined sequences may be different from desired values  Replace concrete values with symbolic values and use dynamic symbolic execution Extracted sequences individually may not be sufficient to achieve desired object states  Combine extracted sequences to generate new sequences

MSeqGen: Code Searching Problem: Existing code bases are often large and complete analysis is expensive Solution: Use keyword search for identifying relevant method bodies using target classes Analyze only those relevant method bodies Target classes: System.Collections.Hashtable QuickGraph.Algorithms.TSAlgorithm Keywords: Hashtable, TSAlgorithm Shortnames of target classes are used as keywords

MSeqGen: Sequence Generalization Problem: Concrete values in mined sequences are different from desired values to achieve target states Solution: Generalize sequences by replacing concrete values with symbolic values Method Under Test Class A { int f1 { set; get; } int f2 { set; get; } void CoverMe() { if (f1 != 10) return; if (f2 > 25) throw new Exception(“bug”); } Mined Sequence for A A obj = new A(); obj.setF1(14); obj.setF2(-10); obj.CoverMe(); Sequence cannot help in exposing bug since desired values are f1=10 and f2>25

MSeqGen: Sequence Generalization Replace concrete values 14 and -10 with symbolic values X1 and X2 Mined Sequence for A Generalized Sequence for A A obj = new A(); obj.setF1(14); obj.setF2(-10); obj.CoverMe(); int x1 = *, x2 = *; A obj = new A(); obj.setF1(x1); obj.setF2(x2); obj.CoverMe(); Use DSE for generating desired values for X1 and X2 DSE explores CoverMe method and generates desired values (X1 = 10 and X2 = 35)

Improvement of State-of-the-Art Randoop Without assistance from MSeqGen: achieved 32% branch coverage  achieved 86% branch coverage In evaluation, help Randoop achieve 8.7% (maximum 20%) higher branch coverage Pex Without assistance from MSeqGen: achieved 45% branch coverage  achieved 86% branch coverage In evaluation, help Pex achieve 17.4% (maximum 22.5%) higher branch coverage 43 43

Test Oracles Write assertions and Pex will try to break them Without assertions, Pex can only find violations of runtime contracts causing NullReferenceException, IndexOutOfRangeException, etc. Assertions leveraged in product and test code Pex can leverage Code Contracts

Summary: Automated Developer Testing = ? + Expected Outputs Test inputs Program Outputs Test Oracles Division of Labors Test Generation Test inputs for PUT generated by tools (e.g., Pex) Fitnex: guided exploration of paths [DSN 09] MSeqGen: exploiting real-usage sequences [ESEC/FSE 09] Test Oracles Assertions in PUT specified by developers

Thank you http://research.microsoft.com/pex http://pexase.codeplex.com/ https://sites.google.com/site/asergrp/

Code Contracts http://research.microsoft.com/en-us/projects/contracts/ Library to state preconditions, postconditions, invariants Supported by two tools: Static Checker Rewriter: turns Code Contracts into runtime checks Pex analyses the runtime checks Contracts act as Test Oracle Pex may find counter examples for contracts Missing Contracts may be suggested

Example: ArrayList Class invariant specification: public class ArrayList { private Object[] _items; private int _size; ... [ContractInvariantMethod] // attribute comes with Contracts protected void Invariant() { Contract.Invariant(this._items != null); Contract.Invariant(this._size >= 0); Contract.Invariant(this._items.Length >= this._size); } How many tests do you expect to cover all reachable branches for this scenario?

Parameterized Models

Unit Testing vs. Integration Testing Unit test: while it is debatable what a ‘unit’ is, a ‘unit’ should be small. Integration test: exercises large portions of a system. Observation: Integration tests are often “sold” as unit tests White-box test generation does not scale well to integration test scenarios. Possible solution: Introduce abstraction layers, and mock components not under test

Example Testing with Interfaces AppendFormat(null, “{0} {1}!”, “Hello”, “World”);  “Hello World!” .Net Implementation: public StringBuilder AppendFormat( IFormatProvider provider, char[] chars, params object[] args) { if (chars == null || args == null) throw new ArgumentNullException(…); int pos = 0; int len = chars.Length; char ch = '\x0'; ICustomFormatter cf = null; if (provider != null) cf = (ICustomFormatter)provider.GetFormat(typeof(ICustomFormatter)); …

Stubs / Mock Objects Introduce a mock class which implements the interface. Write assertions over expected inputs, provide concrete outputs public class MFormatProvider : IFormatProvider { public object GetFormat(Type formatType) { Assert.IsTrue(formatType != null); return new MCustomFormatter(); } Problems: Costly to write detailed behavior by example How many and which mock objects do we need to write?

Parameterized Mock Objects - 1 Introduce a mock class which implements the interface. Let an oracle provide the behavior of the mock methods. public class MFormatProvider : IFormatProvider { public object GetFormat(Type formatType) { … object o = call.ChooseResult<object>(); return o; } Result: Relevant result values can be generated by white-box test input generation tool, just as other test inputs can be generated!

Parameterized Mock Objects - 2 Chosen values can be shaped by assumptions public class MFormatProvider : IFormatProvider { public object GetFormat(Type formatType) { … object o = call.ChooseResult<object>(); PexAssume.IsTrue(o is ICustomFormatter); return o; } (Note: Assertions and assumptions are “reversed” when compared to parameterized unit tests.)

Models from Choices Choices to build parameterized models class PFileSystem : IFileSystem { // cached choices PexChosenIndexedValue<string,string> files; string ReadFile(string name) { var content = this.files[name]; if (content == null) throw new FileNotFoundException(); return content; }}

MSeqGen Evaluation Subjects: QuickGraph Facebook Research Questions: RQ1: Can our approach assist Randoop (random testing tool) in achieving higher code coverages? RQ2: Can our approach assist Pex (DSE-based testing tool) in achieving higher code coverages? 56 56 56 56 56

RQ1: Assisting Randoop 57 57 57 57

RQ2: Assisting Pex Legend: #c: number of classes P: branch coverage achieved by Pex P + M: branch coverage achieved by Pex and MSeqGen 58 58 58 58

Assumptions and Assertions void PexAssume.IsTrue(bool c) { if (!c) throw new AssumptionViolationException(); } void PexAssert.IsTrue(bool c) { if (!c) throw new AssertionViolationException(); } Assumptions and assertions induce branches Executions which cause assumption violations are ignored, not reported as errors or test cases

Motivation: Unit Testing Hell ResourceReader How to test this code? (Actual code from .NET base class libraries)

Motivation: Unit Testing Hell ResourceReader

ResourceReader PUT [PexClass, TestClass] [PexAllowedException(typeof(ArgumentNullException))] [PexAllowedException(typeof(ArgumentException))] [PexAllowedException(typeof(FormatException))] [PexAllowedException(typeof(BadImageFormatException))] [PexAllowedException(typeof(IOException))] [PexAllowedException(typeof(NotSupportedException))] public partial class ResourceReaderTest { [PexMethod] public unsafe void ReadEntries(byte[] data) { PexAssume.IsTrue(data != null); fixed (byte* p = data) using (var stream = new UnmanagedMemoryStream(p, data.Length)) { var reader = new ResourceReader(stream); foreach (var entry in reader) { /* reading entries */ } }

Creating Complex Objects Exploration of constructor/mutator method sequences Testing with class invariants

Object Creation: Class Invariants Write class invariant as boolean-valued parameterless method Refers to private fields Must be placed in implementation code Exploration of valid states by setting public/private fields May include states that are not reachable

Example: ArrayList Class invariant specification: public class ArrayList { private Object[] _items; private int _size; ... [ContractInvariantMethod] // attribute comes with Contracts protected void Invariant() { Contract.Invariant(this._items != null); Contract.Invariant(this._size >= 0); Contract.Invariant(this._items.Length >= this._size); } How many tests do you expect to cover all reachable branches for this scenario?

Example: ArrayList PUT: [PexMethod] public void ArrayListTest(ArrayList al, object o) { int len = al.Count; al.Add(o); PexAssert.IsTrue(al[len] == o); } How many tests do you expect to cover all reachable branches for this scenario?

Example: ArrayList Generated Test: [TestMethod] public void Add01() { object[] os = new object[0]; // create raw instance ArrayList arrayList = PexInvariant.CreateInstance<ArrayList>(); // set private field via reflection PexInvariant.SetField<object[]>(arrayList, "_items", os); PexInvariant.SetField<int>(arrayList, "_size", 0); // invoke invariant method via reflection PexInvariant.CheckInvariant(arrayList); // call to PUT ArrayListTest(arrayList, null); } How many tests do you expect to cover all reachable branches for this scenario?